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732 Commits
Author SHA1 Message Date
Mathias Rainer Schmidt 4d2456b7a2 - deleted Qfunction 2026-08-14 11:33:27 -07:00
Mathias Rainer Schmidt e3772b49be - update 2026-08-11 14:39:30 -07:00
Mathias Rainer Schmidt 1e89d06c70 Merge branch 'dfem-dev' into Rref_TO 2026-08-04 14:11:44 -07:00
Mathias Rainer Schmidt 0fa991a460 -new version 2026-08-04 14:10:12 -07:00
Julian Andrej cc94176f57 use local apply for global mode 2026-08-04 13:32:23 -07:00
Julian Andrej 8f1b56b539 add functional gradient tests 2026-08-04 13:03:26 -07:00
Julian Andrej 6aa804b54b performance with static loop bounds 2026-08-04 13:01:34 -07:00
Julian Andrej 98266d97b9 Merge branch 'dfem-dev' of github.com:mfem/mfem into dfem-dev 2026-08-04 11:57:40 -07:00
Julian Andrej 24df6d251d bugs in assemble 2026-08-04 11:57:15 -07:00
Julian Andrej b5e11d6e77 add variations to benchmarks 2026-08-04 11:57:01 -07:00
Mathias Rainer Schmidt a1b0651261 Merge branch 'dfem-dev' into Rref_TO 2026-08-04 10:47:16 -07:00
Mathias Rainer Schmidt eb580cd380 Merge branch 'dfem-dev' into Rref_TO 2026-08-04 10:44:58 -07:00
Julian Andrej 47eb62ee72 add functional derivative assemble 2026-08-04 10:44:06 -07:00
Julian Andrej b4d3b754d4 move h2d out of timing 2026-08-03 19:03:42 -07:00
Mathias Rainer Schmidt 2a7e6f03e2 Merge branch 'dfem-dev' into Rref_TO 2026-08-03 13:59:50 -07:00
Julian Andrej 93a57893e2 Merge remote-tracking branch 'refs/remotes/origin/dfem-dev' into dfem-dev 2026-08-03 08:49:56 -07:00
Julian Andrej bf40d8f35f lvector mode and simple benchmark 2026-08-03 08:36:52 -07:00
molinari2 87e7df1222 Merge functional mixed derivative changes from branch 'dfem-hyperelasticity' into dfem-dev 2026-07-31 12:31:55 -07:00
molinari2 61c2e7c5a7 Test 2nd derivative checks all mixed. 2026-07-28 16:07:51 -07:00
molinari2 df3cc63beb Restored dfem-hyperelasticity miniapp. 2026-07-28 16:06:34 -07:00
molinari2 c02b997e05 Fetched updates from dfem-dev. 2026-07-28 15:31:08 -07:00
molinari2 35f0700d73 Mixed derivatives for dFEM functional. 2026-07-28 14:48:49 -07:00
Julian Andrej 0ec98723c3 global cache index change and unit tests 2026-07-27 17:41:04 -07:00
Julian Andrej 3b8edc1657 local qf cache index change 2026-07-27 17:26:11 -07:00
Julian Andrej ab35846618 remove allocation in Mult path 2026-07-27 17:22:32 -07:00
Julian Andrej 7dcc257d97 clarity 2026-07-27 16:50:23 -07:00
Julian Andrej da8d4b2786 hoist invariants out of loop 2026-07-27 16:13:49 -07:00
Julian Andrej 8c736a51bf reorder threads in derivative setup 2026-07-27 16:04:36 -07:00
Julian Andrej a9a98e2c93 avoid divmod indexing 2026-07-27 15:56:31 -07:00
Julian Andrej 5111404b47 optimization pass 2026-07-27 08:58:20 -07:00
Julian Andrej 9b7bfad768 Merge branch 'dfem-dev' of github.com:mfem/mfem into dfem-dev 2026-07-24 12:49:17 -07:00
Julian Andrej 8006dc9c1a implement multiple outputs AssembleDiagonal 2026-07-24 12:49:06 -07:00
Julian Andrej 475ec67308 Updates from dfem-dev 2026-07-24 09:59:42 -07:00
Julian Andrej 666c1d5389 more syncs 2026-07-23 17:11:19 -07:00
Julian Andrej ac7697b374 make -O0 work again 2026-07-23 16:43:31 -07:00
Julian Andrej 8d4897ec65 make -O0 work again 2026-07-23 16:39:36 -07:00
molinari2 5218648fc1 Merge remote-tracking branch 'origin/dfem-hyperelasticity' into dfem-dev 2026-07-23 16:26:49 -07:00
molinari2 af3595c18e astyle 2026-07-22 14:28:27 -07:00
molinari2 bd08300c86 Added gpu flag to multikernel enzyme test 2026-07-22 12:33:38 -07:00
molinari2 dc0b841eba One more fix to Enzyme tests. 2026-07-22 12:18:00 -07:00
molinari2 02f4ea48fb Fixed some gpu tests on Eznyme/dfem. 2026-07-22 11:56:03 -07:00
molinari2 b610b63c4b Changed visibility of device in pgpu_unit_test. 2026-07-22 11:55:40 -07:00
molinari2 7cea347081 Fixed to dimension check in Enzyme-aware forall. 2026-07-22 11:55:14 -07:00
molinari2 2f76f0cc7a Fix for gpu Enzyme tests. 2026-07-22 08:30:39 -07:00
molinari2 2ee8e73d06 Removed old scratch_bank header and use default CreateShadow(). 2026-07-21 17:24:25 -07:00
molinari2 f77069bd45 Conditional behavior based on QF type (if with scratch), extended to GlobalBackend. 2026-07-21 15:15:54 -07:00
molinari2 54115bbbec Initial changes for independently handling QFWithScratch case in dFEM. 2026-07-21 15:01:41 -07:00
molinari2 959c9621e5 Printing in test hyperelasticity 2026-07-21 14:58:31 -07:00
molinari2 ed7eb30b6f Test verbosity 2026-07-21 13:54:27 -07:00
molinari2 11a85623fc Fix enzyme scratch test with qfconst 2026-07-21 13:30:46 -07:00
molinari2 c32754655e Fix for gpu Enzyme tests. 2026-07-21 11:22:01 -07:00
molinari2 17fffcfe75 [WIP] Modified functional registration in hyperelasticity. 2026-07-20 18:06:07 -07:00
molinari2 3b08e80d79 style 2026-07-20 16:23:51 -07:00
molinari2 70c3aaacf9 Added sample SED for simple fiber reinforced materials. 2026-07-20 16:23:51 -07:00
molinari2 ac430f2284 Matched constitutive law from Hooke miniapp. 2026-07-20 16:23:51 -07:00
molinari2 8472c35998 astyle 2026-07-20 16:23:51 -07:00
molinari2 29ac7ecdda Small fix to multiple_outputs unit test. 2026-07-20 16:23:51 -07:00
molinari2 96bec6cea4 dfem-hyperelasticity unit test comparing energy (functional) and stress formulation. 2026-07-20 16:23:51 -07:00
molinari2 3fedd522af Comparison of energy and stress-based formulations. 2026-07-20 16:21:37 -07:00
molinari2 84bf61d7a9 Using tensor IdentityMatrix(), 2026-07-20 16:21:37 -07:00
molinari2 a1e269cc9b dfem Hyperelasticity example using energy-based formulation. 2026-07-20 16:21:37 -07:00
molinari2 7bf23a56dd Changes to enable assembly for dfem functional. 2026-07-20 16:21:37 -07:00
molinari2 062c3c156c Merge branch 'dfem-global-split' into dfem-dev 2026-07-20 14:31:35 -07:00
molinari2 4a49d18cc3 Fix to test_mass assemble diagonal (vector already T-Vec) 2026-07-20 14:15:52 -07:00
molinari2 e3b81f95ac Refactor to move ScratchBank internally. 2026-07-20 14:15:30 -07:00
molinari2 ca2eccb958 Forall fix in hypre_using_gpu when compiling with clang<20+. 2026-07-20 11:39:41 -07:00
molinari2 79910c6750 Style 2026-07-20 11:37:45 -07:00
Julian Andrej fe24f1198d astyle 2026-07-17 08:15:48 -07:00
Julian Andrej 26a762ac66 merge master 2026-07-17 08:08:49 -07:00
Julian Andrej 9f1da23f70 ea for vdim>1 and mixed spaces 2026-07-17 07:58:49 -07:00
Mathias Rainer Schmidt b63320c9dc Merge branch 'master' into Rref_TO 2026-07-16 12:01:35 -07:00
Mathias Rainer Schmidt acec9161fb Merge branch 'master' of https://github.com/mfem/mfem 2026-07-16 12:00:57 -07:00
Mathias Rainer Schmidt d6a05078fd - updated branch 2026-07-16 11:51:35 -07:00
molinari2 8262a9837a Added version with qvector-like wrapper. 2026-07-15 10:17:37 -07:00
molinari2 b0197a33e3 Small test showing split reverse mode in Enzyme. 2026-07-15 09:51:21 -07:00
molinari2 75998f0e50 Moved residual reverse-split stuff to other example. 2026-07-15 09:50:44 -07:00
molinari2 45d46509c1 Moved some tests to tests/enzyme. 2026-07-14 12:36:13 -07:00
molinari2 c413a2887c Modified DifferentiableOperator for persisting scratch. 2026-07-13 15:54:31 -07:00
molinari2 b1b6818960 Some modification for persistency of scratch vars in GlobalQF. 2026-07-13 12:27:00 -07:00
molinari2 783511bc45 Added templated Global layout to ScratchBank and test. 2026-07-10 18:41:48 -07:00
molinari2 1017a8d681 Enzyme test for scratch persistence with multiple kernels. 2026-07-10 12:53:23 -07:00
molinari2 804853f5fa Refactor of dfem-scratch example. 2026-07-10 12:52:52 -07:00
Mathias Rainer Schmidt 01dd1c9b57 - minor changes 2026-07-10 12:35:29 -07:00
molinari2 dac90ec028 Added SetScratch for multiple scratch vecs with same size. 2026-07-08 17:02:40 -07:00
molinari2 5e0ed819e8 Unified interface for different QF with scratch. 2026-07-08 16:39:43 -07:00
molinari2 c5952ecf46 Extended test to multiple sizes. 2026-07-08 16:14:37 -07:00
molinari2 229efc4a98 Moved to tests + refactor. 2026-07-08 15:25:09 -07:00
molinari2 ad2b590339 Initial development of scratch bank. 2026-07-08 11:57:37 -07:00
molinari2 7282b47016 Working global+scratch playground. 2026-07-08 10:49:31 -07:00
molinari2 9dcf5fabb5 Modified scratch example before porting shadow fixes. 2026-07-08 10:17:26 -07:00
molinari2 64aa6eb040 examples with global + scratch (not working) 2026-07-08 10:17:26 -07:00
molinari2 eb957ed78a scratch from nnz external data 2026-07-08 10:17:26 -07:00
molinari2 54b32baa1d Added some alternative setups to scratch example. 2026-07-08 10:17:26 -07:00
molinari2 0f1df77fe9 Test global qf with splitting and scratch mem. 2026-07-08 10:17:26 -07:00
Julian Andrej ba3dde5dcc Update util.hpp 2026-07-07 13:48:32 -07:00
camierjs f0b56d6bd3 Compilation w/o MFEM_USE_ENZYME, style 2026-07-07 07:13:35 -07:00
andrej1 bc14c40084 make qfunction a dependent variable 2026-07-06 15:38:46 -07:00
andrej1 67ba6a755f Update forall.hpp 2026-07-06 08:39:10 -07:00
andrej1 c33759b9e5 callback changes 2026-07-06 08:23:52 -07:00
Julian Andrej 244642d3e6 global gpu fixes 2026-06-26 17:07:05 -05:00
Julian Andrej 45b379a37e style 2026-06-26 11:23:25 -07:00
Julian Andrej 7c4810c7b1 remove references and correct threadblocks 2026-06-26 11:02:05 -07:00
Julian Andrej 95a502344d assert 2026-06-26 10:47:44 -07:00
Julian Andrej 18753362a7 syntax 2026-06-26 10:45:06 -07:00
Julian Andrej 442fbd78b0 gpu path 2026-06-26 10:44:31 -07:00
Julian Andrej 52021d2484 more wrapper changes 2026-06-26 10:34:33 -07:00
Julian Andrej 3b1aa9e3db update forall wrappers 2026-06-26 10:27:14 -07:00
Julian Andrej a0a5bbb1ae added global enzyme forall compatibility layer 2026-06-26 08:55:10 -07:00
Julian Andrej aab443b78d dedicated functionalvalue fieldoperator 2026-06-25 15:19:33 -07:00
Julian Andrej 1cfe7721d9 guard global qfunction from device 2026-06-24 10:19:01 -07:00
Julian Andrej f044e73313 add enzyme variable to host/device macro 2026-06-24 10:18:49 -07:00
Julian Andrej 91a41a30aa make lcoal backend defautl 2026-06-24 10:18:39 -07:00
Julian Andrej ea61e0180c bugfixes 2026-06-23 14:43:29 -07:00
Julian Andrej 32fd898fb9 comparison warning 2026-06-22 07:33:26 -07:00
Julian Andrej 08408bff1e reenable tests 2026-06-22 07:33:19 -07:00
Julian Andrej a97d4d2f6f cleanup 2026-06-20 10:06:32 -07:00
camierjs 724e414848 Merge branch 'dfem-dev' of github.com:mfem/mfem into dfem-dev 2026-06-19 13:41:50 -07:00
camierjs 4005340f30 Avoid Enzyme global w/ mfem::forall tests, cleanup global derivative setup 2026-06-19 13:41:49 -07:00
camierjs 795adb0b21 Avoid too much shared memory for derivative_assemble 2026-06-19 13:40:38 -07:00
camierjs 48cb7acd9e Add ∂FEM local QFunction action specializations for bench 2026-06-19 09:50:02 -07:00
camierjs da7d6b1276 Add ∂FEM 'tmop' skeleton tests, fix style 2026-06-19 09:21:02 -07:00
camierjs bdb1042f14 Guard ∂FEM functionals only with Enzyme 2026-06-19 08:40:36 -07:00
camierjs ce307e0081 Merge branch 'dfem-dev' of github.com:mfem/mfem into dfem-dev 2026-06-19 08:34:40 -07:00
camierjs 9973bc7f75 Fix and simplify ∂FEM bench 2026-06-19 08:34:18 -07:00
Julian Andrej d3a9c198fc Merge branch 'dfem-dev' of github.com:mfem/mfem into dfem-dev 2026-06-19 08:10:06 -07:00
Julian Andrej eeff282330 hacky fix 2026-06-19 08:09:55 -07:00
camierjs 3562c476bb Add Eval 2D/3D vector support, add vector mass tests 2026-06-19 08:03:50 -07:00
Julian Andrej 53200e682e more second derivatives 2026-06-18 18:35:59 -07:00
Julian Andrej e57d86b7b9 second derivative prototype 2026-06-18 08:30:56 -07:00
camierjs 6cf6db31a2 Merge branch 'master' into dfem-dev 2026-06-16 17:47:36 -07:00
camierjs 82e9af5750 Remove instantiated fallback kernels 2026-06-16 17:33:02 -07:00
Julian Andrej e03db70e0f Merge branch 'tuple-refactor' into dfem-multiple-outputs 2026-06-15 08:56:28 -07:00
Julian Andrej 8dcec41e68 resolve tensor issues 2026-06-15 08:56:03 -07:00
Julian Andrej e807fc5c99 Merge branch 'tensor-refactor' into dfem-multiple-outputs
# Conflicts:
#	linalg/tensor.hpp
2026-06-15 08:40:06 -07:00
Julian Andrej d0488784a3 Merge pull request #5352 from mfem/dfem-multiple-outputs-kernels
∂FEM multiple outputs kernels
2026-06-15 08:27:28 -07:00
camierjs 655c1483cf Use mfem::out instead of std::cout in unit tests 2026-06-13 12:56:53 -07:00
camierjs b41fcbf961 Merge branch 'dfem-multiple-outputs' into dfem-multiple-outputs-kernels 2026-06-13 12:53:11 -07:00
Julian Andrej c8ca8ea5d8 Merge branch 'dfem-multiple-outputs' of github.com:mfem/mfem into dfem-multiple-outputs 2026-06-12 16:12:14 -07:00
Julian Andrej d676d119f0 functional stuff 2026-06-12 16:11:53 -07:00
camierjs cfcd07c29a Re-avoiding 'number of sections exceeded object file format limit' error in test_jvp_vjp 2026-06-12 13:16:51 -07:00
camierjs 71a3684d8a Avoiding 'number of sections exceeded object file format limit' error in test_jvp_vjp 2026-06-12 12:35:07 -07:00
camierjs 607d1f0b06 Re avoiding 'number of sections exceeded object file format limit' error 2026-06-12 10:30:48 -07:00
camierjs a2b52e8942 Avoid too many instantiations in fallbacks 2026-06-12 10:26:14 -07:00
camierjs aa11f6c0e8 Simplify dFEM ultiple inputs tests 2026-06-12 09:33:19 -07:00
camierjs 8313768ca1 Avoid DYNAMIC_SECTION try for MSVC C1128 'number of sections exceeded object file format limit' 2026-06-12 06:41:47 -07:00
camierjs 0a1f2b53d1 Merge branch 'dfem-multiple-outputs' into dfem-multiple-outputs-kernels 2026-06-11 19:35:38 -07:00
camierjs a2253b7bca Style and cleanup local actions 2026-06-11 12:51:08 -07:00
camierjs f7ab2c8ac4 MSVC avoid bigobj, cleanup ∂FEM unit test tags 2026-06-11 11:58:36 -07:00
camierjs dd1d941813 Merge branch 'master' into dfem-multiple-outputs 2026-06-11 10:26:28 -07:00
camierjs c0710a7e0c Add a Dispatch Kernel By Q1D for the fallbacks 2026-06-11 10:24:50 -07:00
camierjs 6ab5ec543c Remove debug traces in dFEM benchmarks 2026-06-11 09:58:35 -07:00
camierjs c81d4e8d1f Remove unused headers and SharedMemoryInfo 2026-06-11 09:40:04 -07:00
camierjs a70daf6123 Fix MSVC not allowed character in an identifier and fops undeclared identifier 2026-06-11 09:16:04 -07:00
camierjs 0f6774eba2 Fix FP32 build 2026-06-11 08:17:15 -07:00
camierjs 1cf9cdc6d8 Add tests unit dfem multiple inputs with Values and Gradients 2026-06-10 19:17:42 -07:00
camierjs 052462e98e wip tests unit dfem multiple inputs 2026-06-10 18:44:16 -07:00
camierjs 77f74936ef Merge branch 'master' into dfem-multiple-outputs-kernels 2026-06-10 17:03:44 -07:00
John Camier 71e3120f78 Merge branch 'master' into tensor-refactor 2026-06-09 06:54:27 -07:00
John Camier dbb5fe2f0e Merge branch 'master' into tuple-refactor 2026-06-09 06:54:17 -07:00
camierjs 08acd54f51 Avoid MSVC error C2065: 'outputs': undeclared identifier 2026-06-06 18:08:56 -07:00
camierjs 65a476c7b7 Revert with codecov-action@v5 2026-06-06 17:03:41 -07:00
camierjs 4245965c46 Try with codecov-action@v5 2026-06-06 16:33:57 -07:00
camierjs 9c2e25041f Fix ∂FEM mtop miniapp include 2026-06-06 15:05:46 -07:00
camierjs 431685728e Fix dFEM MPI runs 2026-06-06 14:50:07 -07:00
camierjs 0d9552d9d5 Fix dFEM Operator Mult 2026-06-06 14:07:02 -07:00
camierjs 783677b95d wip dFEM prolongations 2026-06-06 12:57:17 -07:00
camierjs 72e05eadd1 Re-fix win32 function dllimport, address tensors older compiler errors, avoid failing JIT example 2026-06-06 08:27:06 -07:00
camierjs 8afa3a3bfc Fix win32 definition of dllimport function not allowed 2026-06-05 17:41:09 -07:00
Tzanio Kolev 94da954917 Merge branch 'master' into tuple-refactor 2026-06-05 16:01:05 -07:00
camierjs cd887460ae Update cmake lists and style 2026-06-05 11:45:55 -07:00
camierjs 07cd749016 Avoid JIT playground w/o Proteus 2026-06-04 13:09:40 -07:00
camierjs 92c72e929f Fix pedantic unused variables 2026-06-04 11:24:54 -07:00
camierjs 2e59af76eb Fix MPI guards for serial runs 2026-06-04 10:27:24 -07:00
camierjs d18985cfd5 Fix out-of-source build and mtop dFEM solver 2026-06-04 09:45:03 -07:00
camierjs e5ecfdb9fc Fix tensor arrays guards & unused 2026-06-04 09:08:32 -07:00
camierjs 9ed5391919 Rename test_jvp_vjp and variables naming convention 2026-06-04 08:55:50 -07:00
camierjs 617c5fb295 Fix doxygen documentation 2026-06-04 07:33:08 -07:00
camierjs 81c4ce6a0c Cleanup dbg traces and meld back 2026-06-04 06:08:28 -07:00
camierjs a3967f36ce Cleanup tests, bring HO local kernels, add local specialization utils 2026-06-03 17:42:57 -07:00
camierjs d90d870868 Re-introduced 'enzyme_dup' vs. 'enzyme_const' for test_multiple_outputs 2026-06-03 15:41:23 -07:00
camierjs a1f93f45d7 Revert enzyme_const/enzyme_dup w/ shadow work-around 2026-06-03 15:04:08 -07:00
camierjs 4407597c3e Add LO/HO instantiations 2026-06-03 12:03:52 -07:00
Tzanio Kolev 9e18c64f52 Merge branch 'master' into tensor-refactor 2026-06-02 10:08:03 -07:00
camierjs 0e50038e5f Add dFEM GPU multiple outputs tests 2026-06-01 20:33:08 -07:00
camierjs d169026296 Add dFEM GPU functional tests 2026-06-01 20:09:39 -07:00
camierjs 94cb8fb05c Fix dFEM GPU derivative transposed tests 2026-06-01 20:03:58 -07:00
camierjs 68c51adb5c dFEM GPU dual tests 2026-06-01 18:47:46 -07:00
camierjs 3be5ec1dfa Fix dFEM DIFFUSION GPU action tests 2026-06-01 18:17:05 -07:00
camierjs e8e5d0a322 Cleanup 2026-06-01 18:02:50 -07:00
camierjs 67148db340 Merge branch 'dfem-multiple-outputs-kernels' of github.com:mfem/mfem into dfem-multiple-outputs-kernels 2026-06-01 17:54:23 -07:00
camierjs e795976b44 Fix dFEM mixed MASS GPU tests 2026-06-01 17:54:20 -07:00
camierjs ca79d9ac43 Merge branch 'dfem-multiple-outputs-kernels' of github.com:mfem/mfem into dfem-multiple-outputs-kernels 2026-06-01 17:46:51 -07:00
camierjs a989a27f6b wip dFEM mixed MASS GPU tests 2026-06-01 17:40:07 -07:00
camierjs 2b8f4f15bc wip dFEM mass tests: Linearized, Diagonal 2026-06-01 17:12:01 -07:00
camierjs 6c46647b43 wip debug device pass 2026-06-01 16:24:10 -07:00
camierjs 5a4c6ffdb7 wip dFEM MASS GPU tests 2026-06-01 11:59:55 -07:00
camierjs eb8aa62c67 wip GPU mass 2026-06-01 11:10:28 -07:00
John Camier 85a0d18caa Merge branch 'master' into tensor-refactor 2026-06-01 08:08:02 -07:00
camierjs f95970b551 Fix parallel adjoint consistency test 2026-06-01 07:10:20 -07:00
camierjs ca77f8245a Avoid Enzyme forward-diff and mfem::forall 2026-05-31 18:39:53 -07:00
camierjs 366516b757 Simplify local derivative assembly 2026-05-31 17:24:01 -07:00
camierjs 6c05daab28 Cleanup local derivative assembly 2026-05-31 16:55:49 -07:00
camierjs 1d58190e65 Simplify derivative assembly 2026-05-31 13:55:20 -07:00
camierjs ecd95ce33f wip assembly 2026-05-31 12:55:18 -07:00
camierjs f0aebb96d3 Cleanup 2026-05-31 10:31:37 -07:00
camierjs 384f21655b Add Local Specializations for Low Order kernels 2026-05-31 10:16:45 -07:00
camierjs b73939af33 Add last stage extern templates for kernels 2026-05-31 08:24:25 -07:00
camierjs 9da29918d7 Re-enable dFEM mass global tests, rework derivative assembly 2026-05-30 18:24:08 -07:00
camierjs c485588bcb wip device 2026-05-30 17:26:27 -07:00
camierjs 202afb05ae Use Vector for native_dual_t 2026-05-30 17:08:11 -07:00
camierjs 7246c63e76 dFEM device wip 2026-05-30 16:37:00 -07:00
camierjs d2e9a25cde Add more adjoint tests and mass use both global and local backends 2026-05-30 14:45:29 -07:00
camierjs 5dabca7a9f dFEM globals apply with cache, cleanup 2026-05-30 12:43:50 -07:00
camierjs 9e736b2220 wip simplify derivative apply transpose 2026-05-30 08:57:06 -07:00
camierjs 04bca1b63a dFEM Global prelude cleanup 2026-05-29 17:30:13 -07:00
camierjs 584b8bd746 wip derivative assemble, even less shared memory 2026-05-29 17:08:18 -07:00
camierjs 2ffd8fe82a wip derivative assemble, less shared memory 2026-05-29 16:52:39 -07:00
camierjs 7fc1b24e17 wip derivative assemble 2026-05-29 15:55:50 -07:00
camierjs e81e43ed7a Derivative assemble diagonal LO/HO kernels 2026-05-29 13:25:12 -07:00
camierjs 1ce7e4e107 Fix adjoint Enzyme non-linear consistency tests, wip derivative apply transpose 2026-05-29 12:23:09 -07:00
camierjs ec12d3133d wip Derivative Setup/Apply 2026-05-29 08:20:47 -07:00
camierjs 0a4ddccf50 Using Inputs/Outputs/Derivatives for dFEM diffusion tests 2026-05-29 06:53:55 -07:00
camierjs 2eaea9f097 Merge branch 'dfem-multiple-outputs' into dfem-multiple-outputs-kernels 2026-05-29 06:48:34 -07:00
camierjs 0219a408ff Re-enable LocalQFImpl for GlobalQFImpl 2026-05-29 06:47:09 -07:00
camierjs e8889dd69a Cleanup DerivativeAssemble 2026-05-28 12:03:15 -07:00
camierjs 17a628c202 wip DerivativeAssemble 2026-05-28 11:53:46 -07:00
camierjs 5837ac9ab2 Use new driver for derivative assemble diagonal, add mass diagonal tests 2026-05-28 10:14:47 -07:00
Julian Andrej bd85ce1cc6 syntax sugar 2026-05-28 09:21:11 -07:00
camierjs 68b11fcdc1 Cleanup 2026-05-28 09:12:59 -07:00
camierjs 96432772fb Remove now unused 'has_cached_derivative' 2026-05-28 09:04:20 -07:00
camierjs 90bd3527ca Consolidate util functions for local qf backend 2026-05-28 09:02:07 -07:00
camierjs 7e03baa836 Use new driver for derivative apply 2026-05-28 08:50:52 -07:00
camierjs 4679e335b5 Use MFEM_ABORT in derivative_assemble_diagonal 2026-05-28 07:55:43 -07:00
camierjs 937e7568fb Swap input_size_on_qp as array 2026-05-28 07:50:41 -07:00
camierjs f7a20ad557 Cleanup global_qf prelude 2026-05-27 17:39:24 -07:00
camierjs 18acad4ea2 Rename global QF derivative_action 2026-05-27 17:38:05 -07:00
camierjs c716177716 Add new driver in DerivativeSetup, enable mass, multiple outputs, divergence tests.
Enable duals in global Q-functions.
2026-05-27 17:36:07 -07:00
camierjs e920d87133 DerivativeApplyTranspose with new kernels driver 2026-05-27 16:28:34 -07:00
camierjs 5d74f8d098 Added dual transpose/cache path 2026-05-27 15:27:38 -07:00
camierjs df86e132b6 Add dFEM consistency unit test 2026-05-27 13:21:19 -07:00
Tzanio Kolev 6ce18b2005 Merge branch 'master' into tuple-refactor 2026-05-27 09:24:12 -07:00
Julian Andrej c09b6d8a1d make style 2026-05-26 19:49:07 -07:00
Julian AndrejandCopilot Autofix powered by AI 19d9175833 replace tuple implementation with generic sized
Apply suggestions from code review

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>

Add tuple include

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>

use move instead of copy

properly do forwards
2026-05-26 17:41:13 -07:00
Julian Andrej 9fc8398f9a guard array storage size from being zero 2026-05-26 17:26:42 -07:00
Julian Andrej 37dc4c9b08 review changes 2026-05-26 17:05:45 -07:00
Tzanio Kolev 16665bbe4e Merge branch 'master' into tensor-refactor 2026-05-26 10:33:20 -07:00
camierjs 1d984ba63c Add 2D LO backend 2026-05-24 20:12:24 -07:00
camierjs 70eb97b315 Default DIM for LocalQFLOBackend 2026-05-24 17:00:43 -07:00
camierjs 6b5a79ca5f Cleanup 2026-05-24 13:03:41 -07:00
camierjs 654533ac95 Add dFEM headers 2026-05-24 12:47:14 -07:00
camierjs 8312fc66fd Fix Enzyme multiple outputs tests, cache per integrator, populate primal storage and sync cache layout 2026-05-24 12:39:03 -07:00
camierjs 6664566f63 Fix and re-use apply_qpdc for mixed tests 2026-05-24 08:42:06 -07:00
camierjs e976d6155c Cleanup 2026-05-24 07:21:12 -07:00
camierjs d60f9d1659 Rename, cleanup, Enzyme derivative for HO backend 2026-05-23 17:26:59 -07:00
camierjs 194a4f1b57 wip Enzyme derivative for LO backend 2026-05-23 16:45:50 -07:00
camierjs 5c12b17451 dFEM Derivative 2D/3D w/ dual numbers 2026-05-23 16:13:56 -07:00
camierjs a8ef8698ef wip derivative 2D 2026-05-23 15:50:09 -07:00
camierjs 549d8f34c5 Action Linearized 3D 2026-05-23 15:39:12 -07:00
camierjs 758e312404 Cleanup dFEM instantiation guards, GPU benchmark runs 2026-05-23 15:07:57 -07:00
camierjs aa655137f9 Fix refactored WriteGradient for the dFEM benchmarks 2026-05-23 14:02:37 -07:00
camierjs b2debca631 Update dFEM multiple_outputs tests 2026-05-23 13:39:05 -07:00
camierjs 32f4223960 Re-enable lvector_interface tests 2026-05-23 13:29:03 -07:00
camierjs 30b964c9e1 Enable, filter dFEM diffusion, mass, divergence, functional 2026-05-23 13:06:12 -07:00
camierjs c8656fb0c4 Simplify qf_local_action_ho 2026-05-23 12:51:10 -07:00
camierjs 2f192f735c wip dFEM 2D vector action 2026-05-23 10:51:34 -07:00
camierjs 3719d88d0b wip dFEM action 2D/3D 2026-05-23 08:29:24 -07:00
camierjs bd326bcf95 wip integrating local_qf action: output gradient rank 1 only 2026-05-22 18:22:41 -07:00
camierjs ad3854dce2 Filter dFEM diffusion test w/o Enzyme 2026-05-22 17:43:49 -07:00
camierjs 841584b3b0 Report qf_global_kernels changes to default backend 2026-05-22 17:21:41 -07:00
camierjs 0f163b42af Merge branch 'dfem-multiple-outputs' into dfem-multiple-outputs-kernels 2026-05-22 13:57:53 -07:00
camierjs 0f893525ce Merge branch 'master' into dfem-multiple-outputs-kernels 2026-05-22 13:12:14 -07:00
Julian Andrej 356028d825 Merge branch 'dfem-multiple-outputs' of github.com:mfem/mfem into dfem-multiple-outputs 2026-05-21 16:27:22 -07:00
Julian Andrej 5a289baaa3 reverse dtq tensor logic 2026-05-21 16:13:19 -07:00
Veselin Dobrev bdc9c046d1 Merge branch 'master' into dfem-multiple-outputs 2026-05-20 18:49:29 -07:00
Veselin Dobrev a501e773ad Fix include paths in dfem-minimal-surface.cpp 2026-05-20 18:48:13 -07:00
Julian Andrej 5d7e2b5cfe fix remaining tests in parallel 2026-05-20 10:45:20 -07:00
Julian Andrej 195ec594dc fix parallel for functional 2026-05-20 09:41:12 -07:00
Julian Andrej e2de37f8c3 Merge branch 'dfem-multiple-outputs' of github.com:mfem/mfem into dfem-multiple-outputs 2026-05-19 17:25:57 -07:00
Julian Andrej 338830466e fix segfault 2026-05-19 17:25:51 -07:00
Veselin Dobrev 99ea6dfb38 Use the shortcut VectorQuadratureSpace::GetVSize() in some places.
Fix header include paths.

Apply style to new files.

Temporarily disable dfem unit tests with `#if 0`:
* test_lvector_interface.cpp
* test_mass.cpp
2026-05-19 17:04:29 -07:00
Veselin Dobrev f0ea9d1232 Merge branch 'vector-quadrature-space-dev' into dfem-multiple-outputs 2026-05-19 15:15:31 -07:00
Veselin Dobrev 95f2e2c47a In class VectorQuadratureSpace, add shortcut method GetVSize(). 2026-05-18 21:09:04 -07:00
Julian Andrej a5a4623e00 change to VectorQuadratureSpace 2026-05-18 16:26:09 -07:00
Julian Andrej cf59d7e17b Merge branch 'vector-quadrature-space-dev' into dfem-multiple-outputs 2026-05-18 15:57:16 -07:00
Julian Andrej 0c488b5c4b adapted miniapp 2026-05-18 15:26:32 -07:00
Veselin Dobrev 60665cd77b Added class VectorQuadratureSpace that represents a vector (multi-component)
version of the scalar (single-component) class QuadratureSpaceBase.
2026-05-18 15:25:39 -07:00
Julian Andrej 27e3c00e51 fix vdim assemble 2026-05-18 14:18:22 -07:00
Julian Andrej 7aa3cbe267 add currently failing test for vdim sparsematrix 2026-05-18 09:43:09 -07:00
camierjs 7d5e8004fa dFEM LocalQF action linearized for mass and diffusion unit tests 2026-05-15 18:38:32 -07:00
camierjs a60e2f46be wip dFEM LocalQF Kernels derivatives 2026-05-15 16:46:26 -07:00
camierjs 35d26afed9 dFEM LocalQF LO fallback fix & dual support 2026-05-15 13:06:12 -07:00
camierjs 1f067707c5 dFEM 2D/3D GPU: benchmarks & unit tests 2026-05-15 12:42:00 -07:00
Julian Andrej 77bcbab7f3 fix issues in local qf derivative apply and add global derivative setup/apply 2026-05-15 09:37:41 -07:00
Julian Andrej f8c5d5821d bugfix 2026-05-15 09:35:44 -07:00
Julian Andrej 8d934ea6b4 bugfix 2026-05-15 09:35:31 -07:00
camierjs 6455e1c933 dFEM 2D local kernels 2026-05-15 09:04:15 -07:00
camierjs 4893c3ab60 wip dFEM test mass 2026-05-14 11:57:26 -07:00
camierjs 96498d748b Cleanup 2026-05-14 11:16:36 -07:00
camierjs af15063705 Merge branch 'dfem-multiple-outputs' into dfem-multiple-outputs-kernels 2026-05-14 10:53:23 -07:00
camierjs e306968c3e dFEM HO benches 2026-05-14 10:24:52 -07:00
camierjs 53cdad536c Simplify is_identity_fop, all dFEM benches 2026-05-14 09:49:16 -07:00
camierjs 4dd41558a1 Simplify mass_qf, support all mass q-functions 2026-05-14 09:35:30 -07:00
camierjs 8bde57fe8b HO only for MQ1 > 8, bench dFEM for mass 2026-05-14 08:53:33 -07:00
camierjs 776fcaa0af fix value write, cleanup & simplify 2026-05-13 21:06:17 -07:00
camierjs 61a3fb3f63 wip value layout 2026-05-13 19:17:16 -07:00
Julian Andrej 1fa7888706 fixes for transpose functional computation 2026-05-13 10:48:57 -07:00
camierjs 65e92ff2a0 Cleanup 2026-05-13 07:33:28 -07:00
camierjs bf27be2fe5 Cleanup 2026-05-13 06:07:58 -07:00
camierjs 0db1959daa wip value tests 2026-05-12 18:00:46 -07:00
camierjs ef4f3f274b Remove unused code 2026-05-12 11:47:48 -07:00
camierjs 79343b4949 Rename & simplify 2026-05-12 11:25:04 -07:00
camierjs b8ddb61be3 Simplify metadata 2026-05-12 10:52:16 -07:00
camierjs ad488edf55 Simplify metadata 2026-05-12 10:41:11 -07:00
camierjs 1926bb5e17 Cleanup 2026-05-12 10:37:11 -07:00
camierjs c809c833f8 Simplify and add header copyright 2026-05-12 10:10:40 -07:00
camierjs f8d003bda5 Cleanup unused code from using reg tuple 2026-05-12 09:52:21 -07:00
camierjs f931e75579 Fix dfem backends global_qf kernels has_cached_derivative 2026-05-12 07:57:09 -07:00
camierjs 581b16f33c Add dFEM Diffusion punit tests w/ LO/HO 3D backends 2026-05-11 16:50:21 -07:00
camierjs fcb82b850a style 2026-05-11 15:25:49 -07:00
camierjs 6f616e6849 Merge remote-tracking branch 'origin/dfem-multiple-outputs' into dfem-multiple-outputs-kernels 2026-05-11 15:22:23 -07:00
Julian Andrej 66e63180fc MultiVector const ref constructor 2026-05-11 13:31:18 -07:00
camierjs 3e3f9e3c88 Cleanup, rename & simplify 2026-05-10 17:17:58 -07:00
camierjs 416eae77c0 Cleanup GPU local QF, add p=8 for HO only 2026-05-10 16:58:52 -07:00
camierjs 5f1cd5e9f4 fix GPU local QF HO w/ backend reg traits 2026-05-10 16:27:16 -07:00
camierjs 6c93a724df wip GPU local QF HO 2026-05-10 15:51:31 -07:00
camierjs a26743936c wip GPU local QF HO 2026-05-10 15:03:42 -07:00
camierjs 2da32d4c10 wip GPU local QF 2026-05-10 13:56:32 -07:00
camierjs 51492fd1e1 rename local LO/HO kernel backend files 2026-05-10 10:50:39 -07:00
camierjs 2dd3b5339e wip local HO kernel backend 2026-05-10 10:45:49 -07:00
camierjs 0af2ec03c7 wip local LO kernel backend 2026-05-10 10:29:08 -07:00
camierjs d9ae476e6f Fix local_qf kernels HO 2026-05-10 09:37:57 -07:00
camierjs b41c0815bb Simplify & cleanup local_qf kernels HO 2026-05-10 09:35:16 -07:00
camierjs 3520fce371 Simplify & cleanup local_qf kernels 2026-05-10 08:33:11 -07:00
camierjs 53c390432d Simplify low order kernels with unique tuple register args 2026-05-10 06:57:17 -07:00
camierjs b1484d6471 cleanup 2026-05-10 05:37:56 -07:00
camierjs 5eaaa05ab7 Fix CUDA runs with regs3d_vd device wrapper and allow to optin for for shared mem 2026-05-09 17:36:18 -07:00
camierjs 6d6771c0ed fix use of specializations 2026-05-09 15:02:22 -07:00
camierjs e519e1946b wip high kernels 2026-05-09 14:53:03 -07:00
camierjs a0087b7152 wip low kernels 2026-05-09 14:50:14 -07:00
camierjs 205595aac2 wip low/high kernels 2026-05-09 14:32:11 -07:00
camierjs 7f5d5923a3 wip low/high kernels, cleanup 2026-05-09 12:52:00 -07:00
camierjs 301bd7a680 wip MFStiffnessIntegrator 2026-05-09 09:08:11 -07:00
camierjs c7f8bea215 wip low/high kernels 2026-05-09 07:14:31 -07:00
camierjs ba7e52d707 wip low/high orders 2026-05-08 20:47:00 -07:00
camierjs bea47b834f wip qf-function metadata 2026-05-08 17:10:35 -07:00
camierjs 46e7317ef1 Split low/high orders 2026-05-08 16:22:27 -07:00
camierjs b2c569925b Cleanup 2026-05-08 15:07:48 -07:00
camierjs 1b457f045e Merge branch 'dfem-multiple-outputs' into dfem-multiple-outputs-kernels 2026-05-08 14:57:24 -07:00
Julian Andrej 2dfdabcbcf cleanup 2026-05-08 14:39:54 -07:00
camierjs 4d63d4c7b6 meld back toward target 2026-05-08 13:28:22 -07:00
camierjs e59a84509c meld back toward target 2026-05-08 13:11:08 -07:00
camierjs 40dd411d42 Remove specific instruction files 2026-05-08 13:10:50 -07:00
camierjs 9511c087f8 Merge branch 'dfem-multiple-outputs' into dfem-multiple-outputs-kernels 2026-05-08 12:40:59 -07:00
camierjs d80c254f35 Back to using future::tuple 2026-05-08 12:29:51 -07:00
Julian Andrej dc3d947d26 proper diagonal assemble 2026-05-08 10:53:54 -07:00
camierjs ea250a41c4 wip meld back 2026-05-08 10:26:39 -07:00
camierjs 73d2d51a60 Meld back with renaming and w/o mono outputs 2026-05-08 09:37:22 -07:00
camierjs 5a0d1eba4c Rename files 2026-05-08 09:36:33 -07:00
Julian Andrej fe31fbe9e0 diagonal assemble 2026-05-08 08:56:12 -07:00
camierjs d7d5d80eae Fix warnings and remove multi Mult/GetGradient virtuals from operators 2026-05-08 06:52:28 -07:00
camierjs 94701457f2 Propagate merge changes 2026-05-08 05:55:32 -07:00
camierjs e0c12f4008 Merge branch 'dfem-multiple-outputs' into dfem-multiple-outputs-kernels 2026-05-08 05:54:28 -07:00
Julian Andrej 375dfdd51e transpose 2026-05-07 13:10:13 -07:00
Julian Andrej 768f3a567e naming 2026-05-07 07:21:02 -07:00
Julian Andrej fe27a78596 fix derivativeoperator behavior 2026-05-06 16:25:46 -07:00
Julian Andrej ac68a241b2 fix 2026-05-06 16:25:29 -07:00
Julian Andrej 4f57001be5 divergence derivative is buggy 2026-05-06 16:05:50 -07:00
Julian Andrej 0fdb336a3d revive mixed tests 2026-05-06 14:56:04 -07:00
Julian Andrej f7d874b8e2 vector tests 2026-05-06 14:43:46 -07:00
camierjs fd197d55e0 dFEM wip generic GPU runs 2026-05-06 12:52:18 -07:00
Julian Andrej a7e3b3d0c2 reorder lops 2026-05-06 09:57:14 -07:00
Julian Andrej 42b8c9ab4b caching and assemble 2026-05-06 09:43:53 -07:00
camierjs a6664e556d Back to using QuadratureFunction 2026-05-06 07:55:58 -07:00
camierjs 3e764bd06e Merge branch 'dfem-multiple-outputs' into dfem-multiple-outputs-kernels 2026-05-06 07:55:28 -07:00
Julian Andrej b4788ac05b caching 2026-05-06 07:23:31 -07:00
Julian Andrej ae58dfe3ff make QuadratureFunction work 2026-05-05 13:15:36 -07:00
Julian Andrej 8e88b832d4 derivatives for local qf 2026-05-05 08:19:19 -07:00
camierjs ff18f29993 wip generic qf local devices poly action cleanup 2026-05-04 20:37:01 -07:00
camierjs fd4d104eae wip eval generic qf local devices poly action 2026-05-04 20:18:03 -07:00
camierjs 65e0d8e197 wip generic qf local devices poly action 2026-05-04 17:49:32 -07:00
camierjs a941b0109a wip generic backends local_qf devices poly action 2026-05-04 15:24:22 -07:00
camierjs 767c3aaf39 Merge branch 'dfem-multiple-outputs' into dfem-multiple-outputs-kernels 2026-05-04 12:54:54 -07:00
Julian Andrej fe49b19a50 tests 2026-05-04 10:50:37 -07:00
camierjs 5d954e8349 Cleanup LocalQFDevicesPolyImpl 2026-05-04 08:45:39 -07:00
Julian Andrej a6c2cd1c26 formatting 2026-05-04 08:22:46 -07:00
Julian Andrej 2813bbf566 update test 2026-05-04 08:20:36 -07:00
Julian Andrej d94bebb31f fix multiple outputs for local qf and add test 2026-05-04 08:14:59 -07:00
camierjs 28abd02668 Melding back 2026-05-03 16:16:32 -07:00
camierjs 631a0d2d7b Cleanup 2026-05-03 16:05:58 -07:00
camierjs 954c962306 Cleanup 2026-05-03 15:52:28 -07:00
camierjs bc4a48efd6 dFEM outputs kernels GPU runs 2026-05-03 14:32:39 -07:00
camierjs 554485e349 dFEM PA/MF global/local mono/poly 2026-05-03 10:20:45 -07:00
camierjs 1c7fa2839d Moved dFEM backends utils to util_qf 2026-05-03 10:20:16 -07:00
camierjs a59003ea7f dFEM MF local, devices, poly operator wip 2026-05-02 18:01:21 -07:00
camierjs a7a4ade3f0 dFEM MF local, devices, poly operator setup 2026-05-02 17:04:40 -07:00
camierjs 39ac074486 dFEM devices mono/poly backends init 2026-05-02 16:51:00 -07:00
camierjs 3ec411df2f dFEM move devices mono backends 2026-05-02 16:50:55 -07:00
camierjs 3a677eccc1 dFEM local devices backend simplify 2026-05-02 14:47:56 -07:00
camierjs c67156a1ab dFEM simplify action_callback_new signature 2026-05-02 11:46:24 -07:00
camierjs 548a7fa21b Rename dFEM local device backend action 2026-05-02 08:21:23 -07:00
camierjs 6665423e34 dFEM bench with global/local default MF and devices PA 2026-05-02 06:42:33 -07:00
camierjs 19bfb888d2 Merge branch 'dfem-multiple-outputs' into dfem-multiple-outputs-kernels 2026-05-02 04:42:17 -07:00
camierjs 692befefcc dFEM local globals runs with backends 2026-05-01 20:44:19 -07:00
camierjs 810eba0618 wip dFEM local devices backend 2026-05-01 18:40:02 -07:00
Julian Andrej c99e4d1280 full shmem local action 2026-05-01 18:10:19 -07:00
Julian Andrej a13ea95d27 crude local qf impl 2026-05-01 17:40:50 -07:00
camierjs f9cf2dd860 dFEM global benchmarks runs 2026-05-01 15:49:00 -07:00
Julian Andrej 1ddef79954 Merge branch 'dfem-multiple-outputs' of github.com:mfem/mfem into dfem-multiple-outputs 2026-05-01 14:51:42 -07:00
Julian Andrej ebfd6bfcba stage 2026-05-01 14:51:32 -07:00
camierjs 9ea6a591e1 Add extra subdir level in qf backends 2026-05-01 13:20:43 -07:00
camierjs abb2c75c88 dFEM global benchmarks 2026-05-01 10:57:33 -07:00
camierjs bce6adc1f0 Merge branch 'dfem-multiple-outputs' into dfem-bench-global 2026-05-01 09:36:22 -07:00
camierjs 5a3e9a93c2 Merge branch 'master' into dfem-multiple-outputs 2026-05-01 09:30:41 -07:00
Julian Andrej b2bf589c87 jit playground updates 2026-04-29 13:09:32 -07:00
Julian Andrej ac48dfcfa5 update 2026-04-27 16:02:33 -07:00
Mathias Rainer Schmidt 9d3a672969 - updated test 2026-04-27 15:04:00 -07:00
Julian Andrej 5e98b82b26 skeleton 2026-04-20 14:52:41 -07:00
Julian Andrej dfc582149d move files 2026-04-20 10:27:29 -07:00
Julian Andrej 79680d9bc9 reorganizing dfem backends 2026-04-20 10:21:39 -07:00
camierjs cd761775b6 Merge branch 'master' into camierjs-dfem-bench-global 2026-04-14 08:18:20 -07:00
camierjs 109cc7aa03 Cleanup 2026-04-02 09:06:47 -07:00
Julian Andrej faba224c26 jit playground 2026-04-02 08:34:33 -07:00
camierjs ab0836db42 Cleanup dFEM bench orders 2026-04-02 08:16:28 -07:00
camierjs eb1d0b5031 Use NewMemoryAndSize to avoid D2D copies 2026-04-02 07:20:58 -07:00
camierjs f0573545b3 wip Q blocks 2026-04-01 20:40:06 -07:00
camierjs a0747133ff wip prolongation extra copy 2026-04-01 15:03:49 -07:00
camierjs dfe66e08e4 Adding NVTX traces 2026-04-01 13:40:07 -07:00
camierjs 1f0d68c679 CUDA runs 2026-04-01 13:03:17 -07:00
camierjs 4300e71ae2 Factorize dOperatorSetup 2026-04-01 10:26:13 -07:00
camierjs ab5eea2a20 Fix create_descriptors_to_fields_map usage 2026-04-01 10:09:37 -07:00
camierjs ba3c328fd1 Remove warnings 2026-04-01 09:58:28 -07:00
camierjs 89b576b993 Revert default backend, cleanup tuple usage to std one, add devices backend 2026-04-01 09:42:27 -07:00
camierjs 4cf92a8e51 Cleanup kernel dispatch 2026-04-01 06:36:09 -07:00
camierjs 31b4d1e5bf Merge branch 'master' into camierjs-dfem-bench-global 2026-04-01 06:23:28 -07:00
camierjs 6837cb591c Please clangd AddKernelSpecializations 2026-03-31 12:38:25 -07:00
Giorgis Georgakoudis 485121d3ad Use proteus::jit_arg instrumentation 2026-03-30 16:55:34 -07:00
Giorgis Georgakoudis af527e27d1 Update top-level CMakeLists.txt for proteus
- Add target-based path for libProteusPass
- Link with libproteus
2026-03-30 16:51:52 -07:00
Julian Andrej 3e680af733 disable derivatives temporarily 2026-03-30 12:41:16 -07:00
Julian Andrej 4212310405 add proteus 2026-03-30 12:20:44 -07:00
camierjs 66708c83aa dFEM profiling 2026-03-27 18:00:03 -07:00
camierjs 513d0669d9 H100 dFEM global runs 2026-03-27 14:25:11 -07:00
camierjs 070b9b530f dFEM global bench on GPU 2026-03-26 11:15:58 -07:00
camierjs 8861b809e6 Remove remaining NVTX_FMT_HPP 2026-03-25 16:53:51 -07:00
camierjs 1771bcca40 Merge branch 'master' into camierjs-dfem-bench-global 2026-03-25 16:45:14 -07:00
camierjs 3ab0d8357f dFEM util FieldBasisFromWeight HostReadWrite 2026-03-25 16:44:59 -07:00
camierjs 463df47610 Runs 2026-03-25 16:25:41 -07:00
camierjs b40d6efe6f Cleanup 2026-03-25 16:17:13 -07:00
camierjs cbff5ea532 Pre cleanup full WrapOpArg1 2026-03-25 16:11:31 -07:00
camierjs 601db29d9f wip WrapOpArg1 2026-03-25 16:01:46 -07:00
camierjs 4479afdf5c dFEM PA CG running 2026-03-25 12:57:01 -07:00
camierjs 62d3e4994e Cleanup 2026-03-25 09:46:24 -07:00
camierjs 76f9014fd6 Remove nvtx link file 2026-03-25 08:09:34 -07:00
camierjs 75cf276e41 Cleanup traces 2026-03-24 22:27:54 -07:00
camierjs 76d9ae4428 dFEM CG multi outputs and blocks 2026-03-24 22:21:03 -07:00
camierjs 2138b21771 Wip CG solver 2026-03-24 18:22:31 -07:00
camierjs 307cdf279a Wip dop in CG with BlockVector 2026-03-24 16:12:32 -07:00
camierjs 4ebd435a2b Merge remote-tracking branch 'origin/dfem-multiple-outputs-laghos' into camierjs-global 2026-03-24 10:54:45 -07:00
camierjs 05c5e98a90 Update debug traces 2026-03-24 10:49:48 -07:00
camierjs ee0d1fa0b7 Merge branch 'master' 2026-03-24 10:33:06 -07:00
camierjs bf3a40f73e Init mdofs before benchmarks 2026-03-24 10:27:28 -07:00
Mathias Rainer Schmidt 5ea9d086aa -initial commit 2026-03-17 00:07:56 -07:00
Julian Andrej 41aed0e916 cosmetic changes 2026-03-12 08:42:35 -07:00
camierjs fd27a338e4 Cleanup 2026-03-10 09:56:03 -07:00
camierjs a7ef657395 Merge branch 'dfem-multiple-outputs' into dfem-multiple-outputs-laghos 2026-03-10 09:20:36 -07:00
camierjs f7cf475d59 dbg traces 2026-03-10 09:20:02 -07:00
Julian Andrej 9bf156adf2 bugfix 2026-03-10 09:18:45 -07:00
camierjs 4baf621cca Merge branch 'dfem-multiple-outputs' into dfem-multiple-outputs-laghos 2026-03-10 08:36:50 -07:00
Julian Andrej 9f0fcd6b10 custom layouts 2026-03-10 08:10:38 -07:00
camierjs 8d31ada017 wip laghos multi vectors 2026-03-09 20:08:10 -07:00
camierjs 33998bdc23 Merge branch 'dfem-multiple-outputs' into dfem-multiple-outputs-laghos 2026-03-09 17:52:32 -07:00
camierjs 69094094fa tensor ndarrays mutable strides to swap inputs 2026-03-09 17:51:24 -07:00
Julian Andrej 2350a5e9eb typo 2026-03-05 10:52:39 -08:00
Julian Andrej 001c686a19 make rank 0 tensor compatible with real_t 2026-03-05 10:50:33 -08:00
Julian Andrej da9fc85862 support MultiVector 2026-03-04 13:32:19 -08:00
Julian Andrej 996553be3d simplify assert 2026-03-04 12:53:26 -08:00
Julian Andrej ff6715b8b1 Merge branch 'multi-vector-dev' into dfem-multiple-outputs 2026-03-04 12:46:47 -08:00
Julian Andrej 54acbdd395 consistency checks 2026-03-04 10:35:30 -08:00
Julian Andrej 76d4f1942b refactor how bases are created 2026-03-04 07:36:19 -08:00
Julian Andrej 939310203d updates 2026-03-03 15:02:16 -08:00
Julian Andrej 979f08b3eb allow Q-function arguments to be non-const references 2026-03-02 09:14:15 -08:00
Veselin Dobrev 1ed3b48c2e In class MultiVector, remove the need for Memory flag synchronizations
in some cases. This required changes in the internals of the class.

Added some new methods in class MultiVector.
2026-02-26 09:57:21 -08:00
Veselin Dobrev fbd9189e7b Restrist with 'enable_if' the variadic template MultiVector ctor and
MakeRef method to be considered only when the arg types are convertible
to (Vector &).
2026-02-25 19:17:07 -08:00
Veselin Dobrev 1dd889cb16 Add support for constructing and re-constructing MultiVectors to reference
multiple Vectors given as arguments.
2026-02-25 17:44:31 -08:00
Veselin Dobrev 2e8fbd661a Fix a warning in a miniapp. 2026-02-25 14:56:28 -08:00
Veselin Dobrev 6e424dba6e Draft implementation of an array-of-Vectors class where each Vector generally
has a different size and is allocated independently.

The tentative name for the new class is MultiVector.

In class Operator, added new virtual methods Mult() and GetGradient() that
use MultiVectors.
2026-02-25 13:51:43 -08:00
Julian Andrej 60a04e4e4f qdata L to Q 2026-02-23 17:22:52 -08:00
Julian Andrej 8d95a6e5ca qdata 2026-02-23 16:51:58 -08:00
Julian Andrej 10cb466fb2 more stuff 2026-02-23 14:14:41 -08:00
Julian Andrej 5be9de7e95 bugfixes 2026-02-23 09:15:17 -08:00
Julian Andrej a13a4f4d8b more 2026-02-20 14:14:10 -08:00
Julian Andrej bf9b6f4d83 multiple outputs with derivatives 2026-02-19 12:51:30 -08:00
Julian Andrej 91c775eb58 refactor tensor for generic size 2026-02-11 16:08:35 -08:00
Julian Andrej 52b8703b78 bugs 2026-02-06 16:26:43 -08:00
Julian Andrej 69e7820d01 phew 2026-02-06 15:05:03 -08:00
Julian Andrej dbedeecece more refactor 2026-02-05 09:58:24 -08:00
Julian Andrej e8847b80a2 refactor 2026-02-04 13:25:00 -08:00
Julian Andrej 0fe2aece0b enable multiple outputs 2026-01-26 14:58:58 -08:00
camierjs 856d13e9ff Roctx init 2025-07-04 08:00:50 -07:00
camierjs 7763785ed7 Use MFEM_FOREACH_THREAD_DIRECT 2025-07-02 10:29:40 -07:00
camierjs 2baa889917 Merge branch 'master' into dfem-bench 2025-07-02 08:38:17 -07:00
camierjs 2ed1a9eaad BP3/1/6/25 @ 40 MDof/s 2025-06-30 18:02:56 -07:00
camierjs 1545f03a94 Merge branch 'master' into dfem-bench 2025-06-30 16:19:53 -07:00
camierjs 59a5c9fc79 Sync with fem/kernels.hpp, still performance wip 2025-06-24 11:43:05 -07:00
camierjs c389a3c434 Use latest dFEM for benchmark 2025-06-24 11:27:34 -07:00
camierjs ec96a85f86 Merge branch 'master' into dfem-bench 2025-06-24 11:27:15 -07:00
camierjs 81b6b7eeb2 Merge branch 'master'/'dfem-phase-1' into dfem-bench 2025-05-19 16:02:46 -07:00
camierjs 4b5974f600 Fix CMake and dFEM bench 2025-05-19 16:01:16 -07:00
camierjs a6926f4ce6 Merge branch 'dfem-phase1-dev' 2025-05-19 15:54:58 -07:00
camierjs b6e972af79 Merge branch 'master' 2025-05-19 15:49:54 -07:00
Julian Andrej e76ec19775 restructure 2025-05-19 14:46:20 -07:00
Julian Andrej d797322fea path 2025-05-19 08:22:36 -07:00
Julian AndrejandJohn Camier 5a5e34a744 Update fem/dfem/doperator.hpp
Co-authored-by: John Camier <camierjs@gmail.com>
2025-05-19 08:11:13 -07:00
Julian AndrejandJohn Camier 93db7052ff Update fem/dfem/util.hpp
Co-authored-by: John Camier <camierjs@gmail.com>
2025-05-19 08:10:44 -07:00
Julian AndrejandJohn Camier f7170af7bd Update fem/dfem/tuple.hpp
Co-authored-by: John Camier <camierjs@gmail.com>
2025-05-19 08:10:12 -07:00
Julian AndrejandJohn Camier b78eef3eaa Update fem/dfem/tuple.hpp
Co-authored-by: John Camier <camierjs@gmail.com>
2025-05-19 08:10:00 -07:00
Julian Andrej d5decea85c Revert "change default location for enzyme and add instructions"
This reverts commit dea3ae3317.
2025-05-16 12:59:14 -07:00
Julian Andrej dea3ae3317 change default location for enzyme and add instructions 2025-05-16 12:55:04 -07:00
Julian Andrej 33c1e50235 astyle 2025-05-16 12:39:47 -07:00
Julian Andrej 5718ad1b53 cuda compat 2025-05-16 12:38:08 -07:00
Julian AndrejandAndrew Ho 4f3671e253 Update fem/dfem/util.hpp
Co-authored-by: Andrew Ho <ho37@llnl.gov>
2025-05-16 11:58:50 -07:00
Julian AndrejandAndrew Ho 4e08bb1b66 Update fem/dfem/util.hpp
Co-authored-by: Andrew Ho <ho37@llnl.gov>
2025-05-16 11:58:42 -07:00
Julian AndrejandAndrew Ho 69c5016b63 Update fem/dfem/util.hpp
Co-authored-by: Andrew Ho <ho37@llnl.gov>
2025-05-16 11:58:20 -07:00
Julian AndrejandAndrew Ho ce1bf58dc0 Update fem/dfem/doperator.hpp
Co-authored-by: Andrew Ho <ho37@llnl.gov>
2025-05-16 11:58:13 -07:00
Julian AndrejandAndrew Ho 5eb00c9ee6 Update fem/dfem/doperator.hpp
Co-authored-by: Andrew Ho <ho37@llnl.gov>
2025-05-16 11:58:05 -07:00
Julian AndrejandAndrew Ho 1f3b6b95aa Update fem/dfem/util.hpp
Co-authored-by: Andrew Ho <ho37@llnl.gov>
2025-05-16 11:57:58 -07:00
Julian AndrejandAndrew Ho 118db41049 Update fem/dfem/util.hpp
Co-authored-by: Andrew Ho <ho37@llnl.gov>
2025-05-16 11:57:49 -07:00
Julian AndrejandAndrew Ho 8390c3e50b Update fem/dfem/doperator.hpp
Co-authored-by: Andrew Ho <ho37@llnl.gov>
2025-05-16 11:57:40 -07:00
Julian Andrej 168b5179e6 remove findenzyme module 2025-05-16 11:57:11 -07:00
Julian AndrejandAndrew Ho 7697f6d400 Update CMakeLists.txt
Co-authored-by: Andrew Ho <ho37@llnl.gov>
2025-05-16 11:56:11 -07:00
Julian AndrejandJan Nikl 235ebce5d5 Update examples/dfem/minimal_surface.cpp
Co-authored-by: Jan Nikl <nikl1@llnl.gov>
2025-05-16 07:58:47 -07:00
Julian AndrejandJan Nikl e8a09d6499 Update examples/dfem/minimal_surface.cpp
Co-authored-by: Jan Nikl <nikl1@llnl.gov>
2025-05-16 07:57:47 -07:00
Julian AndrejandJan Nikl edc67827d8 Update examples/dfem/minimal_surface.cpp
Co-authored-by: Jan Nikl <nikl1@llnl.gov>
2025-05-16 07:57:34 -07:00
Julian Andrej 9e5cdef2ef add host device 2025-05-14 17:39:40 -07:00
Andrew Ho c2f4a5e248 Updated makefile to work with clang as the cuda compiler 2025-05-14 11:25:59 -07:00
Julian Andrej 72d811b289 device support for fdjacobian 2025-05-14 09:57:18 -07:00
Julian Andrej 43731aa990 memory type for temporary 2025-05-14 09:46:39 -07:00
Julian Andrej 45f59fff3a device memory locations 2025-05-14 09:23:58 -07:00
Julian Andrej 58a4cfa132 cuda compat 2025-05-14 07:43:13 -07:00
Julian Andrej 333dd3f2fd rename ParametricSpace -> ParameterSpace 2025-05-13 13:29:38 -07:00
Julian Andrej c4f7dd77b1 bugs 2025-05-13 13:24:18 -07:00
Julian Andrej f442b83573 whitespace 2025-05-13 11:33:54 -07:00
Julian Andrej 768aaae25d docs 2025-05-13 11:27:36 -07:00
Julian Andrej eab997c557 typo 2025-05-13 11:26:09 -07:00
Julian Andrej 9d73dc487d docs 2025-05-13 11:24:36 -07:00
Julian Andrej 2575ac61ba more comments 2025-05-13 09:08:54 -07:00
Julian Andrej 6130144da1 comments 2025-05-13 08:46:15 -07:00
camierjs 68db31da44 SetMaxOf comments 2025-05-12 18:15:09 -07:00
Julian Andrej 1acbce733c cmake 2025-05-09 11:46:10 -07:00
Julian Andrej b44316049b cmake 2025-05-09 10:41:11 -07:00
Julian Andrej 2e133e8ecb remove serial tests from cmake 2025-05-09 10:36:37 -07:00
Julian Andrej dfb2f4d7f2 typos 2025-05-09 08:41:17 -07:00
Julian Andrej 10e9e4215f cmake 2025-05-09 08:38:46 -07:00
Julian Andrej 8125a211d3 Merge branch 'master' into dfem-phase1-dev 2025-05-08 09:40:48 -07:00
Julian Andrej 818b8db433 switch example to CG 2025-05-07 17:19:36 -07:00
Julian Andrej ad4626edfc leftover comment 2025-05-07 15:51:29 -07:00
Julian Andrej 8d7e8933cf mesh 2025-05-07 15:50:43 -07:00
Julian Andrej 3ad21a409f precision 2025-05-07 15:31:39 -07:00
Julian Andrej b16b550150 corrections 2025-05-07 15:08:11 -07:00
Julian Andrej 102dc8bd02 ifdef 2025-05-07 14:20:41 -07:00
Julian Andrej e306ba0c85 ifdef 2025-05-07 13:44:30 -07:00
Julian Andrej 4b88ad2b0a more minsurface 2025-05-07 13:19:28 -07:00
Julian Andrej d0fb4e342e example draft 2025-05-06 21:06:56 -07:00
Julian Andrej b53d0529db bug 2025-05-06 17:41:48 -07:00
Julian Andrej 8c7988b525 changes 2025-05-06 17:41:22 -07:00
Julian Andrej dfffe4b5e8 rename fops 2025-05-06 09:12:33 -07:00
Julian Andrej 538aa11904 rename fops 2025-05-06 08:56:20 -07:00
Julian Andrej 6fa978af9a rename fops 2025-05-06 08:53:31 -07:00
Julian Andrej 3f81af72f6 rename fops 2025-05-06 08:51:06 -07:00
Julian Andrej 97f1cf08fb docs 2025-05-05 13:45:03 -07:00
Tzanio Kolev d3f1379dc8 Merge branch 'master' into dfem-phase1-dev 2025-05-03 13:46:43 -07:00
Julian Andrej ea6fb52698 bug 2025-05-02 13:09:47 -07:00
Julian Andrej 07a87e369c style 2025-05-02 12:01:08 -07:00
camierjs 53bc415268 Squashed commit of the following:
commit be537728df
Merge: 8cc9eec53 4e5b98b10
Author: camierjs <camierjs@gmail.com>
Date:   Fri May 2 10:37:34 2025 -0700

    Merge branch 'dfem-phase1-dev' into dfem-bench

commit 4e5b98b10f
Author: Julian Andrej <andrej1@llnl.gov>
Date:   Fri May 2 10:05:20 2025 -0700

    doc

commit d4acd906bf
Author: Julian Andrej <andrej1@llnl.gov>
Date:   Fri May 2 09:01:51 2025 -0700

    update brew before enzyme install

commit d751ce66a3
Author: Julian Andrej <andrej1@llnl.gov>
Date:   Fri May 2 08:43:46 2025 -0700

    ci

commit 3f0abd4dfd
Author: Julian Andrej <andrej1@llnl.gov>
Date:   Fri May 2 08:40:45 2025 -0700

    ci

commit 44a423d804
Author: Julian Andrej <andrej1@llnl.gov>
Date:   Fri May 2 08:39:58 2025 -0700

    ci

commit 3e61e0490e
Author: Julian Andrej <andrej1@llnl.gov>
Date:   Fri May 2 08:38:47 2025 -0700

    ci

commit def4919592
Author: Julian Andrej <andrej1@llnl.gov>
Date:   Fri May 2 08:33:33 2025 -0700

    ci config

commit 2d147d70e0
Author: Julian Andrej <andrej1@llnl.gov>
Date:   Fri May 2 08:33:29 2025 -0700

    reintroduce tests

commit e29e64dffe
Author: Julian Andrej <andrej1@llnl.gov>
Date:   Fri May 2 08:04:44 2025 -0700

    reintroduce macos fp64 ci target

commit a7ec259bd5
Author: Julian Andrej <andrej1@llnl.gov>
Date:   Thu May 1 16:46:22 2025 -0700

    reintroduce macos fp64 ci target

commit 3e93e19767
Author: Julian Andrej <andrej1@llnl.gov>
Date:   Thu May 1 14:41:25 2025 -0700

    enzyme bug notes

commit 532b065596
Author: Julian Andrej <andrej1@llnl.gov>
Date:   Thu May 1 14:41:17 2025 -0700

    consistency

commit 82c1e2315b
Author: Julian Andrej <andrej1@llnl.gov>
Date:   Thu May 1 13:19:25 2025 -0700

    modernize

commit 8cc9eec535
Author: camierjs <camierjs@gmail.com>
Date:   Thu May 1 11:06:03 2025 -0700

    Remove unused code

commit dece65be31
Author: camierjs <camierjs@gmail.com>
Date:   Thu May 1 10:59:50 2025 -0700

    Header and style

commit 3e6d29b3dd
Author: camierjs <camierjs@gmail.com>
Date:   Thu May 1 10:53:12 2025 -0700

    Meld toward dfem

commit 487135b497
Author: camierjs <camierjs@gmail.com>
Date:   Thu May 1 10:48:02 2025 -0700

    Meld back toward dfem dev

commit 91f648aa95
Author: camierjs <camierjs@gmail.com>
Date:   Thu May 1 10:36:43 2025 -0700

    Remove examples leftovers

commit 999931ded2
Author: camierjs <camierjs@gmail.com>
Date:   Thu May 1 10:36:18 2025 -0700

    Sync dfem bench
2025-05-02 10:40:23 -07:00
camierjs be537728df Merge branch 'dfem-phase1-dev' into dfem-bench 2025-05-02 10:37:34 -07:00
Julian Andrej 4e5b98b10f doc 2025-05-02 10:05:20 -07:00
Julian Andrej d4acd906bf update brew before enzyme install 2025-05-02 09:01:51 -07:00
Julian Andrej d751ce66a3 ci 2025-05-02 08:43:46 -07:00
Julian Andrej 3f0abd4dfd ci 2025-05-02 08:40:45 -07:00
Julian Andrej 44a423d804 ci 2025-05-02 08:39:58 -07:00
Julian Andrej 3e61e0490e ci 2025-05-02 08:38:47 -07:00
Julian Andrej def4919592 ci config 2025-05-02 08:33:33 -07:00
Julian Andrej 2d147d70e0 reintroduce tests 2025-05-02 08:33:29 -07:00
Julian Andrej e29e64dffe reintroduce macos fp64 ci target 2025-05-02 08:04:44 -07:00
Julian Andrej a7ec259bd5 reintroduce macos fp64 ci target 2025-05-01 16:46:22 -07:00
Julian Andrej 3e93e19767 enzyme bug notes 2025-05-01 14:41:25 -07:00
Julian Andrej 532b065596 consistency 2025-05-01 14:41:17 -07:00
Julian Andrej 82c1e2315b modernize 2025-05-01 13:19:25 -07:00
camierjs 8cc9eec535 Remove unused code 2025-05-01 11:06:03 -07:00
camierjs dece65be31 Header and style 2025-05-01 10:59:50 -07:00
camierjs 3e6d29b3dd Meld toward dfem 2025-05-01 10:53:12 -07:00
camierjs 487135b497 Meld back toward dfem dev 2025-05-01 10:48:02 -07:00
camierjs 91f648aa95 Remove examples leftovers 2025-05-01 10:36:43 -07:00
camierjs 999931ded2 Sync dfem bench 2025-05-01 10:36:18 -07:00
camierjs 15dbcae725 Add version info 2025-05-01 10:26:49 -07:00
camierjs 01efb623da Update kernels pa to regs use 2025-05-01 10:08:01 -07:00
camierjs f854c5262d Move kernels pa to dfem regs 2025-05-01 10:07:46 -07:00
camierjs a91b754aaa Update dfem examples 2025-05-01 10:06:06 -07:00
camierjs b1623ff3d4 Sync dfem examples with latest changes 2025-05-01 10:05:54 -07:00
camierjs c2426ca45a Merge branch 'dfem-phase1-dev' 2025-05-01 09:35:22 -07:00
camierjs 276f419a3d Merge branch 'dfem-phase1-dev' of github.com:mfem/mfem into dfem-phase1-dev 2025-05-01 09:31:53 -07:00
Julian Andrej c91b8bea01 prevent possible indexing error 2025-05-01 08:42:56 -07:00
Veselin Dobrev 7bdceca6ce Windows CI debug 2025-05-01 04:48:28 -07:00
Veselin Dobrev 6f9a263435 Disable Ninja on windows -- it does not detect MSVC.
Add a debug action step to print the environment under windows.
2025-05-01 03:49:52 -07:00
Veselin Dobrev 28a7865ed1 Fix MSVC build issue.
Use the Ninja CMake generator on Windows to try to speedup the build.
2025-05-01 00:44:37 -07:00
Julian Andrej 6e7335ac52 Revert "test more captures"
This reverts commit 8115383dec.
2025-04-30 16:49:35 -07:00
Julian Andrej 8115383dec test more captures 2025-04-30 16:34:17 -07:00
Julian Andrej 3d1b017a60 Revert "test capture"
This reverts commit bf14e5b018.
2025-04-30 16:29:16 -07:00
Julian Andrej bf14e5b018 test capture 2025-04-30 16:12:23 -07:00
Julian Andrej fb3517453f correctness 2025-04-30 15:48:35 -07:00
Julian Andrej bfca6beb28 Revert "hints for mscv"
This reverts commit 78a60cc1d9.
2025-04-30 14:30:02 -07:00
Julian Andrej f51e46d3d8 changelog 2025-04-30 14:02:28 -07:00
Julian Andrej 78a60cc1d9 hints for mscv 2025-04-30 14:02:24 -07:00
Julian Andrej 935d3a9e42 namespaces 2025-04-30 10:30:44 -07:00
Julian Andrej 35866f8485 namespaces 2025-04-30 09:40:45 -07:00
Julian Andrej 6b4b644355 namespaces 2025-04-30 09:38:52 -07:00
Julian Andrej b9ec58e7a1 guards 2025-04-30 09:19:17 -07:00
Julian Andrej 4644aed322 native ad test 2025-04-30 09:18:22 -07:00
Julian Andrej 80da896859 namespaces 2025-04-30 09:18:16 -07:00
Julian Andrej b96dcb4401 namespaces 2025-04-30 08:54:57 -07:00
Julian Andrej 5054f1784d again 2025-04-29 14:13:51 -07:00
Julian Andrej 788c0efda0 sync input values 2025-04-29 14:10:42 -07:00
Julian Andrej 4d49d42702 typo 2025-04-29 13:33:16 -07:00
Julian Andrej f5192230e0 more msvc handholding 2025-04-29 11:22:24 -07:00
Tzanio Kolev 400e3eca7d Merge branch 'master' into dfem-phase1-dev 2025-04-29 09:55:18 -07:00
Julian Andrej b90c8d80fe remove problematic constexpr 2025-04-29 08:50:20 -07:00
Veselin Dobrev a0491f6bfc Fix some msvc warnings which also fixed some compilation errors 2025-04-29 01:43:41 -07:00
Julian Andrej a8df54cf5d please msvc 2025-04-28 20:39:29 -07:00
Julian Andrej 9c4e43ee12 revert 2025-04-28 19:29:23 -07:00
Julian Andrej 7a1887c525 oops 2025-04-28 17:58:40 -07:00
Julian Andrej 907783f9ca testing 2025-04-28 17:56:23 -07:00
Julian Andrej f4f68fa021 size 2025-04-28 17:08:04 -07:00
Julian Andrej b76e9e80a7 real annoying real_t 2025-04-28 17:03:59 -07:00
Julian Andrej b8f677b2fe shadows 2025-04-28 16:59:44 -07:00
Julian Andrej 6e42fbae4d guards 2025-04-28 16:51:34 -07:00
Julian Andrej b8c0008061 include orders etc 2025-04-28 16:36:44 -07:00
Julian Andrej cdce090c2a cmake 2025-04-28 15:48:25 -07:00
Julian Andrej e246c0852b c++17 2025-04-28 15:40:50 -07:00
Julian Andrej 4db86286ee unguard test 2025-04-28 14:05:55 -07:00
Julian Andrej 9308946715 guards 2025-04-28 14:05:44 -07:00
Julian Andrej d28eca6b7f renaming 2025-04-28 14:05:34 -07:00
Julian Andrej 8e26105232 temporary disable offended unit tests 2025-04-28 11:53:12 -07:00
Julian Andrej c674f9f7ad defuse test 2025-04-24 15:29:09 -07:00
Julian Andrej 537d30120a Merge branch 'master' into dfem-phase1-dev 2025-04-24 14:35:23 -07:00
Julian Andrej 519267e1cb paths 2025-04-24 14:02:09 -07:00
Julian Andrej 2c495fb70d shadow warnings 2025-04-24 13:36:05 -07:00
Julian Andrej 401d1aec7b ci 2025-04-24 13:02:10 -07:00
Julian Andrej 8299b1c036 ci 2025-04-24 12:52:18 -07:00
Julian Andrej 9dd1e4dbdb ci 2025-04-24 11:48:17 -07:00
Julian Andrej 47a3534eff ci 2025-04-24 11:44:08 -07:00
Julian Andrej 2f39ff66f3 ci 2025-04-24 11:34:36 -07:00
Julian Andrej ddca183704 ci 2025-04-24 11:20:31 -07:00
Julian Andrej 078ce6130c ci 2025-04-24 11:17:54 -07:00
Julian Andrej 6d15c2a156 ci 2025-04-24 11:11:54 -07:00
Julian Andrej 7d705c0677 ci 2025-04-24 11:09:42 -07:00
Julian Andrej c027328b91 ci 2025-04-24 11:07:27 -07:00
Julian Andrej 65cb67e1c1 ci 2025-04-24 11:04:54 -07:00
Julian Andrej 494f27c14c ci 2025-04-24 11:00:37 -07:00
Julian Andrej 3c02b72084 ci 2025-04-24 10:51:20 -07:00
Julian Andrej 75e2be35ba ci 2025-04-24 10:46:12 -07:00
Julian Andrej b0f9cbfd26 ci 2025-04-24 10:42:24 -07:00
Julian Andrej 6afea18cde ci 2025-04-24 10:39:14 -07:00
Julian Andrej 2e69ff4b97 ci 2025-04-24 10:33:08 -07:00
Julian Andrej 6c70fe9334 ci 2025-04-24 10:27:46 -07:00
Julian Andrej 4ccbd4581e ci 2025-04-24 10:19:07 -07:00
Julian Andrej 6e262f6c3f ci 2025-04-24 10:13:37 -07:00
Julian Andrej 52e10475a5 ci 2025-04-24 10:10:20 -07:00
Julian Andrej c0299a5a4b ci 2025-04-24 10:05:24 -07:00
Julian Andrej 06eecb0dce yaml lint and first enzyme ci entries 2025-04-24 10:01:07 -07:00
Julian Andrej 96261a7742 c++17 and experimental namespace 2025-04-23 18:09:12 -07:00
Julian Andrej d7c479fa1e documentation 2025-04-21 09:21:07 -07:00
Julian Andrej 8b01d8f13b std::cout -> mfem::out 2025-04-16 10:53:23 -07:00
Julian Andrej 710da275c8 add dfem folder to makefile 2025-04-16 09:02:57 -07:00
Julian Andrej fd481eb725 correct include orders 2025-04-16 09:02:43 -07:00
Julian Andrej b5bbdbbed5 vectorfe leftover 2025-04-16 09:02:31 -07:00
Julian Andrej 6a26200314 remove vectorfe crumbs 2025-04-15 11:31:14 -07:00
Julian Andrej a485121526 msvc ambiguity enable_if 2025-04-14 14:40:52 -07:00
Julian Andrej 1f9e1cf175 brackets 2025-04-14 14:03:28 -07:00
Julian Andrej ec402882da move guard 2025-04-14 13:58:10 -07:00
Julian Andrej e7633e0e2c guard tests 2025-04-14 13:49:46 -07:00
Julian Andrej 30aeb465b7 includes 2025-04-14 13:27:15 -07:00
Julian Andrej ff4993fc51 array include 2025-04-14 13:13:44 -07:00
Julian Andrej 0a42ea8021 copyright dates 2025-04-14 13:13:33 -07:00
Julian Andrej b8d024b59b remove example subdirectory 2025-04-14 10:51:57 -07:00
Julian Andrejandcamierjs 9e1ccf4543 phase 1 skeleton
Co-authored-by: camierjs <camierjs@gmail.com>
2025-04-14 09:43:43 -07:00
camierjs 075ebb255d Do one first benchmark 2025-04-09 11:35:40 -07:00
camierjs 3eb6a5b3b2 Merge branch 'dfem-phase1-dev' 2025-04-03 14:01:28 -07:00
Julian Andrej 8ba1f17f72 add nonlinear solver options to command line arguments 2025-04-03 11:01:31 -07:00
Julian Andrej e5f5a79e66 attempt to fix parametric function transfers 2025-04-03 08:19:53 -07:00
Julian Andrej 43f1b19767 switch to 2d by default 2025-04-03 08:19:32 -07:00
Julian Andrej 7bebe4528f stop printing dependency maps 2025-04-03 08:19:16 -07:00
camierjs da63657cdd GCC warning fixes 2025-04-02 18:40:57 -07:00
camierjs 2b1d271888 Merge branch 'dfem-phase1-dev' 2025-04-02 18:34:46 -07:00
camierjs 47fb8a4fda No auto for gcc 2025-04-02 18:34:30 -07:00
camierjs ee7d9726df Warnings & fixes 2025-04-02 18:34:08 -07:00
camierjs 44b560a916 Merge branch 'dfem-phase1-dev' 2025-04-02 17:56:37 -07:00
Julian Andrej 5657f6ebe8 Merge branch 'dfem-phase1-dev' of github.com:mfem/mfem into dfem-phase1-dev 2025-04-02 17:44:22 -07:00
Julian Andrej 19543b6b16 more device stuff 2025-04-02 17:41:57 -07:00
camierjs 94a832a0c6 Merge branch 'dfem-phase1-dev' 2025-04-02 17:21:09 -07:00
camierjs b56e994ecd Copyright header, includes trim & warning fixes 2025-04-02 17:20:29 -07:00
camierjs 8be11cdfdb Remove duplicate inline 2025-04-02 16:49:20 -07:00
camierjs d71a9602b5 Merge branch 'dfem-phase1-dev' 2025-04-02 16:41:06 -07:00
camierjs 1108bb7e85 Use SetMaxOf inside kernel 2025-04-02 16:40:38 -07:00
Julian Andrej ae8e5aa88d some device stuff 2025-04-02 16:21:18 -07:00
camierjs 17f4acf6b1 Merge branch 'main' of github.com:camierjs/mfem-dfem-bench into main 2025-04-02 16:03:32 -07:00
camierjs 2ce3f3037c Cleanup 2025-04-02 16:03:30 -07:00
camierjs 29189a6d4a Merge branch 'dfem-phase1-dev' 2025-04-02 16:02:10 -07:00
Julian Andrej 08f3c86b8a make attributes device compatible 2025-04-02 15:46:19 -07:00
camierjs c6eb171b5b Back to foreach treads 2025-04-02 14:33:42 -07:00
camierjs d26695cd2a Use latest AddDomainIntegrator API 2025-04-02 12:18:21 -07:00
camierjs 01ab390b06 Merge branch 'dfem-phase1-dev' 2025-04-02 12:09:57 -07:00
camierjs 43c42295d3 Few changes with clang 20.1 2025-04-02 12:09:36 -07:00
camierjs 52bc915120 Few fixes to run on device and removed warnings 2025-04-02 12:07:57 -07:00
camierjs cd9cabb955 Cleanup all hipGetLastError 2025-04-02 09:32:36 -07:00
Julian Andrej e66a61c198 add build instructions 2025-03-31 17:23:33 -07:00
Julian Andrej f8b3c78b19 tensor additions 2025-03-31 14:28:29 -07:00
Julian Andrej 4749746171 add laghos 2025-03-31 14:28:10 -07:00
camierjs 1ddd01c2a0 All dfem BP3 versions 2025-03-31 13:47:06 -07:00
camierjs 87ec3850b5 Update Diffusion class 2025-03-30 13:08:31 -07:00
camierjs 1b25a61c9e Re-order kpc benchmarks 2025-03-30 11:52:41 -07:00
camierjs 7bee8e8161 tests/benchmarks/bench_dfem 2025-03-30 11:40:41 -07:00
camierjs a545ff8264 Bring StiffnessIntegrator in bench dfem 2025-03-30 10:29:17 -07:00
camierjs 5352234aef Use SetMaxOf 2025-03-30 10:06:54 -07:00
camierjs c3732f9d86 dfem diffusion3d D1D Q1D tests 2025-03-30 09:46:08 -07:00
camierjs b95f3809fe ParametricSpace d1d/q1d 2025-03-28 17:24:29 -07:00
camierjs e6a28b7753 Merge branch 'dfem-phase1-dev' 2025-03-28 15:09:46 -07:00
camierjs 62adea8b46 WIP dfem diffusion 2025-03-28 15:09:22 -07:00
camierjs 7d11db33c0 Add dfem diffusion multi-version example and bench dfem setup 2025-03-28 12:09:52 -07:00
Julian Andrej 11fce4235b revert width determination 2025-03-28 08:16:26 -07:00
camierjs f500b4875f dfem bench check 2025-03-27 10:48:46 -07:00
camierjs ba212c583e bench dfem init with nvtx 2025-03-27 10:34:12 -07:00
Julian Andrej fd341e07da example 2025-03-21 15:54:58 -07:00
Julian Andrej d59e2a229c phase 1 skeleton 2025-03-21 15:54:18 -07:00
106 changed files with 30809 additions and 6070 deletions
+5
View File
@@ -44,7 +44,12 @@ Discretization improvements
- Added methods to estimate function extremum using piecewise linear bounds plus
recursive subdivision.
<<<<<<<<< Temporary merge branch 1
- Added class VectorQuadratureSpace that represents a vector (multi-component)
version of the scalar (single-component) class QuadratureSpaceBase.
=========
- Extend FindPointsGSLIB to support surface meshes.
>>>>>>>>> Temporary merge branch 2
Meshing improvements
--------------------
+27 -11
View File
@@ -601,6 +601,13 @@ if (MFEM_USE_ENZYME)
set(ENZYME_INCLUDE_DIRS ${ENZYME_DIR}/include)
endif()
if (MFEM_USE_PROTEUS)
enable_language(C)
find_package(proteus REQUIRED PATHS "${PROTEUS_DIR}")
message(STATUS "${PROTEUS_DIR}/include")
include_directories("${PROTEUS_DIR}/include")
endif()
# MFEM_TIMER_TYPE
if (NOT DEFINED MFEM_TIMER_TYPE)
if (APPLE)
@@ -737,6 +744,16 @@ mfem_add_library(mfem ${SOURCES} ${HEADERS} ${MASTER_HEADERS})
target_compile_features(mfem PUBLIC cxx_std_${CMAKE_CXX_STANDARD})
# message(STATUS "TPL_LIBRARIES = ${TPL_LIBRARIES}")
target_link_libraries(mfem PUBLIC ${TPL_LIBRARIES} ${TPL_TARGETS})
if (MFEM_USE_PROTEUS)
add_library(ClangProteusFlags INTERFACE IMPORTED)
set_target_properties(ClangProteusFlags PROPERTIES
INTERFACE_COMPILE_OPTIONS "-fpass-plugin=$<TARGET_FILE:ProteusPass>"
)
target_link_libraries(mfem PUBLIC ClangProteusFlags)
target_link_libraries(mfem PUBLIC proteus)
endif()
if (TPL_TARGETS)
add_dependencies(mfem ${TPL_TARGETS})
endif()
@@ -773,7 +790,7 @@ set_target_properties(mfem PROPERTIES SOVERSION "${mfem_VERSION}")
# If building out-of-source, define MFEM_CONFIG_FILE to point to the config file
# inside the build directory.
if (NOT ("${PROJECT_SOURCE_DIR}" STREQUAL "${PROJECT_BINARY_DIR}"))
target_compile_definitions(mfem PRIVATE
target_compile_definitions(mfem PUBLIC
"MFEM_CONFIG_FILE=\"${PROJECT_BINARY_DIR}/config/_config.hpp\"")
endif()
@@ -833,16 +850,15 @@ if (MFEM_ENABLE_TESTING)
add_mfem_target(${MFEM_ALL_TESTS_TARGET_NAME} OFF)
add_subdirectory(tests EXCLUDE_FROM_ALL)
if (MFEM_USE_BENCHMARK)
# Create a target for all benchmarks and, optionally, enable it.
set(MFEM_ALL_BENCHMARKS_TARGET_NAME benchmarks)
add_mfem_target(${MFEM_ALL_BENCHMARKS_TARGET_NAME}
${MFEM_ENABLE_BENCHMARKS})
if (MFEM_ENABLE_BENCHMARKS)
add_subdirectory(tests/benchmarks) #install benchmarks if enabled
else()
add_subdirectory(tests/benchmarks EXCLUDE_FROM_ALL)
endif()
# Create a target for all benchmarks and, optionally, enable it. Some simple
# timer-based benchmarks in tests/benchmarks do not require Google Benchmark.
set(MFEM_ALL_BENCHMARKS_TARGET_NAME benchmarks)
add_mfem_target(${MFEM_ALL_BENCHMARKS_TARGET_NAME}
${MFEM_ENABLE_BENCHMARKS})
if (MFEM_ENABLE_BENCHMARKS)
add_subdirectory(tests/benchmarks) #install benchmarks if enabled
else()
add_subdirectory(tests/benchmarks EXCLUDE_FROM_ALL)
endif()
endif()
+2 -2
View File
@@ -18,9 +18,9 @@
#define MFEM_CONFIG_HPP
#ifdef MFEM_CONFIG_FILE
#include MFEM_CONFIG_FILE
#include MFEM_CONFIG_FILE // IWYU pragma: export
#else
#include "_config.hpp"
#include "_config.hpp" // IWYU pragma: export
#endif
#include <cstdint>
+1
View File
@@ -47,6 +47,7 @@ list(APPEND ALL_EXE_SRCS
ex39.cpp
ex40.cpp
ex41.cpp
# jitplayground.cpp
)
if (MFEM_USE_MPI)
+548
View File
@@ -0,0 +1,548 @@
#include <mfem.hpp>
#ifdef MFEM_USE_PROTEUS
#include "../fem/dfem/util.hpp"
#include <proteus/CppJitModule.h>
#include "jitplayground.hpp"
#include <algorithm>
#include <array>
#include <cctype>
#include <cmath>
#include <fstream>
#include <initializer_list>
#include <iostream>
#include <memory>
#include <sstream>
#include <string>
#include <string_view>
#include <type_traits>
#include <unordered_map>
#include <unordered_set>
#include <utility>
#include <vector>
namespace util
{
constexpr std::string_view Dirname(std::string_view path)
{
const size_t last_sep = path.find_last_of("/\\");
if (last_sep == std::string_view::npos) { return {}; }
return path.substr(0, last_sep);
}
constexpr std::string_view thisFileDir = Dirname(__FILE__);
}
template <typename T>
static std::string TypeNameString()
{
return std::string(mfem::future::get_type_name<T>());
}
template <typename Tuple, size_t... Is>
static auto ParamTypeStringsImpl(std::index_sequence<Is...>)
{
return std::array<std::string, sizeof...(Is)>
{
TypeNameString<std::remove_reference_t<decltype(mfem::future::get<Is>(std::declval<Tuple&>()))>>()...
};
}
template <typename Tuple>
static auto ParamTypeStrings()
{
return ParamTypeStringsImpl<Tuple>(
std::make_index_sequence<mfem::future::tuple_size<Tuple>::value> {});
}
static std::string_view Trim(std::string_view s)
{
size_t begin = 0;
while (begin < s.size() && std::isspace(static_cast<unsigned char>(s[begin])))
{
++begin;
}
size_t end = s.size();
while (end > begin &&
std::isspace(static_cast<unsigned char>(s[end - 1])))
{
--end;
}
return s.substr(begin, end - begin);
}
static bool IsValidIdentifier(std::string_view s)
{
if (s.empty()) { return false; }
const unsigned char c0 = static_cast<unsigned char>(s[0]);
if (!(std::isalpha(c0) || c0 == '_')) { return false; }
for (size_t i = 1; i < s.size(); ++i)
{
const unsigned char c = static_cast<unsigned char>(s[i]);
if (!(std::isalnum(c) || c == '_')) { return false; }
}
return true;
}
static bool ParseJitDirective(std::string_view line,
std::string &type,
std::string &var,
std::string &kind)
{
const size_t jit_pos = line.find("$JIT");
if (jit_pos == std::string_view::npos) { return false; }
const size_t open = line.find('[', jit_pos);
const size_t close = line.find(']', jit_pos);
MFEM_VERIFY(open != std::string_view::npos &&
close != std::string_view::npos &&
close > open,
"malformed $JIT directive (expected brackets): " << line);
const std::string_view payload = line.substr(open + 1, close - open - 1);
const size_t comma1 = payload.find(',');
const size_t comma2 = (comma1 == std::string_view::npos)
? std::string_view::npos
: payload.find(',', comma1 + 1);
MFEM_VERIFY(comma1 != std::string_view::npos &&
comma2 != std::string_view::npos,
"malformed $JIT directive (expected 3 comma-separated fields): "
<< line);
const std::string_view f0 = Trim(payload.substr(0, comma1));
const std::string_view f1 = Trim(payload.substr(comma1 + 1,
comma2 - comma1 - 1));
const std::string_view f2 = Trim(payload.substr(comma2 + 1));
MFEM_VERIFY(!f0.empty() && !f1.empty() && !f2.empty(),
"malformed $JIT directive (empty field): " << line);
type.assign(f0);
var.assign(f1);
kind.assign(f2);
return true;
}
static std::string ReadFileOrEmpty(const std::string &fn)
{
std::ifstream file(fn);
if (!file.is_open())
{
std::cerr << "could not open file " << fn << "\n";
return {};
}
std::stringstream buffer;
buffer << file.rdbuf();
return buffer.str();
}
static std::vector<std::string> ExtractJitVarNames(const std::string
&kernel_code)
{
std::stringstream ss(kernel_code);
std::string line;
std::vector<std::string> var_names;
std::unordered_set<std::string> seen_vars;
while (std::getline(ss, line))
{
std::string type, var, kind;
if (ParseJitDirective(line, type, var, kind))
{
MFEM_VERIFY(IsValidIdentifier(var),
"$JIT variable must be a valid identifier: " << var);
MFEM_VERIFY(seen_vars.insert(var).second,
"duplicate $JIT variable name: " << var);
var_names.push_back(var);
}
}
return var_names;
}
static std::string RewriteKernelForJit(std::string kernel_code,
const std::vector<std::string> &jit_values)
{
std::stringstream ss(kernel_code);
std::string line;
std::string out;
out.reserve(kernel_code.size() + 128);
bool have_pending = false;
size_t pending_index = 0;
std::string pending_type;
std::string pending_var;
std::unordered_set<std::string> seen_vars;
while (std::getline(ss, line))
{
line.push_back('\n');
if (have_pending)
{
MFEM_VERIFY(pending_index < jit_values.size(),
"not enough JIT values provided");
const size_t indent_end = line.find_first_not_of(" \t");
const std::string indent =
(indent_end == std::string::npos) ? std::string() :
line.substr(0, indent_end);
out += indent + "const " + pending_type + " " + pending_var + " = " +
jit_values[pending_index] + ";\n";
have_pending = false;
++pending_index;
continue;
}
std::string type, var, kind;
if (ParseJitDirective(line, type, var, kind))
{
MFEM_VERIFY(IsValidIdentifier(var),
"$JIT variable must be a valid identifier: " << var);
MFEM_VERIFY(kind == "generic",
"unsupported $JIT kind: " << kind);
MFEM_VERIFY(seen_vars.insert(var).second,
"duplicate $JIT variable name: " << var);
pending_type = std::move(type);
pending_var = std::move(var);
have_pending = true;
continue; // drop directive line
}
out += line;
}
MFEM_VERIFY(!have_pending,
"$JIT directive must annotate a following line");
MFEM_VERIFY(jit_values.size() == pending_index,
"JIT value count must match number of $JIT directives");
return out;
}
static std::string GeneratedOutputPath(std::string_view original_path)
{
const size_t last_sep = original_path.find_last_of("/\\");
const size_t dot = original_path.find_last_of('.');
const bool dot_in_filename =
(dot != std::string_view::npos) &&
(last_sep == std::string_view::npos || dot > last_sep);
const std::string_view base =
dot_in_filename ? original_path.substr(0, dot) : original_path;
return std::string(base) + "_generated.hpp";
}
static void WriteFileOrWarn(const std::string &path,
const std::string &contents)
{
std::ofstream out(path);
if (!out.is_open())
{
std::cerr << "could not write generated file " << path << "\n";
return;
}
out << contents;
}
class JitQFunction
{
public:
template <typename ImplT, size_t N>
JitQFunction(ImplT, const std::string &fn,
const std::array<bool, N> &activity_map)
{
using qf_signature = typename
mfem::future::get_function_signature<
decltype(&ImplT::operator())>::type;
using qf_param_ts = typename qf_signature::parameter_ts;
constexpr size_t nparams = mfem::future::tuple_size<qf_param_ts>::value;
static_assert(N == nparams, "activity_map size must match qfunc arity");
this->fn = fn;
this->nparams = nparams;
this->activity_map.reserve(N);
for (size_t i = 0; i < N; ++i)
{
this->activity_map.push_back(activity_map[i]);
}
{
const auto param_types_arr = ParamTypeStrings<qf_param_ts>();
this->param_types.assign(param_types_arr.begin(), param_types_arr.end());
}
this->return_type = TypeNameString<typename qf_signature::return_t>();
this->return_is_void = std::is_same_v<typename qf_signature::return_t, void>;
this->impl_type_name = TypeNameString<ImplT>();
this->jit_var_names = ExtractJitVarNames(ReadFileOrEmpty(fn));
}
template <typename ReturnT, typename... Args>
ReturnT run(std::string_view name,
std::initializer_list<std::pair<std::string_view, std::string_view>> jit_values,
Args&&... args)
{
auto ordered_values = MatchJitValues(jit_values);
auto &mod = GetOrCreateModule(ordered_values);
auto &instance = mod.instantiate(std::string(name), std::string());
return instance.template run<ReturnT>(std::forward<Args>(args)...);
}
template <typename ReturnT, typename... Args>
ReturnT run_primal(
std::initializer_list<std::pair<std::string_view, std::string_view>> jit_values,
Args&&... args)
{
return run<ReturnT>(qfunc_name, jit_values,
std::forward<Args>(args)...);
}
template <typename ReturnT, typename... Args>
ReturnT run_derivative(
std::initializer_list<std::pair<std::string_view, std::string_view>> jit_values,
Args&&... args)
{
return run<ReturnT>(qfunc_name + "_fwddiff", jit_values,
std::forward<Args>(args)...);
}
private:
std::vector<std::string_view> MatchJitValues(
std::initializer_list<std::pair<std::string_view, std::string_view>>
named_values) const
{
std::unordered_map<std::string_view, std::string_view> value_map;
for (const auto &[name, value] : named_values)
{
value_map[name] = value;
}
std::vector<std::string_view> ordered_values;
ordered_values.reserve(jit_var_names.size());
for (const auto &var_name : jit_var_names)
{
auto it = value_map.find(var_name);
MFEM_VERIFY(it != value_map.end(),
"missing JIT value for variable: " << var_name);
ordered_values.push_back(it->second);
}
MFEM_VERIFY(ordered_values.size() == named_values.size(),
"provided " << named_values.size() << " JIT values but expected "
<< jit_var_names.size());
return ordered_values;
}
std::string BuildModuleCode(const std::vector<std::string> &jit_values) const
{
std::string module_code =
RewriteKernelForJit(ReadFileOrEmpty(fn), jit_values);
module_code += "\n\n";
module_code += "// --- generated ---\n";
module_code +=
"template <typename return_type, typename... Args>\n"
"return_type __enzyme_fwddiff(Args...);\n"
"\n"
"extern int enzyme_const;\n"
"extern int enzyme_dup;\n"
"\n";
// Generate a primal wrapper with the requested symbol name, so the kernel
// header can just define the qfunc as a functor.
//
// Note: Proteus instantiates entrypoints via `qfunc_wrapper<>(...)` even
// when there are no user template args, so keep the wrapper itself a
// template (with a default parameter) while still doing literal `$JIT`
// replacements in the kernel code.
module_code += "template <typename = void>\n";
module_code += return_type + " " +
std::string(qfunc_name) + "(";
bool first = true;
for (size_t i = 0; i < nparams; ++i)
{
if (!first) { module_code += ", "; }
first = false;
module_code += param_types[i] + " Arg" + std::to_string(i);
}
module_code += ")\n";
module_code += "{\n";
module_code += " " + impl_type_name + " qf;\n";
if (return_is_void)
{
module_code += " ";
}
else
{
module_code += " return ";
}
module_code += "qf(";
for (size_t i = 0; i < nparams; ++i)
{
if (i) { module_code += ", "; }
module_code += "Arg" + std::to_string(i);
}
module_code += ");\n";
module_code += "}\n\n";
module_code += "template <typename = void>\n";
module_code += return_type + " " +
std::string(qfunc_name) + "_fwddiff(";
first = true;
for (size_t i = 0; i < nparams; ++i)
{
if (!first) { module_code += ", "; }
first = false;
module_code += param_types[i] + " Arg" + std::to_string(i);
if (activity_map[i])
{
module_code += ", " + param_types[i] + " dArg" + std::to_string(i);
}
}
module_code += ")\n";
module_code += "{\n";
if (return_is_void)
{
module_code += " __enzyme_fwddiff<void>(\n";
}
else
{
module_code += " return __enzyme_fwddiff<" +
return_type + ">(\n";
}
module_code += " (void*)" + std::string(qfunc_name) + "<>";
module_code += ",\n";
for (size_t i = 0; i < nparams; ++i)
{
if (activity_map[i])
{
module_code += " enzyme_dup, Arg" + std::to_string(i) +
", dArg" + std::to_string(i);
}
else
{
module_code += " enzyme_const, Arg" + std::to_string(i);
}
module_code += (i + 1 == nparams) ? ");\n" : ",\n";
}
module_code += "}\n";
WriteFileOrWarn(GeneratedOutputPath(fn), module_code);
return module_code;
}
proteus::CppJitModule &GetOrCreateModule(
const std::vector<std::string_view> &jit_values)
{
std::string key;
for (const auto &val : jit_values)
{
if (!key.empty()) { key += ","; }
key += val;
}
auto it = modules.find(key);
if (it != modules.end())
{
return *it->second;
}
std::vector<std::string> values(jit_values.begin(), jit_values.end());
std::string code = BuildModuleCode(values);
auto mod = std::make_unique<proteus::CppJitModule>("host", code,
DefaultExtraArgs());
auto [inserted, ok] = modules.emplace(key, std::move(mod));
MFEM_VERIFY(ok, "failed to cache JIT module");
return *inserted->second;
}
static std::vector<std::string> DefaultExtraArgs()
{
return {"-fplugin=/Users/andrej1/local/enzyme/lib/ClangEnzyme-20.dylib"};
}
std::string qfunc_name = "qfunc_wrapper";
std::string fn;
size_t nparams = 0;
std::vector<bool> activity_map;
std::vector<std::string> param_types;
std::string return_type;
bool return_is_void = false;
std::string impl_type_name;
std::vector<std::string> jit_var_names;
std::unordered_map<std::string, std::unique_ptr<proteus::CppJitModule>> modules;
};
int main()
{
const size_t N = 4;
const size_t M = 5;
const double A = 123.4;
std::vector<double> X(N);
std::vector<double> Y(N);
for (size_t i = 0; i < N; ++i)
{
X[i] = static_cast<double>(i + 1);
Y[i] = static_cast<double>(N - i);
}
// // >>> user interface calls
// const std::string kernel_path = std::string(util::thisFileDir) +
// "/jitplayground.hpp";
// JitQFunction qf(daxpy_op{}, kernel_path, std::array{false, true, false});
// // <<< user interface calls
// // this will happen internally in dFEM
daxpy_op op;
printf("\n\nfunction call\n");
op(&A, X.data(), Y.data(), &N);
// reset X for the derivative test
for (size_t i = 0; i < N; ++i)
{
X[i] = static_cast<double>(i + 1);
Y[i] = static_cast<double>(N - i);
}
std::vector<double> dX(N, 1.0);
printf("\n\nforward diff call\n");
daxpy_op_fwddiff(&A, X.data(), dX.data(), Y.data(), &N);
std::vector<double> dX_manual(N, A);
printf("\n\nderivative checks\n");
std::cout << "dX: ";
for (size_t i = 0; i < N; ++i)
{
std::cout << dX[i] << (i + 1 == N ? '\n' : ' ');
}
std::cout << "dX_manual: ";
for (size_t i = 0; i < N; ++i)
{
std::cout << dX_manual[i] << (i + 1 == N ? '\n' : ' ');
}
double max_abs_err = 0.0;
for (size_t i = 0; i < N; ++i)
{
max_abs_err = std::max(max_abs_err, std::abs(dX[i] - dX_manual[i]));
}
std::cout << "max |dX - dX_manual| = " << max_abs_err << "\n";
return 0;
}
#else
int main()
{
std::cerr << "Proteus is required to run this example.\n";
return EXIT_FAILURE;
}
#endif // MFEM_USE_PROTEUS
+58
View File
@@ -0,0 +1,58 @@
#pragma once
#include <cstddef>
#include <vector>
#include <type_traits>
#include "proteus/JitInterface.h"
struct daxpy_op
{
void operator()(
const double *a,
double *x,
const double *y,
const size_t *N) const
{
const size_t n = *N;
auto lam = [=, n = proteus::jit_variable(n)]
() __attribute__((annotate("jit")))
{
printf("N = %zu\n", n);
for (size_t i = 0; i < n; ++i)
{
printf("x[%zu] = %f, y[%zu] = %f\n", i, x[i], i, y[i]);
x[i] = *a * x[i] + y[i];
printf("updated x[%zu] = %f\n", i, x[i]);
}
};
proteus::register_lambda(lam);
lam();
}
};
template <typename return_type, typename... Args>
return_type __enzyme_fwddiff(Args...);
extern int enzyme_const;
extern int enzyme_dup;
void daxpy_op_wrapper(const double * Arg0, double * Arg1,
const double * Arg2, const size_t *Arg3)
{
daxpy_op qf;
qf(Arg0, Arg1, Arg2, Arg3);
}
void daxpy_op_fwddiff(const double * Arg0, double * Arg1,
double * dArg1, const double * Arg2, const size_t *Arg3)
{
__enzyme_fwddiff<void>(
(void*)daxpy_op_wrapper,
enzyme_const, Arg0,
enzyme_dup, Arg1, dArg1,
enzyme_const, Arg2,
enzyme_const, Arg3);
}
+41 -15
View File
@@ -65,6 +65,7 @@ set(SRCS
dgmassinv.cpp
doftrans.cpp
dfem/doperator.cpp
dfem/backends/local_qf/kernels.cpp
eltrans.cpp
batchitrans.cpp
estimators.cpp
@@ -121,6 +122,11 @@ set(SRCS
qinterp/eval_hdiv.cpp
qinterp/grad_by_nodes.cpp
qinterp/grad_by_vdim.cpp
qinterp/grad_transpose.cpp
qinterp/grad_transpose_by_nodes.cpp
qinterp/grad_transpose_by_vdim.cpp
qinterp/eval_transpose.cpp
qinterp/eval_transpose_by_vdim.cpp
qspace.cpp
quadinterpolator.cpp
quadinterpolator_face.cpp
@@ -213,13 +219,31 @@ set(HDRS
dgmassinv_kernels.hpp
doftrans.hpp
dfem/doperator.hpp
dfem/fielddescriptor.hpp
dfem/fieldoperator.hpp
dfem/integrate.hpp
dfem/integrator_ctx.hpp
dfem/parameterspace.hpp
dfem/qfunction_apply.hpp
dfem/qfunction_transform.hpp
dfem/tuple.hpp
dfem/util.hpp
dfem/backends/util.hpp
dfem/backends/global_qf/action.hpp
dfem/backends/global_qf/derivative_action.hpp
dfem/backends/global_qf/derivative_apply.hpp
dfem/backends/global_qf/derivative_apply_transpose.hpp
dfem/backends/global_qf/derivative_setup.hpp
dfem/backends/global_qf/prelude.hpp
dfem/backends/local_qf/action.hpp
dfem/backends/local_qf/derivative_action.hpp
dfem/backends/local_qf/derivative_apply.hpp
dfem/backends/local_qf/derivative_apply_transpose.hpp
dfem/backends/local_qf/derivative_assemble.hpp
dfem/backends/local_qf/derivative_assemble_diagonal.hpp
dfem/backends/local_qf/derivative_setup.hpp
dfem/backends/local_qf/kernels.hpp
dfem/backends/local_qf/kernels_ho.hpp
dfem/backends/local_qf/kernels_lo.hpp
dfem/backends/local_qf/prelude.hpp
dfem/backends/local_qf/util.hpp
eltrans.hpp
estimators.hpp
fe.hpp
@@ -284,8 +308,10 @@ set(HDRS
qfunction.hpp
qinterp/det.hpp
qinterp/eval.hpp
qinterp/eval_transpose.hpp
qinterp/eval_hdiv.hpp
qinterp/grad.hpp
qinterp/grad_transpose.hpp
qspace.hpp
quadinterpolator.hpp
quadinterpolator_face.hpp
@@ -320,36 +346,36 @@ set(HDRS
)
if (MFEM_USE_SIDRE)
list(APPEND SRCS sidredatacollection.cpp)
list(APPEND HDRS sidredatacollection.hpp)
list(APPEND SRCS sidredatacollection.cpp)
list(APPEND HDRS sidredatacollection.hpp)
endif()
if (MFEM_USE_CONDUIT)
list(APPEND SRCS conduitdatacollection.cpp)
list(APPEND HDRS conduitdatacollection.hpp)
list(APPEND SRCS conduitdatacollection.cpp)
list(APPEND HDRS conduitdatacollection.hpp)
endif()
if (MFEM_USE_ADIOS2)
list(APPEND SRCS adios2datacollection.cpp)
list(APPEND HDRS adios2datacollection.hpp)
list(APPEND SRCS adios2datacollection.cpp)
list(APPEND HDRS adios2datacollection.hpp)
endif()
if (MFEM_USE_FMS)
list(APPEND SRCS fmsdatacollection.cpp fmsconvert.cpp)
list(APPEND HDRS fmsdatacollection.hpp fmsconvert.hpp)
list(APPEND SRCS fmsdatacollection.cpp fmsconvert.cpp)
list(APPEND HDRS fmsdatacollection.hpp fmsconvert.hpp)
endif()
if (MFEM_USE_MPI)
list(APPEND SRCS
list(APPEND SRCS
pbilinearform.cpp
pfespace.cpp
pgridfunc.cpp
plinearform.cpp
pnonlinearform.cpp
prestriction.cpp)
# If this list (HDRS -> HEADERS) is used for install, we probably want the
# headers added all the time.
list(APPEND HDRS
# If this list (HDRS -> HEADERS) is used for install, we probably want the
# headers added all the time.
list(APPEND HDRS
pbilinearform.hpp
pfespace.hpp
pgridfunc.hpp
-403
View File
@@ -1,403 +0,0 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "util.hpp"
namespace mfem::future
{
/// @brief Assemble element matrix for three dimensional data.
///
/// Note: In the below layouts, total_trial_op_dim is > 1 if
/// there are more than one inputs dependent on the derivative variable.
///
/// @param A Memory for one element matrix with layout
/// [test_ndof, test_vdim, trial_ndof, trial_vdim].
/// @param fhat Memory to hold the residual computation with layout
/// [test_vdim, test_op_dim, nqp].
/// @param qpdc The quadrature point data cache with data layout
/// [test_vdim, test_op_dim, trial_vdim, total_trial_op_dim, nqp].
/// @param itod Input Trial Operator Dimension array. If the trial
/// operator is not dependent, the dimension is 0 to indicate that.
/// @param inputs The input field operator types.
/// @param output The output field operator types.
/// @param input_dtqmaps The input DofToQuad maps.
/// @param output_dtqmap The output DofToQuad maps.
/// @param scratch_shmem Scratch shared memory for computations.
/// @param q1d The number of quadrature points in one dimension.
/// @param td1d The number of trial dofs in one dimension.
template <typename input_fop_ts, size_t num_inputs, typename output_fop_t>
MFEM_HOST_DEVICE void assemble_element_mat_t3d(
const DeviceTensor<4, real_t>& A,
const DeviceTensor<3, real_t>& fhat,
const DeviceTensor<5, const real_t>& qpdc,
const DeviceTensor<1, const real_t>& itod,
const input_fop_ts& inputs,
const output_fop_t& output,
const std::array<DofToQuadMap, num_inputs>& input_dtqmaps,
const DofToQuadMap& output_dtqmap,
std::array<DeviceTensor<1>, 6>& scratch_shmem,
const int& q1d,
const int& td1d)
{
constexpr int dimension = 3;
// [test_vdim, test_op_dim, trial_vdim, total_trial_op_dim, num_qp]
const int test_vdim = qpdc.GetShape()[0];
const int test_op_dim = qpdc.GetShape()[1];
const int trial_vdim = qpdc.GetShape()[2];
// [num_test_dof, ...]
const auto num_test_dof = A.GetShape()[0];
for (int Jx = 0; Jx < td1d; Jx++)
{
for (int Jy = 0; Jy < td1d; Jy++)
{
for (int Jz = 0; Jz < td1d; Jz++)
{
const int J = Jx + td1d * (Jy + td1d * Jz);
for (int j = 0; j < trial_vdim; j++)
{
for (int tv = 0; tv < test_vdim; tv++)
{
for (int tod = 0; tod < test_op_dim; tod++)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(qz, z, q1d)
{
const int q = qx + q1d * (qy + q1d * qz);
fhat(tv, tod, q) = 0.0;
}
}
}
}
}
// MSVC lambda capture workaround
[[maybe_unused]] const auto& inputs_ref = inputs;
int m_offset = 0;
for_constexpr<num_inputs>([&](auto s)
{
using fop_t = std::decay_t<decltype(get<s>(inputs_ref))>;
const int trial_op_dim = static_cast<int>(itod(static_cast<int>(s)));
if (trial_op_dim == 0)
{
// This is inside a lambda so we have to return
// instead of idiomatic 'continue'.
return;
}
auto& B = input_dtqmaps[s].B;
auto& G = input_dtqmaps[s].G;
if constexpr (is_value_fop<fop_t>::value)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(qz, z, q1d)
{
const int q = qx + q1d * (qy + q1d * qz);
for (int m = 0; m < trial_op_dim; m++)
{
for (int i = 0; i < test_vdim; i++)
{
for (int k = 0; k < test_op_dim; k++)
{
const real_t f = qpdc(i, k, j, m + m_offset, q);
fhat(i, k, q) += f * B(qx, 0, Jx) * B(qy, 0, Jy) * B(qz, 0, Jz);
}
}
}
}
}
}
}
else if constexpr (is_gradient_fop<fop_t>::value)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(qz, z, q1d)
{
const int q = qx + q1d * (qy + q1d * qz);
for (int m = 0; m < trial_op_dim; m++)
{
for (int i = 0; i < test_vdim; i++)
{
for (int k = 0; k < test_op_dim; k++)
{
const real_t f = qpdc(i, k, j, m + m_offset, q);
if (m == 0)
{
fhat(i, k, q) += f * G(qx, 0, Jx) * B(qy, 0, Jy) * B(qz, 0, Jz);
}
else if (m == 1)
{
fhat(i, k, q) += f * B(qx, 0, Jx) * G(qy, 0, Jy) * B(qz, 0, Jz);
}
else if (m == 2)
{
fhat(i, k, q) += f * B(qx, 0, Jx) * B(qy, 0, Jy) * G(qz, 0, Jz);
}
}
}
}
}
}
}
}
else
{
#if !(defined(MFEM_USE_CUDA) || defined(MFEM_USE_HIP))
MFEM_ABORT("sum factorized sparse matrix assemble routine "
"not implemented for field operator");
#endif
}
MFEM_SYNC_THREAD;
m_offset += trial_op_dim;
});
auto bvtfhat = Reshape(&A(0, 0, J, j), num_test_dof, test_vdim);
map_quadrature_data_to_fields(bvtfhat, fhat, output, output_dtqmap,
scratch_shmem, dimension, true);
}
}
}
}
}
/// @brief Assemble element matrix for two dimensional data.
///
/// Note: In the below layouts, total_trial_op_dim is > 1 if
/// there are more than one inputs dependent on the derivative variable.
///
/// @param A Memory for one element matrix with layout
/// [test_ndof, test_vdim, trial_ndof, trial_vdim].
/// @param fhat Memory to hold the residual computation with layout
/// [test_vdim, test_op_dim, nqp].
/// @param qpdc The quadrature point data cache with data layout
/// [test_vdim, test_op_dim, trial_vdim, total_trial_op_dim, nqp].
/// @param itod Input Trial Operator Dimension array. If the trial
/// operator is not dependent, the dimension is 0 to indicate that.
/// @param inputs The input field operator types.
/// @param output The output field operator types.
/// @param input_dtqmaps The input DofToQuad maps.
/// @param output_dtqmap The output DofToQuad maps.
/// @param scratch_shmem Scratch shared memory for computations.
/// @param q1d The number of quadrature points in one dimension.
/// @param td1d The number of trial dofs in one dimension.
template <typename input_fop_ts, size_t num_inputs, typename output_fop_t>
MFEM_HOST_DEVICE void assemble_element_mat_t2d(
const DeviceTensor<4, real_t>& A,
const DeviceTensor<3, real_t>& fhat,
const DeviceTensor<5, const real_t>& qpdc,
const DeviceTensor<1, const real_t>& itod,
const input_fop_ts& inputs,
const output_fop_t& output,
const std::array<DofToQuadMap, num_inputs>& input_dtqmaps,
const DofToQuadMap& output_dtqmap,
std::array<DeviceTensor<1>, 6>& scratch_shmem,
const int& q1d,
const int& td1d)
{
constexpr int dimension = 2;
// [test_vdim, test_op_dim, trial_vdim, total_trial_op_dim, num_qp]
const int test_vdim = qpdc.GetShape()[0];
const int test_op_dim = qpdc.GetShape()[1];
const int trial_vdim = qpdc.GetShape()[2];
// [num_test_dof, ...]
const auto num_test_dof = A.GetShape()[0];
for (int Jx = 0; Jx < td1d; Jx++)
{
for (int Jy = 0; Jy < td1d; Jy++)
{
const int J = Jy + Jx * td1d;
for (int j = 0; j < trial_vdim; j++)
{
for (int tv = 0; tv < test_vdim; tv++)
{
for (int tod = 0; tod < test_op_dim; tod++)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
const int q = qy + qx * q1d;
fhat(tv, tod, q) = 0.0;
}
}
}
}
// MSVC lambda capture workaround
[[maybe_unused]] const auto& inputs_ref = inputs;
int m_offset = 0;
for_constexpr<num_inputs>([&](auto s)
{
using fop_t = std::decay_t<decltype(get<s>(inputs_ref))>;
const int trial_op_dim = static_cast<int>(itod(static_cast<int>(s)));
if (trial_op_dim == 0)
{
// This is inside a lambda so we have to return
// instead of idiomatic 'continue'.
return;
}
auto& B = input_dtqmaps[s].B;
auto& G = input_dtqmaps[s].G;
if constexpr (is_value_fop<fop_t>::value)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
const int q = qy + qx * q1d;
for (int m = 0; m < trial_op_dim; m++)
{
for (int i = 0; i < test_vdim; i++)
{
for (int k = 0; k < test_op_dim; k++)
{
const real_t f = qpdc(i, k, j, m + m_offset, q);
fhat(i, k, q) += f * B(qx, 0, Jx) * B(qy, 0, Jy);
}
}
}
}
}
}
else if constexpr (is_gradient_fop<fop_t>::value)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
const int q = qy + qx * q1d;
for (int m = 0; m < trial_op_dim; m++)
{
for (int i = 0; i < test_vdim; i++)
{
for (int k = 0; k < test_op_dim; k++)
{
const real_t f = qpdc(i, k, j, m + m_offset, q);
if (m == 0)
{
fhat(i, k, q) += f * B(qx, 0, Jx) * G(qy, 0, Jy);
}
else
{
fhat(i, k, q) += f * G(qx, 0, Jx) * B(qy, 0, Jy);
}
}
}
}
}
}
}
else
{
#if !(defined(MFEM_USE_CUDA) || defined(MFEM_USE_HIP))
MFEM_ABORT("sum factorized sparse matrix assemble routine "
"not implemented for field operator");
#endif
}
MFEM_SYNC_THREAD;
m_offset += trial_op_dim;
});
auto bvtfhat = Reshape(&A(0, 0, J, j), num_test_dof, test_vdim);
map_quadrature_data_to_fields(bvtfhat, fhat, output, output_dtqmap,
scratch_shmem, dimension, true);
}
}
}
}
/// @brief Assemble element matrix for two or three dimensional data.
///
/// Note: In the below layouts, total_trial_op_dim is > 1 if
/// there are more than one inputs dependent on the derivative variable.
///
/// @param A Memory for one element matrix with layout
/// [test_ndof, test_vdim, trial_ndof, trial_vdim].
/// @param fhat Memory to hold the residual computation with layout
/// [test_vdim, test_op_dim, nqp].
/// @param qpdc The quadrature point data cache with data layout
/// [test_vdim, test_op_dim, trial_vdim, total_trial_op_dim, nqp].
/// @param itod Input Trial Operator Dimension array. If the trial
/// operator is not dependent, the dimension is 0 to indicate that.
/// @param inputs The input field operator types.
/// @param output The output field operator types.
/// @param input_dtqmaps The input DofToQuad maps.
/// @param output_dtqmap The output DofToQuad maps.
/// @param scratch_shmem Scratch shared memory for computations.
/// @param dimension The spatial dimension.
/// @param q1d The number of quadrature points in one dimension.
/// @param td1d The number of trial dofs in one dimension.
/// @param use_sum_factorization Indicator if sum factorization is used.
template <typename input_fop_ts, size_t num_inputs, typename output_fop_t>
MFEM_HOST_DEVICE void assemble_element_mat_naive(
const DeviceTensor<4, real_t>& A,
const DeviceTensor<3, real_t>& fhat,
const DeviceTensor<5, const real_t>& qpdc,
const DeviceTensor<1, const real_t>& itod,
const input_fop_ts& inputs,
const output_fop_t& output,
const std::array<DofToQuadMap, num_inputs>& input_dtqmaps,
const DofToQuadMap& output_dtqmap,
std::array<DeviceTensor<1>, 6>& scratch_shmem,
const int& dimension,
const int& q1d,
const int& td1d,
const bool& use_sum_factorization)
{
if (use_sum_factorization)
{
if (dimension == 2)
{
assemble_element_mat_t2d(A, fhat, qpdc, itod, inputs, output,
input_dtqmaps, output_dtqmap, scratch_shmem, q1d, td1d);
}
else if (dimension == 3)
{
assemble_element_mat_t3d(A, fhat, qpdc, itod, inputs, output,
input_dtqmaps, output_dtqmap, scratch_shmem, q1d, td1d);
}
}
else
{
#if !(defined(MFEM_USE_CUDA) || defined(MFEM_USE_HIP))
MFEM_ABORT("element matrix assemble not implemented for non tensor "
"product basis");
#endif
}
}
} // namespace mfem::future
+122
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@@ -0,0 +1,122 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../util.hpp"
#include "../../integrator_ctx.hpp"
#include <utility>
namespace mfem::future
{
namespace GlobalQFImpl
{
template<
typename qfunc_t,
typename inputs_t,
typename outputs_t,
size_t ninputs = tuple_size<inputs_t>::value,
size_t noutputs = tuple_size<outputs_t>::value>
struct Action
{
Action(
IntegratorContext ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs) :
ctx(ctx),
qfunc(qfunc),
inputs(inputs),
outputs(outputs)
{
create_fop_to_fd(inputs, ctx.infds, input_to_infd);
create_fop_to_fd(outputs, ctx.outfds, output_to_outfd);
check_consistency(inputs, input_to_infd, ctx.infds);
check_consistency(outputs, output_to_outfd, ctx.outfds);
create_fieldbases(inputs, input_to_infd, ctx.infds, ctx.ir, input_bases);
create_fieldbases(outputs, output_to_outfd, ctx.outfds, ctx.ir, output_bases);
create_qlayouts(inputs, ctx.in_qlayouts, input_qlayouts);
create_qlayouts(outputs, ctx.out_qlayouts, output_qlayouts);
const int nqp = ctx.ir.GetNPoints();
gnqp = nqp * ctx.nentities;
// prepare xq and yq BlockVectors
xq_offsets.SetSize(ninputs + 1);
xq_offsets[0] = 0;
constexpr_for<0, ninputs>([&](auto i)
{
const auto input = get<i>(inputs);
xq_offsets[i + 1] = nqp * input.size_on_qp * ctx.nentities;
});
xq_offsets.PartialSum();
InitBlockVector(xq, xq_offsets);
yq_offsets.SetSize(noutputs + 1);
yq_offsets[0] = 0;
constexpr_for<0, noutputs>([&](auto i)
{
const auto output = get<i>(outputs);
yq_offsets[i + 1] = nqp * output.size_on_qp * ctx.nentities;
});
yq_offsets.PartialSum();
InitBlockVector(yq, yq_offsets);
}
void operator()(
const std::vector<Vector *> &xe,
std::vector<Vector *> &ye) const
{
if (ctx.attr.Size() == 0) { return; }
// E -> Q
interpolate(input_to_infd, input_bases, xe, xq);
// Q -> Q
static_assert(
detail::supports_tensor_array_qfunc<qfunc_t, inputs_t, outputs_t>::value,
"qfunc signature not supported by default backend Action");
detail::call_qfunc(
qfunc, xq, yq, gnqp, input_qlayouts, output_qlayouts,
std::make_index_sequence<ninputs> {},
std::make_index_sequence<noutputs> {});
// Q -> E
integrate(output_to_outfd, output_bases, yq, ye);
}
IntegratorContext ctx;
qfunc_t qfunc;
inputs_t inputs;
outputs_t outputs;
std::array<size_t, ninputs> input_to_infd;
std::array<size_t, noutputs> output_to_outfd;
std::array<FieldBasis, ninputs> input_bases;
std::array<FieldBasis, noutputs> output_bases;
std::array<std::vector<int>, ninputs> input_qlayouts;
std::array<std::vector<int>, noutputs> output_qlayouts;
int gnqp = 0;
Array<int> xq_offsets, yq_offsets;
mutable BlockVector xq, yq;
};
}
}
@@ -0,0 +1,180 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../../integrator_ctx.hpp"
#include "../util.hpp"
#include <utility>
namespace mfem::future::GlobalQFImpl
{
template<
int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t,
size_t ninputs = tuple_size<inputs_t>::value,
size_t noutputs = tuple_size<outputs_t>::value>
struct DerivativeAction
{
using qfunc_shadow_t = detail::qfunc_shadow_t<qfunc_t>;
DerivativeAction(
IntegratorContext ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs):
ctx(ctx), qfunc(qfunc),
qfunc_shadow(detail::MakeQFunctionShadowStorage(this->qfunc)),
inputs(inputs), outputs(outputs)
{
create_fop_to_fd(inputs, ctx.infds, input_to_infd);
create_fop_to_fd(outputs, ctx.outfds, output_to_outfd);
check_consistency(inputs, input_to_infd, ctx.infds);
check_consistency(outputs, output_to_outfd, ctx.outfds);
create_fieldbases(inputs, input_to_infd, ctx.infds, ctx.ir, input_bases);
create_fieldbases(
outputs, output_to_outfd, ctx.outfds, ctx.ir, output_bases);
create_qlayouts(inputs, ctx.in_qlayouts, input_qlayouts);
create_qlayouts(outputs, ctx.out_qlayouts, output_qlayouts);
const int nqp = ctx.ir.GetNPoints();
gnqp = nqp * ctx.nentities;
xq_offsets.SetSize(ninputs + 1);
xq_offsets[0] = 0;
constexpr_for<0, ninputs>([&](auto i)
{
const auto input = get<i>(inputs);
xq_offsets[i + 1] = nqp * input.size_on_qp * ctx.nentities;
});
xq_offsets.PartialSum();
InitBlockVector(xq, xq_offsets);
yq_offsets.SetSize(noutputs + 1);
yq_offsets[0] = 0;
constexpr_for<0, noutputs>([&](auto i)
{
const auto output = get<i>(outputs);
yq_offsets[i + 1] = nqp * output.size_on_qp * ctx.nentities;
});
yq_offsets.PartialSum();
InitBlockVector(yq, yq_offsets);
// Shadow blocks use the same offsets as xq so tensor_array views
shadow_xq_offsets.SetSize(xq_offsets.Size());
shadow_xq_offsets = xq_offsets;
InitBlockVector(shadow_xq, shadow_xq_offsets);
dof_ordering = ElementDofOrdering::LEXICOGRAPHIC;
const size_t direction_fd_idx = FindIdx(derivative_id, ctx.infds);
MFEM_ASSERT(direction_fd_idx != SIZE_MAX,
"derivative direction field not found in infds");
direction_fd = ctx.infds[direction_fd_idx];
}
void operator()(
const std::vector<Vector *> &xe,
const Vector *de,
std::vector<Vector *> &ye)
{
if (ctx.attr.Size() == 0) { return; }
// E -> Q
interpolate(input_to_infd, input_bases, xe, xq);
constexpr auto input_active =
detail::make_activity_map<derivative_id>(inputs_t{});
MFEM_ASSERT(de != nullptr, "derivative direction vector is null");
restriction(direction_fd, direction_rcache, *de, direction_e,
dof_ordering);
shadow_xq = 0.0;
shadow_xq.SyncToBlocks();
constexpr_for<0, ninputs>([&](auto i)
{
if (!input_active[i]) { return; }
input_bases[i].forward(direction_e, shadow_xq.GetBlock(i));
});
static_assert(detail::supports_tensor_array_qfunc<qfunc_t,
inputs_t,
outputs_t>::value,
"qfunc signature not supported by default backend Action");
// Q -> Q
yq = 0.0;
yq.SyncToBlocks();
if constexpr (detail::qfunc_uses_scratch_v<qfunc_t>)
{
detail::fwddiff<derivative_id, qfunc_t, qfunc_shadow_t, inputs_t,
outputs_t>(
qfunc,
qfunc_shadow,
xq,
shadow_xq,
yq,
gnqp,
input_qlayouts,
output_qlayouts,
std::make_index_sequence<ninputs> {},
std::make_index_sequence<noutputs> {});
}
else
{
detail::fwddiff<derivative_id, qfunc_t, inputs_t, outputs_t>(
qfunc,
xq,
shadow_xq,
yq,
gnqp,
input_qlayouts,
output_qlayouts,
std::make_index_sequence<ninputs> {},
std::make_index_sequence<noutputs> {});
}
// Q -> E
integrate(output_to_outfd, output_bases, yq, ye);
}
IntegratorContext ctx;
qfunc_t qfunc;
qfunc_shadow_t qfunc_shadow;
inputs_t inputs;
outputs_t outputs;
std::array<size_t, ninputs> input_to_infd;
std::array<size_t, noutputs> output_to_outfd;
std::array<FieldBasis, ninputs> input_bases;
std::array<FieldBasis, noutputs> output_bases;
std::array<std::vector<int>, ninputs> input_qlayouts;
std::array<std::vector<int>, noutputs> output_qlayouts;
int gnqp = 0;
Array<int> xq_offsets, shadow_xq_offsets, yq_offsets;
mutable BlockVector xq, shadow_xq, yq;
FieldDescriptor direction_fd;
ElementDofOrdering dof_ordering = ElementDofOrdering::LEXICOGRAPHIC;
mutable Vector direction_e;
mutable RestrictionCache<Entity::Element> direction_rcache;
};
} // namespace mfem::future::GlobalQFImpl
@@ -0,0 +1,242 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../../integrator_ctx.hpp"
#include "../util.hpp"
#include <array>
#include <utility>
#include <vector>
namespace mfem::future::GlobalQFImpl
{
// Q-function-shape-agnostic cached forward apply (J·v)
template<
int derivative_id,
typename inputs_t,
typename outputs_t>
struct DerivativeApply
{
static constexpr std::size_t n_inputs = tuple_size<inputs_t>::value;
static constexpr std::size_t n_outputs = tuple_size<outputs_t>::value;
DerivativeApply(
IntegratorContext ctx,
inputs_t inputs,
outputs_t outputs,
const Vector &qp_cache):
ctx(ctx), inputs(std::move(inputs)), outputs(std::move(outputs)),
qp_cache(qp_cache)
{
create_fop_to_fd(this->inputs, ctx.infds, input_to_infd);
create_fop_to_fd(this->outputs, ctx.outfds, output_to_outfd);
check_consistency(this->inputs, input_to_infd, ctx.infds);
check_consistency(this->outputs, output_to_outfd, ctx.outfds);
create_fieldbases(
this->inputs, input_to_infd, ctx.infds, ctx.ir, input_bases);
create_fieldbases(
this->outputs, output_to_outfd, ctx.outfds, ctx.ir, output_bases);
const int nqp = ctx.ir.GetNPoints();
const int ne = ctx.nentities;
num_qp = nqp;
gnqp = nqp * ne;
// Precompute Q-space BlockVector layouts
dir_q_offsets.SetSize(n_inputs + 1);
dir_q_offsets[0] = 0;
constexpr_for<0, n_inputs>([&](auto i)
{
dir_q_offsets[i + 1] =
dir_q_offsets[i] + get<i>(this->inputs).size_on_qp * nqp * ne;
});
InitBlockVector(dir_q_local, dir_q_offsets);
result_q_offsets.SetSize(n_outputs + 1);
result_q_offsets[0] = 0;
constexpr_for<0, n_outputs>([&](auto i)
{
result_q_offsets[i + 1] =
result_q_offsets[i] + get<i>(this->outputs).size_on_qp * nqp * ne;
});
InitBlockVector(result_q_local, result_q_offsets);
// Cache layout metadata (must match DerivativeSetup)
residual_size_on_qp = 0;
trial_vdim = 0;
total_trial_op_dim = 0;
constexpr auto activity =
detail::make_activity_map<derivative_id>(inputs_t{});
constexpr_for<0, n_inputs>([&](auto i)
{
if (!activity[i]) { return; }
const auto &fop = get<i>(this->inputs);
trial_vdim = fop.vdim;
total_trial_op_dim += fop.size_on_qp / fop.vdim;
});
constexpr_for<0, n_outputs>([&](auto i)
{ residual_size_on_qp += get<i>(this->outputs).size_on_qp; });
residual_size_on_qp *= trial_vdim * total_trial_op_dim;
}
void operator()(
const std::vector<Vector *> & /*xe*/,
const Vector *direction_l,
std::vector<Vector *> &ye) const
{
if (ctx.attr.Size() == 0) { return; }
MFEM_ASSERT(direction_l != nullptr,
"Global DerivativeApply: direction vector is null");
// Re-zero pre-allocated Q temporaries
dir_q_local = 0.0;
dir_q_local.SyncToBlocks();
result_q_local = 0.0;
result_q_local.SyncToBlocks();
// Restrict trial direction from the derivative field
size_t in_fd = SIZE_MAX;
constexpr_for<0, n_inputs>([&](auto i)
{
if (get<i>(inputs).GetFieldId() == derivative_id)
{
in_fd = input_to_infd[i.value];
}
});
MFEM_ASSERT(in_fd != SIZE_MAX,
"DerivativeApply: derivative field not found among inputs");
const auto &fd = ctx.infds[in_fd];
Vector dir_e;
restriction(fd, direction_rcache, *direction_l, dir_e,
ElementDofOrdering::LEXICOGRAPHIC);
// Forward the trial direction into active input Q block
constexpr_for<0, n_inputs>([&](auto s)
{
if (get<s>(inputs).GetFieldId() != derivative_id) { return; }
input_bases[s.value].forward(dir_e, dir_q_local.GetBlock(s.value));
});
const real_t *cache_ptr = qp_cache.Read();
const int res_sz = residual_size_on_qp;
const int gnqp_local = gnqp;
const int num_qp_local = num_qp;
const int trial_vdim_local = trial_vdim;
const int total_trial_op_dim_local = total_trial_op_dim;
constexpr_for<0, n_outputs>([&](auto o)
{
const int tv_o = get<o>(outputs).vdim;
const int to_o = get<o>(outputs).size_on_qp / tv_o;
const int out_base = [&]
{
int off = 0;
constexpr_for<0, o.value>([&](auto prev)
{ off += get<prev>(outputs).size_on_qp; });
return off;
}();
real_t *res_o = result_q_local.GetBlock(o.value).ReadWrite();
int m_offset = 0;
constexpr_for<0, n_inputs>([&](auto s)
{
if (get<s>(inputs).GetFieldId() != derivative_id) { return; }
const int tv = get<s>(inputs).vdim;
const int to = get<s>(inputs).size_on_qp / tv;
const real_t *dir_s = dir_q_local.GetBlock(s.value).Read();
mfem::forall(gnqp_local, [=] MFEM_HOST_DEVICE(int gq)
{
// Cache is (q, cache_idx, e): adjacent threads (adjacent gq)
// read adjacent addresses for a fixed cache_idx.
const int cache_base =
(gq % num_qp_local) +
num_qp_local * res_sz * (gq / num_qp_local);
for (int j = 0; j < tv; ++j)
{
for (int m = 0; m < to; ++m)
{
const real_t v = dir_s[(j * to + m) + (tv * to) * gq];
const int m_global = m + m_offset;
for (int i = 0; i < tv_o; ++i)
{
for (int k = 0; k < to_o; ++k)
{
const int out_comp = out_base + i * to_o + k;
const int cache_idx =
out_comp * trial_vdim_local * total_trial_op_dim_local +
j * total_trial_op_dim_local + m_global;
const real_t c =
cache_ptr[cache_base + num_qp_local * cache_idx];
res_o[(i * to_o + k) + (tv_o * to_o) * gq] += c * v;
}
}
}
}
});
m_offset += to;
});
});
result_q_local.SyncToBlocks();
// Map result Q back to output fields
constexpr_for<0, n_outputs>([&](auto o)
{
const size_t out_fd = output_to_outfd[o.value];
output_bases[o.value].transpose(result_q_local.GetBlock(o.value),
*ye[out_fd]);
});
}
private:
IntegratorContext ctx;
inputs_t inputs;
outputs_t outputs;
const Vector &qp_cache;
std::array<size_t, n_inputs> input_to_infd;
std::array<size_t, n_outputs> output_to_outfd;
std::array<FieldBasis, n_inputs> input_bases;
std::array<FieldBasis, n_outputs> output_bases;
int gnqp = 0;
int num_qp = 0;
Array<int> dir_q_offsets;
Array<int> result_q_offsets;
mutable BlockVector dir_q_local;
mutable BlockVector result_q_local;
mutable RestrictionCache<Entity::Element> direction_rcache;
int residual_size_on_qp = 0;
int trial_vdim = 0;
int total_trial_op_dim = 0;
};
} // namespace mfem::future::GlobalQFImpl
@@ -0,0 +1,260 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../../integrator_ctx.hpp"
#include "../util.hpp"
#include <array>
#include <utility>
#include <vector>
namespace mfem::future::GlobalQFImpl
{
// Q-function-shape-agnostic cached transpose apply (Jᵀ·w)
template<
int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
struct DerivativeApplyTranspose
{
static constexpr std::size_t n_inputs = tuple_size<inputs_t>::value;
static constexpr std::size_t n_outputs = tuple_size<outputs_t>::value;
DerivativeApplyTranspose(
IntegratorContext ctx,
qfunc_t /*qfunc*/,
inputs_t inputs,
outputs_t outputs,
const Vector &qp_cache):
ctx(ctx), inputs(std::move(inputs)), outputs(std::move(outputs)),
qp_cache(qp_cache), dir_out_l(n_outputs), dir_out_e(n_outputs)
{
create_fop_to_fd(this->inputs, ctx.infds, input_to_infd);
create_fop_to_fd(this->outputs, ctx.outfds, output_to_outfd);
check_consistency(this->inputs, input_to_infd, ctx.infds);
check_consistency(this->outputs, output_to_outfd, ctx.outfds);
create_fieldbases(
this->inputs, input_to_infd, ctx.infds, ctx.ir, input_bases);
create_fieldbases(
this->outputs, output_to_outfd, ctx.outfds, ctx.ir, output_bases);
const int nqp = ctx.ir.GetNPoints();
const int ne = ctx.nentities;
num_qp = nqp;
gnqp = nqp * ne;
// Precompute Q-space BlockVector layouts
dir_q_offsets.SetSize(n_outputs + 1);
dir_q_offsets[0] = 0;
constexpr_for<0, n_outputs>([&](auto i)
{
dir_q_offsets[i + 1] =
dir_q_offsets[i] + get<i>(this->outputs).size_on_qp * nqp * ne;
});
InitBlockVector(dir_q_local, dir_q_offsets);
result_q_offsets.SetSize(n_inputs + 1);
result_q_offsets[0] = 0;
constexpr_for<0, n_inputs>([&](auto i)
{
result_q_offsets[i + 1] =
result_q_offsets[i] + get<i>(this->inputs).size_on_qp * nqp * ne;
});
InitBlockVector(result_q_local, result_q_offsets);
// Cache layout metadata
residual_size_on_qp = 0;
trial_vdim = 0;
total_trial_op_dim = 0;
constexpr auto activity =
detail::make_activity_map<derivative_id>(inputs_t{});
constexpr_for<0, n_inputs>([&](auto i)
{
if (!activity[i]) { return; }
const auto &fop = get<i>(this->inputs);
trial_vdim = fop.vdim;
total_trial_op_dim += fop.size_on_qp / fop.vdim;
});
constexpr_for<0, n_outputs>([&](auto i)
{ residual_size_on_qp += get<i>(this->outputs).size_on_qp; });
residual_size_on_qp *= trial_vdim * total_trial_op_dim;
}
void operator()(
const std::vector<Vector *> & /*xe*/,
const Vector *direction_l,
std::vector<Vector *> &ye) const
{
if (ctx.attr.Size() == 0) { return; }
MFEM_ASSERT(direction_l != nullptr,
"Global DerivativeApplyTranspose: direction vector is null");
// Re-zero the pre-allocated Q temporaries
dir_q_local = 0.0;
result_q_local = 0.0;
dir_q_local.SyncToBlocks();
result_q_local.SyncToBlocks();
// Bring test cotangent to quadrature points
pull_output_cotangents_to_q(direction_l, dir_q_local);
// Contract qp_cache with test directions at quadrature points
const real_t *cache_ptr = qp_cache.Read();
const int res_sz = residual_size_on_qp;
const int gnqp_local = gnqp;
const int num_qp_local = num_qp;
const int trial_vdim_local = trial_vdim;
const int total_trial_op_dim_local = total_trial_op_dim;
constexpr_for<0, n_outputs>([&](auto o)
{
const int tv_o = get<o>(outputs).vdim;
const int to_o = get<o>(outputs).size_on_qp / tv_o;
const int out_base = [&]
{
int off = 0;
constexpr_for<0, o.value>([&](auto prev)
{ off += get<prev>(outputs).size_on_qp; });
return off;
}();
const int size_o = get<o>(outputs).size_on_qp;
const real_t *dir_o = dir_q_local.GetBlock(o.value).Read();
int m_offset = 0;
constexpr_for<0, n_inputs>([&](auto s)
{
if (get<s>(inputs).GetFieldId() != derivative_id) { return; }
const int size_s = get<s>(inputs).size_on_qp;
const int to_s = size_s / trial_vdim_local;
real_t *res_s = result_q_local.GetBlock(s.value).ReadWrite();
mfem::forall(gnqp_local, [=] MFEM_HOST_DEVICE(int gq)
{
// Cache is (q, cache_idx, e): adjacent threads (adjacent gq)
// read adjacent addresses for a fixed cache_idx.
const int cache_base =
(gq % num_qp_local) +
num_qp_local * res_sz * (gq / num_qp_local);
for (int i = 0; i < tv_o; ++i)
{
for (int k = 0; k < to_o; ++k)
{
const int out_comp = out_base + i * to_o + k;
const real_t w = dir_o[(i * to_o + k) + size_o * gq];
for (int j = 0; j < trial_vdim_local; ++j)
{
for (int m = 0; m < to_s; ++m)
{
const int m_global = m + m_offset;
const int cache_idx =
out_comp * trial_vdim_local * total_trial_op_dim_local +
j * total_trial_op_dim_local + m_global;
const real_t c =
cache_ptr[cache_base + num_qp_local * cache_idx];
res_s[(j * to_s + m) + size_s * gq] += c * w;
}
}
}
}
});
m_offset += to_s;
});
});
// Map result Q back to the trial (input) fields
constexpr_for<0, n_inputs>([&](auto s)
{
if (get<s>(inputs).GetFieldId() != derivative_id) { return; }
const size_t in_fd = input_to_infd[s.value];
input_bases[s.value].transpose(
result_q_local.GetBlock(s.value), *ye[in_fd]);
});
}
private:
IntegratorContext ctx;
inputs_t inputs;
outputs_t outputs;
const Vector &qp_cache;
std::array<size_t, n_inputs> input_to_infd;
std::array<size_t, n_outputs> output_to_outfd;
std::array<FieldBasis, n_inputs> input_bases;
std::array<FieldBasis, n_outputs> output_bases;
int gnqp = 0;
int num_qp = 0;
// Pre-allocated Q-space temporaries
Array<int> dir_q_offsets;
Array<int> result_q_offsets;
mutable BlockVector dir_q_local;
mutable BlockVector result_q_local;
// Pre-allocated owning storage for output cotangent temporaries
mutable std::array<Vector, n_outputs> dir_out_l_owned;
mutable std::array<Vector, n_outputs> dir_out_e_owned;
mutable std::vector<Vector *> dir_out_l;
mutable std::vector<Vector *> dir_out_e;
mutable RestrictionCache<Entity::Element> out_rcache;
int residual_size_on_qp = 0;
int trial_vdim = 0;
int total_trial_op_dim = 0;
/// Pull output cotangents from L-space into the pre-allocated Q BlockVector
void pull_output_cotangents_to_q(const Vector *direction_l,
BlockVector &dir_q) const
{
int l_offset = 0;
constexpr_for<0, n_outputs>([&](auto i)
{
const size_t outfd = output_to_outfd[i];
const auto &fd = ctx.outfds[outfd];
const int l_size = GetVSize(fd);
dir_out_l_owned[i] =
Vector(*const_cast<Vector *>(direction_l), l_offset, l_size);
dir_out_e_owned[i].SetSize(0);
dir_out_e_owned[i].UseDevice(true);
dir_out_l[i] = &dir_out_l_owned[i];
dir_out_e[i] = &dir_out_e_owned[i];
l_offset += l_size;
});
restriction(ctx.outfds, out_rcache, dir_out_l, dir_out_e);
constexpr_for<0, n_outputs>([&](auto i)
{
output_bases[i.value].forward(*dir_out_e[i], dir_q.GetBlock(i.value));
});
dir_q.SyncToBlocks();
}
};
} // namespace mfem::future::GlobalQFImpl
@@ -0,0 +1,245 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../../integrator_ctx.hpp"
#include "../util.hpp"
#include <utility>
namespace mfem::future::GlobalQFImpl
{
template<
int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t,
size_t ninputs = tuple_size<inputs_t>::value,
size_t noutputs = tuple_size<outputs_t>::value>
struct DerivativeSetup
{
using qfunc_shadow_t = detail::qfunc_shadow_t<qfunc_t>;
DerivativeSetup(
IntegratorContext ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs,
Vector &qp_cache) :
ctx(ctx),
qfunc(qfunc),
qfunc_shadow(detail::MakeQFunctionShadowStorage(this->qfunc)),
inputs(inputs),
outputs(outputs),
qp_cache(qp_cache)
{
create_fop_to_fd(inputs, ctx.infds, input_to_infd);
create_fop_to_fd(outputs, ctx.outfds, output_to_outfd);
check_consistency(inputs, input_to_infd, ctx.infds);
check_consistency(outputs, output_to_outfd, ctx.outfds);
create_fieldbases(inputs, input_to_infd, ctx.infds, ctx.ir, input_bases);
create_fieldbases(outputs, output_to_outfd, ctx.outfds, ctx.ir, output_bases);
create_qlayouts(inputs, ctx.in_qlayouts, input_qlayouts);
create_qlayouts(outputs, ctx.out_qlayouts, output_qlayouts);
const int nqp = ctx.ir.GetNPoints();
num_qp = nqp;
nentities = ctx.nentities;
gnqp = nqp * nentities;
xq_offsets.SetSize(ninputs + 1);
xq_offsets[0] = 0;
constexpr_for<0, ninputs>([&](auto i)
{
xq_offsets[i + 1] = nqp * get<i>(inputs).size_on_qp * nentities;
});
xq_offsets.PartialSum();
InitBlockVector(xq, xq_offsets);
shadow_xq_offsets.SetSize(xq_offsets.Size());
shadow_xq_offsets = xq_offsets;
InitBlockVector(shadow_xq, shadow_xq_offsets);
yq_offsets.SetSize(noutputs + 1);
yq_offsets[0] = 0;
constexpr_for<0, noutputs>([&](auto o)
{
yq_offsets[o + 1] = nqp * get<o>(outputs).size_on_qp * nentities;
});
yq_offsets.PartialSum();
InitBlockVector(yq, yq_offsets);
total_out_size_on_qp = 0;
constexpr_for<0, noutputs>([&](auto o)
{
total_out_size_on_qp += get<o>(outputs).size_on_qp;
out_vdim[o] = get<o>(outputs).vdim;
out_op_dim[o] = get<o>(outputs).size_on_qp / get<o>(outputs).vdim;
});
activity_map = detail::make_activity_map<derivative_id>(inputs_t {});
trial_vdim = 0;
total_trial_op_dim = 0;
constexpr_for<0, ninputs>([&](auto i)
{
if (!activity_map[i]) { return; }
const auto inp = get<i>(inputs);
trial_vdim = inp.vdim;
total_trial_op_dim += inp.size_on_qp / inp.vdim;
});
constexpr_for<0, ninputs>([&](auto i)
{
input_size_on_qp_arr[i] = get<i>(inputs).size_on_qp;
});
residual_size_on_qp = total_out_size_on_qp * trial_vdim * total_trial_op_dim;
qp_cache.SetSize(residual_size_on_qp * num_qp * nentities);
qp_cache.UseDevice(true);
}
void operator()(const std::vector<Vector *> &xe)
{
if (ctx.attr.Size() == 0) { return; }
interpolate(input_to_infd, input_bases, xe, xq);
const int gnqp_local = gnqp;
const int num_qp_local = num_qp;
const int trial_vdim_local = trial_vdim;
const int total_trial_op_dim_local = total_trial_op_dim;
const int residual_size_local = residual_size_on_qp;
for (int j = 0; j < trial_vdim; j++)
{
int m_offset = 0;
constexpr_for<0, ninputs>([&](auto s)
{
if (!activity_map[s]) { return; }
const int input_vdim_s = get<s>(inputs).vdim;
const int input_size_s = input_size_on_qp_arr[s];
const int trial_op_dim_s = input_size_s / input_vdim_s;
for (int m = 0; m < trial_op_dim_s; m++)
{
shadow_xq = 0.0;
shadow_xq.SyncToBlocks();
// Set component (j + input_vdim_s * m) to 1 at all QPs
const int c_shadow = j + input_vdim_s * m;
real_t *shadow_ptr = shadow_xq.GetBlock(s.value).ReadWrite();
mfem::forall(gnqp_local, [=] MFEM_HOST_DEVICE(int gq)
{
shadow_ptr[c_shadow + input_size_s * gq] = 1.0;
});
yq = 0.0;
yq.SyncToBlocks();
if constexpr (detail::qfunc_uses_scratch_v<qfunc_t>)
{
detail::fwddiff<derivative_id, qfunc_t, qfunc_shadow_t,
inputs_t, outputs_t>(
qfunc, qfunc_shadow, xq, shadow_xq, yq, gnqp,
input_qlayouts, output_qlayouts,
std::make_index_sequence<ninputs> {},
std::make_index_sequence<noutputs> {});
}
else
{
detail::fwddiff<derivative_id, qfunc_t, inputs_t, outputs_t>(
qfunc, xq, shadow_xq, yq, gnqp,
input_qlayouts, output_qlayouts,
std::make_index_sequence<ninputs> {},
std::make_index_sequence<noutputs> {});
}
yq.SyncToBlocks();
real_t *cache_d = qp_cache.ReadWrite();
// Write yq into the cache column
const int m_global = m + m_offset;
const int j_cur = j;
int out_offset = 0;
constexpr_for<0, noutputs>([&](auto o)
{
const int test_vdim_o = out_vdim[o];
const int test_op_dim_o = out_op_dim[o];
const int yq_out_size = test_vdim_o * test_op_dim_o;
const int out_offset_o = out_offset;
const real_t *yq_d = yq.GetBlock(o.value).Read();
// The cache is (q, cache_idx, e) with the quadrature index
// fastest, so gq is the fastest-varying thread index to keep
// the stores coalesced.
mfem::forall(gnqp_local * yq_out_size, [=] MFEM_HOST_DEVICE(int idx)
{
const int gq = idx % gnqp_local;
const int c_out = idx / gnqp_local;
const int q = gq % num_qp_local;
const int entity = gq / num_qp_local;
const int out_comp = out_offset_o + c_out;
const int cache_idx =
out_comp * trial_vdim_local * total_trial_op_dim_local +
j_cur * total_trial_op_dim_local +
m_global;
cache_d[q + num_qp_local *
(cache_idx + residual_size_local * entity)] =
yq_d[c_out + yq_out_size * gq];
});
out_offset += yq_out_size;
});
}
m_offset += trial_op_dim_s;
});
}
}
IntegratorContext ctx;
qfunc_t qfunc;
qfunc_shadow_t qfunc_shadow;
inputs_t inputs;
outputs_t outputs;
Vector &qp_cache;
std::array<size_t, ninputs> input_to_infd;
std::array<size_t, noutputs> output_to_outfd;
std::array<FieldBasis, ninputs> input_bases;
std::array<FieldBasis, noutputs> output_bases;
std::array<std::vector<int>, ninputs> input_qlayouts;
std::array<std::vector<int>, noutputs> output_qlayouts;
int gnqp = 0;
int num_qp = 0;
int nentities = 0;
Array<int> xq_offsets, shadow_xq_offsets, yq_offsets;
mutable BlockVector xq, shadow_xq, yq;
int total_out_size_on_qp = 0;
int trial_vdim = 0;
int total_trial_op_dim = 0;
int residual_size_on_qp = 0;
std::array<int, noutputs> out_vdim {};
std::array<int, noutputs> out_op_dim {};
std::array<int, ninputs> input_size_on_qp_arr {};
std::array<bool, ninputs> activity_map {};
};
} // namespace mfem::future::GlobalQFImpl
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// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "action.hpp"
#include "derivative_action.hpp"
#include "derivative_setup.hpp"
#include "derivative_apply_transpose.hpp"
#include "../local_qf/derivative_apply.hpp"
#include "../local_qf/derivative_assemble.hpp"
#include "../local_qf/derivative_assemble_diagonal.hpp"
#include "../scratch_bank.hpp"
namespace mfem::future
{
namespace detail
{
template <typename T>
struct LocalQFShapeArg
{
using type = std::remove_const_t<T>&;
};
template <typename scalar_t, int ndims, int... tensor_sizes>
struct LocalQFShapeArg<tensor_ndarray<scalar_t, ndims, tensor_sizes...>>
{
using scalar_type = std::remove_const_t<scalar_t>;
using type = std::conditional_t<
sizeof...(tensor_sizes) == 0,
scalar_type,
tensor<scalar_type, tensor_sizes...>>&;
};
template <typename scalar_t, int... tensor_sizes>
struct LocalQFShapeArg<tensor<scalar_t, tensor_sizes...>>
{
using scalar_type = std::remove_const_t<scalar_t>;
using type = std::conditional_t<
sizeof...(tensor_sizes) == 0,
scalar_type,
tensor<scalar_type, tensor_sizes...>>&;
};
template <typename qf_param_ts>
struct LocalQFShapeFunction;
template <typename... qf_param_ts>
struct LocalQFShapeFunction<tuple<qf_param_ts...>>
{
void operator()(
typename LocalQFShapeArg<qf_param_decay_t<qf_param_ts>>::type...) const;
};
template <typename qfunc_t>
using LocalQFShapeFunctionFor = LocalQFShapeFunction<
typename get_function_signature<qfunc_t>::type::parameter_ts>;
} // namespace detail
struct GlobalQFBackend
{
/**
* @brief Make an action for a global Q-function.
*
* @param ctx The integrator context.
* @param args The arguments to the action.
* @return The action.
*/
template<
typename qfunc_t,
typename inputs_t,
typename outputs_t>
auto static MakeAction(
const IntegratorContext &ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs)
{
return GlobalQFImpl::Action(ctx, qfunc, inputs, outputs);
}
/**
* @brief Make a derivative action for a global Q-function.
*
* @tparam derivative_id The id of the derivative.
* @param ctx The integrator context.
* @param args The arguments to the derivative action.
* @return The derivative action.
*/
template<
int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
auto static MakeDerivativeAction(
const IntegratorContext &ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs)
{
return GlobalQFImpl::DerivativeAction<
derivative_id, qfunc_t, inputs_t, outputs_t>(
ctx, qfunc, inputs, outputs);
}
/**
* @brief Make a derivative setup for a global Q-function.
*
* @tparam derivative_id The id of the derivative.
* @param ctx The integrator context.
* @param args The arguments to the derivative setup.
* @return The derivative setup.
*/
template<
int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
auto static MakeDerivativeSetup(
const IntegratorContext &ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs,
Vector &qp_cache)
{
return GlobalQFImpl::DerivativeSetup<
derivative_id, qfunc_t, inputs_t, outputs_t>(
ctx, qfunc, inputs, outputs, qp_cache);
}
template<
int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
auto static MakeDerivativeApply(
const IntegratorContext &ctx,
const qfunc_t & /*qfunc*/,
inputs_t inputs,
outputs_t outputs,
const Vector &qp_cache)
{
return LocalQFImpl::DerivativeApply<
derivative_id,
detail::LocalQFShapeFunctionFor<qfunc_t>,
inputs_t,
outputs_t>(ctx,
detail::LocalQFShapeFunctionFor<qfunc_t> {},
inputs,
outputs,
qp_cache);
}
template<
int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
auto static MakeDerivativeApplyTranspose(
const IntegratorContext &ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs,
const Vector &qp_cache)
{
return GlobalQFImpl::DerivativeApplyTranspose<
derivative_id, qfunc_t, inputs_t, outputs_t>(
ctx, qfunc, inputs, outputs, qp_cache);
}
template<
int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
auto static MakeDerivativeAssemble(
const IntegratorContext &ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs,
const Vector &qp_cache)
{
return LocalQFImpl::DerivativeAssemble<
derivative_id, qfunc_t, inputs_t, outputs_t>(
ctx, qfunc, inputs, outputs, qp_cache);
}
template<
int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
auto static MakeDerivativeAssembleDiagonal(
const IntegratorContext &ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs,
const Vector &qp_cache)
{
return LocalQFImpl::DerivativeAssembleDiagonal<
derivative_id, qfunc_t, inputs_t, outputs_t>(
ctx, qfunc, inputs, outputs, qp_cache);
}
};
} // namespace mfem::future
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// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "fem/dfem/fieldoperator.hpp"
#include "kernels.hpp"
#include "util.hpp"
#include "../../integrator_ctx.hpp"
#include "../util.hpp"
namespace mfem::future::LocalQFImpl
{
template<typename qfunc_t, typename inputs_t, typename outputs_t>
class Action
{
static constexpr auto inout_tuple =
merge_mfem_tuples_as_empty_std_tuple(inputs_t {}, outputs_t{});
static constexpr auto filtered_inout_tuple = filter_fields(inout_tuple);
static constexpr size_t nfields =
count_unique_field_ids(filtered_inout_tuple);
using qf_signature = typename get_function_signature<qfunc_t>::type;
using qf_param_ts = typename qf_signature::parameter_ts;
using args_tuple_t = decay_tuple<qf_param_ts>;
static constexpr std::size_t n_inputs = tuple_size<inputs_t>::value;
static constexpr std::size_t n_outputs = tuple_size<outputs_t>::value;
static_assert(n_inputs + n_outputs == tuple_size<qf_param_ts>::value,
"LocalQF: q-function arity must match inputs + outputs");
const qfunc_t qfunc;
const inputs_t inputs;
const outputs_t outputs;
const IntegratorContext ctx;
const std::vector<const DofToQuad *> dtqs;
// inputs: dtq, idx, B, G, d1d, q1d, vdim
const std::array<DofToQuadMap, n_inputs> input_dtq;
const std::array<size_t, n_inputs> input_idx; // input to field
const std::array<const real_t *, n_inputs> input_B, input_G;
const std::array<int, n_inputs> input_d1d, input_q1d, input_vdim;
// outputs: dtq, idx, B, G, d1d, q1d, vdim
const std::array<DofToQuadMap, n_outputs> output_dtq;
const std::array<size_t, n_outputs> output_idx; // output to field
const std::array<const real_t *, n_outputs> output_B, output_G;
const std::array<int, n_outputs> output_d1d, output_q1d, output_vdim;
// other constants
const int dim, ne, nq, q1d;
public:
////////////////////////////////////////////////////////
Action() = delete;
Action(IntegratorContext ctx,
qfunc_t qfunc,
inputs_t inputs,
outputs_t outputs):
qfunc(std::move(qfunc)), inputs(inputs), outputs(outputs), ctx(ctx),
dtqs(make_dtqs(ctx)),
// inputs: dtq, idx, B, G, d1d, q1d, vdim
input_dtq(create_dtq_maps<Entity::Element>(
inputs,
dtqs,
create_union_field_map_for_dtq(ctx, inputs),
ctx.unionfds,
ctx.ir)),
input_idx(create_input_vector_map(ctx, inputs)),
input_B(get_B(input_dtq)), input_G(get_G(input_dtq)),
input_d1d(get_D1D(input_dtq)), input_q1d(get_Q1D(input_dtq)),
input_vdim(get_vdim(inputs)),
// outputs: dtq, idx, B, G, d1d, q1d, vdim
output_dtq(create_dtq_maps<Entity::Element>(
outputs,
dtqs,
create_union_field_map_for_dtq(ctx, outputs),
ctx.unionfds,
ctx.ir)),
output_idx(create_output_vector_map(ctx, outputs)),
output_B(get_B(output_dtq)), output_G(get_G(output_dtq)),
output_d1d(get_D1D(output_dtq)), output_q1d(get_Q1D(output_dtq)),
output_vdim(get_vdim(outputs)),
// other constants
dim(ctx.mesh.Dimension()), ne(ctx.nentities), nq(ctx.ir.GetNPoints()),
q1d(tensor_1d_size(nq, dim))
{
MFEM_ASSERT(ctx.unionfds.size() == nfields,
"LocalQFBackend: unionfds size mismatch");
}
template<typename Backend>
void run_kernels(const std::vector<Vector *> &xe,
std::vector<Vector *> &ye) const
{
Backend::Run(dim,
q1d,
// arguments
ctx,
qfunc,
// inputs
input_idx,
input_B,
input_G,
input_vdim,
input_d1d,
input_q1d,
// outputs
output_idx,
output_B,
output_G,
output_vdim,
output_d1d,
output_q1d,
// input and output vectors
xe,
ye,
// fallback arguments
dim,
q1d);
}
void operator()(const std::vector<Vector *> &xe,
std::vector<Vector *> &ye) const
{
if (q1d <= LocalQFLOBackendMQ1())
{
run_kernels<ActionLO>(xe, ye);
}
else if (q1d <= LocalQFHOBackendMQ1())
{
run_kernels<ActionHO>(xe, ye);
}
else
{
MFEM_ABORT("Unsupported quadrature order for LocalQF backend");
}
}
////////////////////////////////////////////////////////
template<typename backend_t = LocalQFLOBackend<3>, int T_Q1D = 0>
static void
action_callback(const IntegratorContext &ctx,
const qfunc_t &qfunc,
// inputs: idx, B, G, vdim, d1d, q1d
const std::array<size_t, n_inputs> &in_idx,
const std::array<const real_t *, n_inputs> in_B,
const std::array<const real_t *, n_inputs> in_G,
const std::array<int, n_inputs> &in_vdim,
const std::array<int, n_inputs> &in_d1d,
const std::array<int, n_inputs> &in_q1d,
// outputs: idx, B, G, vdim, d1d, q1d
const std::array<size_t, n_outputs> &out_idx,
const std::array<const real_t *, n_outputs> out_B,
const std::array<const real_t *, n_outputs> out_G,
const std::array<int, n_outputs> &out_vdim,
const std::array<int, n_outputs> &out_d1d,
const std::array<int, n_outputs> &out_q1d,
const std::vector<Vector *> &xe,
std::vector<Vector *> &ye,
// fallback arguments
const int dim,
const int q1d)
{
if (ctx.attr.Size() == 0) { return; }
MFEM_CONTRACT_VAR(dim);
MFEM_ASSERT(dim == ctx.mesh.Dimension(), "Dimension mismatch");
static constexpr auto B2D = backend_t::DIM == 2;
static constexpr auto MQ1 = T_Q1D ? T_Q1D : backend_t::Q1D;
static constexpr auto MTPB = backend_t::MAX_THREADS_PER_BLOCK();
const int ne = ctx.nentities;
constexpr auto k_dim = [](const int k) { return k * k * (B2D ? 1 : k); };
// --------------------------------------------------
// INPUTS: XE, 3(max DIM) + 1(VDIM) + 1(number of elements)
// --------------------------------------------------
std::array<DeviceTensor<3 + 1 + 1, const real_t>, n_inputs> in_XE;
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
const size_t k = in_idx[i];
const int d = in_d1d[i], q = in_q1d[i], v = in_vdim[i];
using FOP = tuple_element_t<i, inputs_t>;
if constexpr (is_value_fop_v<FOP> || is_gradient_fop_v<FOP>)
{
MFEM_VERIFY(xe[k]->Size() == k_dim(d) * v * ne, "Size mismatch");
in_XE[i] = Reshape(xe[k]->Read(), d, d, B2D ? 1 : d, v, ne);
}
else if constexpr (is_identity_fop_v<FOP>)
{
MFEM_VERIFY(xe[k]->Size() == k_dim(q) * v * ne, "Size mismatch");
in_XE[i] = Reshape(xe[k]->Read(), v, q, q, B2D ? 1 : q, ne);
}
else if constexpr (is_weight_fop_v<FOP>)
{
MFEM_VERIFY(ctx.ir.GetNPoints() == k_dim(q1d),
"tensor-product IR expected");
in_XE[i] = Reshape(
ctx.ir.GetWeights().Read(), q1d, q1d, B2D ? 1 : q1d, 1, 1);
}
else
{
static_assert(false, "Unsupported");
}
});
// --------------------------------------------------
// OUTPUTS: YE, 3(max DIM) + 1(VDIM) + 1(number of elements)
// --------------------------------------------------
std::array<DeviceTensor<3 + 1 + 1, real_t>, n_outputs> out_YE;
for_constexpr<n_outputs>([&](auto ic)
{
constexpr size_t i = ic.value;
const size_t k = out_idx[i];
const int d = out_d1d[i], q = out_q1d[i], v = out_vdim[i];
using FOP = tuple_element_t<i, outputs_t>;
if constexpr (is_gradient_fop_v<FOP> || is_value_fop_v<FOP>)
{
MFEM_ASSERT(ye[k]->Size() == k_dim(d) * v * ne, "Size mismatch");
out_YE[i] = Reshape(ye[k]->ReadWrite(), d, d, B2D ? 1 : d, v, ne);
}
else if constexpr (is_identity_fop_v<FOP> || is_functionalvalue_fop_v<FOP>)
{
MFEM_ASSERT(ye[k]->Size() == k_dim(q) * v * ne, "Size mismatch");
out_YE[i] = Reshape(ye[k]->ReadWrite(), v, q, q, B2D ? 1 : q, ne);
}
else
{
static_assert(false, "Unsupported FieldOperator");
}
});
const auto d_attr = ctx.attr.Read();
const bool has_attr = ctx.attr.Size() > 0;
const auto d_elem_attr = ctx.elem_attr->Read();
dfem::forall<MTPB>(
[=] MFEM_HOST_DEVICE(const int e, void *)
{
if (has_attr && !d_attr[d_elem_attr[e] - 1]) { return; }
// -----------------------------------------------
// Inputs and outputs argument registers
// -----------------------------------------------
args_reg_t<backend_t, qfunc_t, inputs_t, outputs_t, MQ1> rargs;
// -----------------------------------------------
// Shared memory
// -----------------------------------------------
MFEM_SHARED typename backend_t::Shared smem;
// -----------------------------------------------
// Load inputs
// -----------------------------------------------
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
const auto &XE = in_XE[i];
const int d = in_d1d[i], q = in_q1d[i], Q1D = q1d;
;
const real_t *B = in_B[i], *G = in_G[i];
auto &rarg = get<i>(rargs);
using FOP = tuple_element_t<i, inputs_t>;
if constexpr (is_value_fop<FOP>::value)
{
backend_t::LoadValue(smem, e, d, q, Q1D, B, XE, rarg);
}
else if constexpr (is_gradient_fop_v<FOP>)
{
using XE_t = decltype(XE);
using rarg_t = decltype(rarg);
using qf_param_t =
typename qf_param_slot<qfunc_t, i>::qf_decay_param_t;
constexpr auto RNK = qf_param_slot<qfunc_t, i>::extents.size();
backend_t::template LoadGradient<RNK, rarg_t, XE_t, qf_param_t>(
smem, e, d, q, q1d, B, G, XE, rarg);
}
else if constexpr (is_weight_fop_v<FOP> || is_identity_fop_v<FOP>)
{
// qp values are read directly from in_XE / IR
}
else
{
static_assert(false, "Unsupported");
}
});
// -----------------------------------------------
// Evaluate the quadrature function
// Warning: no 'DIRECT' on the 'Z' direction,
// as one backend may need to iterate over it.
// -----------------------------------------------
MFEM_FOREACH_THREAD(qz, z, (B2D ? 1 : q1d))
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
args_tuple_t qargs;
// --------------------------------------
// Pulling arguments from registers to qargs tuple
// --------------------------------------
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
auto &qarg = get<i>(qargs);
const auto &XE = in_XE[i];
using FOP = tuple_element_t<i, inputs_t>;
using ARG =
typename qf_param_slot<qfunc_t, i>::qf_reg_param_t;
if constexpr (is_identity_fop_v<FOP>)
{
using DT =
typename qf_param_slot<qfunc_t, i>::qf_decay_param_t;
if constexpr (qf_param_uses_dual_v<DT>)
{
qarg = backend_t::template identity_qp_pull_dual<DT>(
false, XE, XE, qx, qy, qz, e);
}
else
{
qarg = as_tensor<ARG>(&XE(0, qx, qy, qz, e));
}
}
else if constexpr (is_weight_fop_v<FOP>)
{
qarg = XE(qx, qy, qz, 0, 0);
}
else if constexpr (is_value_fop_v<FOP> ||
is_gradient_fop_v<FOP>)
{
qarg = backend_t::template qp_pull<ARG>(
get<i>(rargs), qx, qy, qz);
}
else
{
static_assert(false, "Unsupported");
}
});
// --------------------------------------
// Call the quadrature function
// --------------------------------------
call_qfunc_no_move(qfunc, qargs);
// --------------------------------------
// Pushing arguments from qargs tuple to registers
// --------------------------------------
for_constexpr<n_outputs>([&](auto ic)
{
constexpr size_t i = ic.value, o = n_inputs + i;
const auto &qarg = get<o>(qargs);
const auto &YE = out_YE[i];
using FOP = tuple_element_t<i, outputs_t>;
using ARG =
typename qf_param_slot<qfunc_t, o>::qf_reg_param_t;
if constexpr (is_identity_fop_v<FOP> ||
is_functionalvalue_fop_v<FOP>)
{
using DT =
typename qf_param_slot<qfunc_t, o>::qf_decay_param_t;
if constexpr (qf_param_uses_dual_v<DT>)
{
backend_t::identity_qp_write_value(
YE, qx, qy, qz, e, qarg);
}
else
{
as_tensor<ARG>(&YE(0, qx, qy, qz, e)) = qarg;
}
}
else if constexpr (is_value_fop_v<FOP> ||
is_gradient_fop_v<FOP>)
{
auto &rarg = get<o>(rargs);
backend_t::template qp_push<ARG>(
rarg, qx, qy, qz, qarg);
}
else
{
static_assert(false, "Unsupported");
}
});
}
}
}
MFEM_SYNC_THREAD;
// -----------------------------------------------
// Integrate outputs
// -----------------------------------------------
for_constexpr<n_outputs>([&](auto ic)
{
constexpr size_t i = ic.value, o = n_inputs + i;
const int d = out_d1d[i], q = out_q1d[i], Q1D = q1d;
const auto B = out_B[i], G = out_G[i];
const auto &YE = out_YE[i];
auto &rarg = get<o>(rargs);
using FOP = tuple_element_t<i, outputs_t>;
if constexpr (is_value_fop_v<FOP>)
{
backend_t::WriteValue(smem, e, d, q, q1d, B, YE, rarg);
}
else if constexpr (is_gradient_fop_v<FOP>)
{
using YE_t = decltype(YE);
using rarg_t = decltype(rarg);
// Both the rank and the extents have to come from the output
// parameter slot o, not from the output index i.
using qf_param_t =
typename qf_param_slot<qfunc_t, o>::qf_decay_param_t;
constexpr auto RNK = qf_param_slot<qfunc_t, o>::extents.size();
backend_t::template WriteGradient<RNK, rarg_t, YE_t, qf_param_t>(
smem, e, d, q, Q1D, B, G, YE, rarg);
}
else if constexpr (is_identity_fop_v<FOP> ||
is_functionalvalue_fop_v<FOP>)
{
// nothing to do
}
else
{
static_assert(false, "Unsupported");
}
});
},
ne,
backend_t::thread_blocks(compute_kernel_thread_1d<inputs_t, outputs_t>(
q1d, in_d1d, out_d1d)),
0,
nullptr);
}
using KernelType = decltype(&Action::action_callback<>);
MFEM_REGISTER_KERNELS_HEADER_ONLY(ActionLO, KernelType, (int, int) );
MFEM_REGISTER_KERNELS_HEADER_ONLY(ActionHO, KernelType, (int, int) );
};
// Low Order kernels
template<typename qfunc_t, typename inputs_t, typename outputs_t>
template<int DIM, int Q1D>
inline typename Action<qfunc_t, inputs_t, outputs_t>::KernelType
Action<qfunc_t, inputs_t, outputs_t>::ActionLO::Kernel()
{
static_assert(Q1D <= LocalQFLOBackend<DIM>::MQ1);
using action_t = Action<qfunc_t, inputs_t, outputs_t>;
return action_t::template action_callback<LocalQFLOBackend<DIM, Q1D>>;
}
// Low Order fallback
template<typename qfunc_t, typename inputs_t, typename outputs_t>
inline typename Action<qfunc_t, inputs_t, outputs_t>::KernelType
Action<qfunc_t, inputs_t, outputs_t>::ActionLO::Fallback(int dim, int q1d)
{
using action_t = Action<qfunc_t, inputs_t, outputs_t>;
using ActionLO = typename action_t::ActionLO;
if (dim == 2)
{
return DispatchLOKernelByQ1D<ActionLO, 2>(q1d);
}
else if (dim == 3)
{
return DispatchLOKernelByQ1D<ActionLO, 3>(q1d);
}
else
{
MFEM_ABORT("Unsupported dimension");
return nullptr;
}
}
// High Order kernels
template<typename qfunc_t, typename inputs_t, typename outputs_t>
template<int DIM, int Q1D>
inline typename Action<qfunc_t, inputs_t, outputs_t>::KernelType
Action<qfunc_t, inputs_t, outputs_t>::ActionHO::Kernel()
{
using action_t = Action<qfunc_t, inputs_t, outputs_t>;
return action_t::template action_callback<LocalQFHOBackend<DIM>, Q1D>;
}
// High Order fallback
template<typename qfunc_t, typename inputs_t, typename outputs_t>
inline typename Action<qfunc_t, inputs_t, outputs_t>::KernelType
Action<qfunc_t, inputs_t, outputs_t>::ActionHO::Fallback(int dim, int q1d)
{
using action_t = Action<qfunc_t, inputs_t, outputs_t>;
using ActionHO = typename action_t::ActionHO;
if (dim == 2)
{
return DispatchHOKernelByQ1D<ActionHO, 2>(q1d);
}
else if (dim == 3)
{
return DispatchHOKernelByQ1D<ActionHO, 3>(q1d);
}
else
{
MFEM_ABORT("Unsupported dimension");
return nullptr;
}
}
} // namespace mfem::future::LocalQFImpl
@@ -0,0 +1,763 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../../integrator_ctx.hpp"
#include "kernels.hpp"
#include "util.hpp"
namespace mfem::future::LocalQFImpl
{
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
class DerivativeAction
{
static constexpr auto inout_tuple =
merge_mfem_tuples_as_empty_std_tuple(inputs_t {}, outputs_t{});
static constexpr auto filtered_inout_tuple = filter_fields(inout_tuple);
static constexpr size_t nfields =
count_unique_field_ids(filtered_inout_tuple);
using qf_signature = typename get_function_signature<qfunc_t>::type;
using qf_param_ts = typename qf_signature::parameter_ts;
using args_tuple_t = decay_tuple<qf_param_ts>;
static constexpr std::size_t n_inputs = tuple_size<inputs_t>::value;
static constexpr std::size_t n_outputs = tuple_size<outputs_t>::value;
static_assert(n_inputs + n_outputs == tuple_size<qf_param_ts>::value,
"LocalQF: q-function arity must match inputs + outputs");
qfunc_t qfunc;
const inputs_t inputs;
const outputs_t outputs;
const IntegratorContext ctx;
const std::vector<const DofToQuad *> dtqs;
// inputs: dtq, idx, B, G, d1d, q1d, vdim
const std::array<DofToQuadMap, n_inputs> input_dtq;
const std::array<size_t, n_inputs> input_idx;
const std::array<const real_t *, n_inputs> input_B, input_G;
const std::array<int, n_inputs> input_d1d, input_q1d, input_vdim;
// outputs: dtq, idx, B, G, d1d, q1d, vdim
const std::array<DofToQuadMap, n_outputs> output_dtq;
const std::array<size_t, n_outputs> output_idx;
const std::array<const real_t *, n_outputs> output_B, output_G;
const std::array<int, n_outputs> output_d1d, output_q1d, output_vdim;
// other constants
const int dim, ne, nq, q1d;
std::array<bool, n_inputs> input_is_dependent;
FieldDescriptor direction_fd;
mutable Vector direction_e;
mutable RestrictionCache<Entity::Element> direction_rcache;
public:
//////////////////////////////////////////////////////////////////
DerivativeAction() = delete;
DerivativeAction(IntegratorContext ctx,
qfunc_t qfunc,
inputs_t inputs,
outputs_t outputs):
qfunc(std::move(qfunc)), inputs(inputs), outputs(outputs), ctx(ctx),
dtqs(make_dtqs(ctx)),
// inputs: dtq, idx, B, G, d1d, q1d, vdim
input_dtq(create_dtq_maps<Entity::Element>(
inputs,
dtqs,
create_union_field_map_for_dtq(ctx, inputs),
ctx.unionfds,
ctx.ir)),
input_idx(create_input_vector_map(ctx, inputs)),
input_B(get_B(input_dtq)), input_G(get_G(input_dtq)),
input_d1d(get_D1D(input_dtq)), input_q1d(get_Q1D(input_dtq)),
input_vdim(get_vdim(inputs)),
// outputs: dtq, idx, B, G, d1d, q1d, vdim
output_dtq(create_dtq_maps<Entity::Element>(
outputs,
dtqs,
create_union_field_map_for_dtq(ctx, outputs),
ctx.unionfds,
ctx.ir)),
output_idx(create_output_vector_map(ctx, outputs)),
output_B(get_B(output_dtq)), output_G(get_G(output_dtq)),
output_d1d(get_D1D(output_dtq)), output_q1d(get_Q1D(output_dtq)),
output_vdim(get_vdim(outputs)),
// other constants
dim(ctx.mesh.Dimension()), ne(ctx.nentities), nq(ctx.ir.GetNPoints()),
q1d(tensor_1d_size(nq, dim))
{
MFEM_ASSERT(ctx.unionfds.size() == nfields,
"LocalQFBackend: unionfds size mismatch");
// Determine which inputs are dependent on the derivative direction
auto dependency_map = make_dependency_map(inputs);
auto it = dependency_map.find(derivative_id);
MFEM_ASSERT(it != dependency_map.end(),
"Derivative ID not found in dependency map");
input_is_dependent = it->second;
// Find direction field index
int direction_field_idx = -1;
for (size_t uf = 0; uf < nfields; uf++)
{
if (static_cast<int>(ctx.unionfds[uf].id) == derivative_id)
{
direction_field_idx = static_cast<int>(uf);
break;
}
}
MFEM_ASSERT(
direction_field_idx != -1,
"LocalQFBackend: derivative direction field not found in unionfds");
direction_fd = ctx.unionfds[static_cast<size_t>(direction_field_idx)];
}
//////////////////////////////////////////////////////////////////
template<typename Backend>
void run_kernels(const std::vector<Vector *> &xe,
std::vector<Vector *> &ye)
{
Backend::Run(dim,
q1d,
// arguments
ctx,
qfunc,
// inputs
input_idx,
input_B,
input_G,
input_vdim,
input_d1d,
input_q1d,
// outputs
output_idx,
output_B,
output_G,
output_vdim,
output_d1d,
output_q1d,
// input and output vectors
xe,
ye,
input_is_dependent,
direction_e,
// fallback arguments
dim,
q1d);
}
//////////////////////////////////////////////////////////////////
void operator()(const std::vector<Vector *> &xe,
const Vector *direction_l,
std::vector<Vector *> &ye)
{
if (ctx.attr.Size() == 0) { return; }
MFEM_ASSERT(direction_l != nullptr,
"LocalQF DerivativeAction: direction vector is null");
restriction(direction_fd,
direction_rcache,
*direction_l,
direction_e,
ElementDofOrdering::LEXICOGRAPHIC);
if (q1d <= LocalQFLOBackendMQ1())
{
run_kernels<DerivativeActionLO>(xe, ye);
}
else if (q1d <= LocalQFHOBackendMQ1())
{
run_kernels<DerivativeActionHO>(xe, ye);
}
else
{
MFEM_ABORT("Unsupported quadrature order for LocalQF backend");
}
}
//////////////////////////////////////////////////////////////////
template<typename backend_t = LocalQFLOBackend<3>, int T_Q1D = 0>
static void
derivative_action_callback(const IntegratorContext &ctx,
qfunc_t &qfunc,
// inputs: idx, B, G, vdim, d1d, q1d
const std::array<size_t, n_inputs> &in_idx,
const std::array<const real_t *, n_inputs> in_B,
const std::array<const real_t *, n_inputs> in_G,
const std::array<int, n_inputs> &in_vdim,
const std::array<int, n_inputs> &in_d1d,
const std::array<int, n_inputs> &in_q1d,
// outputs: idx, B, G, vdim, d1d, q1d
const std::array<size_t, n_outputs> &out_idx,
const std::array<const real_t *, n_outputs> out_B,
const std::array<const real_t *, n_outputs> out_G,
const std::array<int, n_outputs> &out_vdim,
const std::array<int, n_outputs> &out_d1d,
const std::array<int, n_outputs> &out_q1d,
const std::vector<Vector *> &xe,
std::vector<Vector *> &ye,
const std::array<bool, n_inputs> &input_dep,
const Vector &direction_e,
// fallback arguments
const int dim,
const int q1d)
{
MFEM_VERIFY(dim == ctx.mesh.Dimension(), "Dimension mismatch");
if (ctx.attr.Size() == 0) { return; }
static constexpr auto B2D = backend_t::DIM == 2;
static constexpr auto MQ1 = T_Q1D ? T_Q1D : backend_t::MQ1;
static constexpr auto MTPB = backend_t::MAX_THREADS_PER_BLOCK();
const int ne = ctx.nentities;
constexpr auto k_dim = [](const int k) { return k * k * (B2D ? 1 : k); };
// --------------------------------------------------
// INPUTS: XE, 3(max DIM) + 1(VDIM) + 1(number of elements)
// --------------------------------------------------
std::array<DeviceTensor<3 + 1 + 1, const real_t>, n_inputs> in_XE;
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
const size_t k = in_idx[i];
const int d = in_d1d[i], q = in_q1d[i], v = in_vdim[i];
using FOP = tuple_element_t<i, inputs_t>;
if constexpr (is_value_fop_v<FOP> || is_gradient_fop_v<FOP>)
{
MFEM_VERIFY(xe[k]->Size() == k_dim(d) * v * ne, "Size mismatch");
in_XE[i] = Reshape(xe[k]->Read(), d, d, B2D ? 1 : d, v, ne);
}
else if constexpr (is_identity_fop_v<FOP>)
{
MFEM_VERIFY(xe[k]->Size() == k_dim(q) * v * ne, "Size mismatch");
in_XE[i] = Reshape(xe[k]->Read(), v, q, q, B2D ? 1 : q, ne);
}
else if constexpr (is_weight_fop_v<FOP>)
{
MFEM_VERIFY(ctx.ir.GetNPoints() == k_dim(q1d),
"tensor-product IR expected");
in_XE[i] = Reshape(
ctx.ir.GetWeights().Read(), q1d, q1d, B2D ? 1 : q1d, 1, 1);
}
else
{
static_assert(false, "Unsupported");
}
});
const auto d_direction = direction_e.Read();
std::array<DeviceTensor<3 + 1 + 1, const real_t>, n_inputs> in_XE_dir;
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
const size_t k = in_idx[i];
const int d = in_d1d[i], q = in_q1d[i], v = in_vdim[i];
using FOP = tuple_element_t<i, inputs_t>;
if constexpr (is_value_fop_v<FOP> || is_gradient_fop_v<FOP>)
{
if (input_dep[i])
{
MFEM_ASSERT(direction_e.Size() == xe[k]->Size(),
"direction E-vector size mismatch for input " << i);
in_XE_dir[i] = Reshape(d_direction, d, d, B2D ? 1 : d, v, ne);
}
else
{
in_XE_dir[i] = in_XE[i];
}
}
else if constexpr (is_identity_fop_v<FOP>)
{
if (input_dep[i])
{
MFEM_VERIFY(direction_e.Size() == xe[k]->Size(),
"direction E-vector size mismatch (identity input) "
<< i);
in_XE_dir[i] = Reshape(d_direction, v, q, q, B2D ? 1 : q, ne);
}
else
{
in_XE_dir[i] = in_XE[i];
}
}
else if constexpr (is_weight_fop_v<FOP>) { in_XE_dir[i] = in_XE[i]; }
else
{
static_assert(false, "Unsupported");
}
});
// --------------------------------------------------
// OUTPUTS: YE, 3(max DIM) + 1(VDIM) + 1(number of elements)
// --------------------------------------------------
std::array<DeviceTensor<3 + 1 + 1, real_t>, n_outputs> out_YE;
for_constexpr<n_outputs>([&](auto ic)
{
constexpr size_t i = ic.value;
const size_t k = out_idx[i];
const int d = out_d1d[i], q = out_q1d[i], v = out_vdim[i];
using FOP = tuple_element_t<i, outputs_t>;
if constexpr (is_gradient_fop_v<FOP> || is_value_fop_v<FOP>)
{
MFEM_ASSERT(ye[k]->Size() == k_dim(d) * v * ne, "Size mismatch");
out_YE[i] = Reshape(ye[k]->ReadWrite(), d, d, B2D ? 1 : d, v, ne);
}
else if constexpr (is_identity_fop_v<FOP>)
{
MFEM_ASSERT(ye[k]->Size() == k_dim(q) * v * ne, "Size mismatch");
out_YE[i] = Reshape(ye[k]->ReadWrite(), v, q, q, B2D ? 1 : q, ne);
}
else
{
static_assert(false, "Unsupported FieldOperator");
}
});
const auto d_attr = ctx.attr.Read();
const bool has_attr = ctx.attr.Size() > 0;
const auto d_elem_attr = ctx.elem_attr->Read();
dfem::forall<MTPB>(
[=] MFEM_HOST_DEVICE(const int e, void *)
{
if (has_attr && !d_attr[d_elem_attr[e] - 1]) { return; }
// -----------------------------------------------
// Inputs and outputs argument registers
// -----------------------------------------------
args_reg_t<backend_t, qfunc_t, inputs_t, outputs_t, MQ1> rargs;
input_args_reg_t<backend_t, qfunc_t, inputs_t, outputs_t, MQ1>
sargs; // shadow
// -----------------------------------------------
// Shared memory
// -----------------------------------------------
MFEM_SHARED typename backend_t::Shared smem;
// -----------------------------------------------
// Load primal inputs (rargs)
// -----------------------------------------------
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
const auto &XE = in_XE[i];
const int d = in_d1d[i], q = in_q1d[i], Q1D = q1d;
const real_t *B = in_B[i], *G = in_G[i];
auto &rarg = get<i>(rargs);
using FOP = tuple_element_t<i, inputs_t>;
if constexpr (is_value_fop<FOP>::value)
{
backend_t::LoadValue(smem, e, d, q, Q1D, B, XE, rarg);
}
else if constexpr (is_gradient_fop_v<FOP>)
{
constexpr auto RNK = qf_param_slot<qfunc_t, i>::extents.size();
using FieldParamT =
typename qf_param_slot<qfunc_t, i>::qf_decay_param_t;
backend_t::template LoadGradient<RNK,
decltype(rarg),
decltype(XE),
FieldParamT>(
smem, e, d, q, Q1D, B, G, XE, rarg);
}
else if constexpr (is_weight_fop_v<FOP> || is_identity_fop_v<FOP>)
{
// qp values are read directly from in_XE / IR
}
else
{
static_assert(false, "Unsupported");
}
});
// -----------------------------------------------
// Load tangent directions (sargs)
// -----------------------------------------------
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
if (!input_dep[i]) { return; }
const auto &XE = in_XE_dir[i];
const int d = in_d1d[i], q = in_q1d[i], Q1D = q1d;
const real_t *B = in_B[i], *G = in_G[i];
auto &sarg = get<i>(sargs); // shadow argument register
using FOP = tuple_element_t<i, inputs_t>;
if constexpr (is_value_fop<FOP>::value)
{
backend_t::LoadValue(smem, e, d, q, Q1D, B, XE, sarg);
}
else if constexpr (is_gradient_fop_v<FOP>)
{
constexpr auto RNK = qf_param_slot<qfunc_t, i>::extents.size();
using FieldParamT =
typename qf_param_slot<qfunc_t, i>::qf_decay_param_t;
backend_t::template LoadGradient<RNK,
decltype(sarg),
decltype(XE),
FieldParamT>(
smem, e, d, q, Q1D, B, G, XE, sarg);
}
else if constexpr (is_weight_fop_v<FOP> || is_identity_fop_v<FOP>)
{
}
else
{
static_assert(false, "Unsupported");
}
});
// -----------------------------------------------
// Evaluate the quadrature function
// Warning: no 'DIRECT' on the 'Z' direction,
// as one backend may need to iterate over it.
// -----------------------------------------------
MFEM_FOREACH_THREAD(qz, z, (B2D ? 1 : q1d))
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
#ifdef MFEM_USE_ENZYME
args_tuple_t primal_args {}, shadow_args {};
// --------------------------------------
// Pulling arguments from registers to primal and shadow
// tuples
// --------------------------------------
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
auto &parg = get<i>(primal_args);
auto &targ = get<i>(shadow_args);
const auto &XE = in_XE[i];
const auto &XEd = in_XE_dir[i];
using FOP = tuple_element_t<i, inputs_t>;
using ARG =
typename qf_param_slot<qfunc_t, i>::qf_reg_param_t;
if constexpr (is_identity_fop_v<FOP>)
{
parg = as_tensor<ARG>(&XE(0, qx, qy, qz, e));
if (input_dep[i])
{
targ = as_tensor<ARG>(&XEd(0, qx, qy, qz, e));
}
else
{
targ = ARG{};
}
}
else if constexpr (is_weight_fop_v<FOP>)
{
parg = XE(qx, qy, qz, 0, 0);
targ = real_t(0.0);
}
else if constexpr (is_value_fop_v<FOP> ||
is_gradient_fop_v<FOP>)
{
parg = backend_t::template qp_pull<ARG>(
get<i>(rargs), qx, qy, qz);
if (input_dep[i])
{
targ = backend_t::template qp_pull<ARG>(
get<i>(sargs), qx, qy, qz);
}
else
{
targ = ARG{};
}
}
else
{
static_assert(false, "Unsupported");
}
});
// --------------------------------------
// Call the quadrature function
// --------------------------------------
call_enzyme_fwddiff(qfunc, primal_args, shadow_args);
// --------------------------------------
// Pushing arguments from enzyme_shadow tuple to registers
// --------------------------------------
for_constexpr<n_outputs>([&](auto ic)
{
constexpr size_t i = ic.value, o = n_inputs + i;
const auto &qout = get<o>(shadow_args);
auto &YE = out_YE[i];
using FOP = tuple_element_t<i, outputs_t>;
using ARG =
typename qf_param_slot<qfunc_t, o>::qf_reg_param_t;
if constexpr (is_identity_fop_v<FOP>)
{
as_tensor<ARG>(&YE(0, qx, qy, qz, e)) = qout;
}
else if constexpr (is_value_fop_v<FOP> ||
is_gradient_fop_v<FOP>)
{
auto &rarg = get<o>(rargs);
backend_t::template qp_push_tangent<ARG>(
rarg, qx, qy, qz, qout);
}
else
{
static_assert(false, "Unsupported");
}
});
#else // MFEM_USE_ENZYME
args_tuple_t qargs;
// --------------------------------------
// Pulling arguments from registers to qargs tuple
// --------------------------------------
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
auto &qarg = get<i>(qargs);
const auto &XE = in_XE[i];
const auto &XEd = in_XE_dir[i];
using FOP = tuple_element_t<i, inputs_t>;
using ARG =
typename qf_param_slot<qfunc_t, i>::qf_reg_param_t;
if constexpr (is_identity_fop_v<FOP>)
{
using DT =
typename qf_param_slot<qfunc_t, i>::qf_decay_param_t;
if constexpr (qf_param_uses_dual_v<DT>)
{
qarg = backend_t::template identity_qp_pull_dual<DT>(
input_dep[i], XE, XEd, qx, qy, qz, e);
}
else
{
qarg = as_tensor<ARG>(&XE(0, qx, qy, qz, e));
}
}
else if constexpr (is_weight_fop_v<FOP>)
{
qarg = XE(qx, qy, qz, 0, 0);
}
else if constexpr (is_value_fop_v<FOP> ||
is_gradient_fop_v<FOP>)
{
qarg = backend_t::template qp_pull_directional<ARG>(
get<i>(rargs),
get<i>(sargs),
qx,
qy,
qz,
input_dep[i]);
}
else
{
static_assert(false, "Unsupported");
}
});
// --------------------------------------
// Call the quadrature function
// --------------------------------------
call_qfunc_no_move(qfunc, qargs);
// --------------------------------------
// Pushing arguments from qargs tuple to registers
// --------------------------------------
for_constexpr<n_outputs>([&](auto ic)
{
constexpr size_t i = ic.value, o = n_inputs + i;
const auto &qarg = get<o>(qargs);
const auto &YE = out_YE[i];
using FOP = tuple_element_t<i, outputs_t>;
using ARG =
typename qf_param_slot<qfunc_t, o>::qf_reg_param_t;
if constexpr (is_identity_fop_v<FOP>)
{
using DT =
typename qf_param_slot<qfunc_t, o>::qf_decay_param_t;
if constexpr (qf_param_uses_dual_v<DT>)
{
backend_t::identity_qp_write_tangent(
YE, qx, qy, qz, e, qarg);
}
else
{
as_tensor<ARG>(&YE(0, qx, qy, qz, e)) = qarg;
}
}
else if constexpr (is_value_fop_v<FOP> ||
is_gradient_fop_v<FOP>)
{
auto &rarg = get<o>(rargs);
backend_t::template qp_push_tangent<ARG>(
rarg, qx, qy, qz, qarg);
}
else
{
static_assert(false, "Unsupported");
}
});
#endif // MFEM_USE_ENZYME
}
}
}
MFEM_SYNC_THREAD;
// -----------------------------------------------
// Integrate outputs
// -----------------------------------------------
for_constexpr<n_outputs>([&](auto ic)
{
constexpr size_t i = ic.value, o = n_inputs + i;
const int d = out_d1d[i], q = out_q1d[i];
const auto B = out_B[i], G = out_G[i];
auto &YE = out_YE[i];
auto &rarg = get<o>(rargs);
using FOP = tuple_element_t<i, outputs_t>;
if constexpr (is_value_fop_v<FOP>)
{
backend_t::WriteValue(smem, e, d, q, q1d, B, YE, rarg);
}
else if constexpr (is_gradient_fop_v<FOP>)
{
using YE_t = decltype(YE);
using rarg_t = decltype(rarg);
using qf_param_t =
typename qf_param_slot<qfunc_t, o>::qf_decay_param_t;
constexpr auto RNK = qf_param_slot<qfunc_t, o>::extents.size();
backend_t::template WriteGradient<RNK, rarg_t, YE_t, qf_param_t>(
smem, e, d, q, q1d, B, G, YE, rarg);
}
else if constexpr (is_identity_fop_v<FOP>)
{
// nothing to do
}
else
{
static_assert(false, "Unsupported");
}
});
},
ne,
backend_t::thread_blocks(compute_kernel_thread_1d<inputs_t, outputs_t>(
q1d, in_d1d, out_d1d)),
0,
nullptr);
}
using DerivativeKernelType =
decltype(&DerivativeAction::derivative_action_callback<>);
MFEM_REGISTER_KERNELS_HEADER_ONLY(DerivativeActionLO,
DerivativeKernelType,
(int, int) );
MFEM_REGISTER_KERNELS_HEADER_ONLY(DerivativeActionHO,
DerivativeKernelType,
(int, int) );
};
// Low Order kernels
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
template<int DIM, int Q1D>
inline typename DerivativeAction<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeKernelType
DerivativeAction<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeActionLO::Kernel()
{
static_assert((DIM == 2 || DIM == 3) && Q1D <= 8);
using derivative_action_t =
DerivativeAction<derivative_id, qfunc_t, inputs_t, outputs_t>;
return derivative_action_t::template derivative_action_callback<
LocalQFLOBackend<DIM, Q1D>>;
}
// Low Order fallback
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
inline typename DerivativeAction<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeKernelType
DerivativeAction<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeActionLO::Fallback(int dim, int q1d)
{
using derivative_action_t =
DerivativeAction<derivative_id, qfunc_t, inputs_t, outputs_t>;
using DerivativeActionLO =
typename derivative_action_t::DerivativeActionLO;
if (dim == 2)
{
return DispatchLOKernelByQ1D<DerivativeActionLO, 2>(q1d);
}
else if (dim == 3)
{
return DispatchLOKernelByQ1D<DerivativeActionLO, 3>(q1d);
}
else
{
MFEM_ABORT("Unsupported dimension");
return nullptr;
}
}
// High Order kernels
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
template<int DIM, int Q1D>
inline typename DerivativeAction<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeKernelType
DerivativeAction<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeActionHO::Kernel()
{
using derivative_action_t =
DerivativeAction<derivative_id, qfunc_t, inputs_t, outputs_t>;
return derivative_action_t::
template derivative_action_callback<LocalQFHOBackend<DIM>, Q1D>;
}
// High Order fallback
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
inline typename DerivativeAction<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeKernelType
DerivativeAction<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeActionHO::Fallback(int dim, int q1d)
{
using derivative_action_t =
DerivativeAction<derivative_id, qfunc_t, inputs_t, outputs_t>;
using DerivativeActionHO = typename derivative_action_t::DerivativeActionHO;
if (dim == 2)
{
return DispatchHOKernelByQ1D<DerivativeActionHO, 2>(q1d);
}
else if (dim == 3)
{
return DispatchHOKernelByQ1D<DerivativeActionHO, 3>(q1d);
}
else
{
MFEM_ABORT("Unsupported dimension");
return nullptr;
}
}
} // namespace mfem::future::LocalQFImpl
@@ -0,0 +1,738 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../../integrator_ctx.hpp"
#include "kernels.hpp"
#include "util.hpp"
#include <array>
namespace mfem::future::LocalQFImpl
{
// Cached Jacobian apply: J·v from qp_cache filled by DerivativeSetup
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
class DerivativeApply
{
static constexpr auto inout_tuple =
merge_mfem_tuples_as_empty_std_tuple(inputs_t {}, outputs_t{});
static constexpr auto filtered_inout_tuple = filter_fields(inout_tuple);
static constexpr size_t nfields =
count_unique_field_ids(filtered_inout_tuple);
using qf_signature = typename get_function_signature<qfunc_t>::type;
using qf_param_ts = typename qf_signature::parameter_ts;
using args_tuple_t = decay_tuple<qf_param_ts>;
static constexpr std::size_t n_inputs = tuple_size<inputs_t>::value;
static constexpr std::size_t n_outputs = tuple_size<outputs_t>::value;
static_assert(n_inputs + n_outputs == tuple_size<qf_param_ts>::value,
"LocalQF: q-function arity must match inputs + outputs");
const inputs_t inputs;
const outputs_t outputs;
const IntegratorContext ctx;
const Vector &qp_cache;
const std::vector<const DofToQuad *> dtqs;
// inputs: dtq, idx, B, G, d1d, q1d, vdim
const std::array<DofToQuadMap, n_inputs> input_dtq;
const std::array<size_t, n_inputs> input_idx;
const std::array<const real_t *, n_inputs> input_B, input_G;
const std::array<int, n_inputs> input_d1d, input_q1d, input_vdim;
// outputs: dtq, idx, B, G, d1d, q1d, vdim
const std::array<DofToQuadMap, n_outputs> output_dtq;
const std::array<size_t, n_outputs> output_idx;
const std::array<const real_t *, n_outputs> output_B, output_G;
const std::array<int, n_outputs> output_d1d, output_q1d, output_vdim;
// Jacobian cache metadata
const std::array<bool, n_inputs> input_is_dependent;
const std::array<int, n_inputs> input_size_on_qp;
const std::array<int, n_outputs> out_op_dim;
const std::array<int, n_outputs> out_offsets;
const int output_size_on_qp;
const int trial_vdim;
const int total_trial_op_dim;
const int residual_size_on_qp;
// other constants
const int dim, ne, nq, q1d;
FieldDescriptor direction_fd;
mutable Vector direction_e;
mutable RestrictionCache<Entity::Element> direction_rcache;
template <std::size_t slot>
static constexpr int ParamRank()
{
using param_t = typename qf_param_slot<qfunc_t, slot>::qf_decay_param_t;
return qf_param_shape<param_t>::rank;
}
template <std::size_t slot, int dim_idx>
static constexpr int ParamExtent()
{
using param_t = typename qf_param_slot<qfunc_t, slot>::qf_decay_param_t;
return qf_param_shape<param_t>::extents[dim_idx];
}
template <typename fop_t, std::size_t slot>
static constexpr int StaticVDim()
{
constexpr int rank = ParamRank<slot>();
if constexpr (is_gradient_fop_v<fop_t>)
{
if constexpr (rank <= 1) { return 1; }
else { return ParamExtent<slot, 0>(); }
}
else
{
if constexpr (rank == 0) { return 1; }
else { return ParamExtent<slot, 0>(); }
}
}
template <typename fop_t, std::size_t slot>
static constexpr int StaticOpDim()
{
constexpr int rank = ParamRank<slot>();
if constexpr (is_gradient_fop_v<fop_t>)
{
if constexpr (rank == 0) { return 1; }
else if constexpr (rank == 1) { return ParamExtent<slot, 0>(); }
else { return ParamExtent<slot, 1>(); }
}
else
{
if constexpr (rank <= 1) { return 1; }
else { return ParamExtent<slot, 1>(); }
}
}
template <std::size_t input_slot>
static constexpr bool StaticInputDep()
{
using fop_t = tuple_element_t<input_slot, inputs_t>;
return fop_t::GetFieldId() == derivative_id;
}
template <std::size_t input_slot>
static constexpr int StaticInputVDim()
{
using fop_t = tuple_element_t<input_slot, inputs_t>;
return StaticVDim<fop_t, input_slot>();
}
template <std::size_t input_slot>
static constexpr int StaticInputOpDim()
{
using fop_t = tuple_element_t<input_slot, inputs_t>;
return StaticOpDim<fop_t, input_slot>();
}
template <std::size_t output_slot>
static constexpr int StaticOutputVDim()
{
using fop_t = tuple_element_t<output_slot, outputs_t>;
return StaticVDim<fop_t, n_inputs + output_slot>();
}
template <std::size_t output_slot>
static constexpr int StaticOutputOpDim()
{
using fop_t = tuple_element_t<output_slot, outputs_t>;
return StaticOpDim<fop_t, n_inputs + output_slot>();
}
template <std::size_t output_slot>
static constexpr int StaticOutputOffset()
{
int offset = 0;
for_constexpr<output_slot>([&](auto oc)
{
constexpr size_t o = oc.value;
offset += StaticOutputVDim<o>() * StaticOutputOpDim<o>();
});
return offset;
}
template <std::size_t input_slot>
static constexpr int StaticInputOpOffset()
{
int offset = 0;
for_constexpr<input_slot>([&](auto sc)
{
constexpr size_t s = sc.value;
if constexpr (StaticInputDep<s>()) { offset += StaticInputOpDim<s>(); }
});
return offset;
}
static constexpr int StaticTrialVDim()
{
int vdim = 1;
for_constexpr<n_inputs>([&](auto sc)
{
constexpr size_t s = sc.value;
if constexpr (StaticInputDep<s>()) { vdim = StaticInputVDim<s>(); }
});
return vdim;
}
static constexpr int StaticTotalTrialOpDim()
{
int op_dim = 0;
for_constexpr<n_inputs>([&](auto sc)
{
constexpr size_t s = sc.value;
if constexpr (StaticInputDep<s>()) { op_dim += StaticInputOpDim<s>(); }
});
return op_dim;
}
public:
DerivativeApply() = delete;
DerivativeApply(IntegratorContext ctx,
qfunc_t /*qfunc*/,
inputs_t inputs,
outputs_t outputs,
const Vector &qp_cache_in):
inputs(inputs), outputs(outputs), ctx(ctx), qp_cache(qp_cache_in),
dtqs(make_dtqs(ctx)), input_dtq(create_dtq_maps<Entity::Element>(
inputs,
dtqs,
create_union_field_map_for_dtq(ctx, inputs),
ctx.unionfds,
ctx.ir)),
input_idx(create_input_vector_map(ctx, inputs)),
input_B(get_B(input_dtq)), input_G(get_G(input_dtq)),
input_d1d(get_D1D(input_dtq)), input_q1d(get_Q1D(input_dtq)),
input_vdim(get_vdim(inputs)),
output_dtq(create_dtq_maps<Entity::Element>(
outputs,
dtqs,
create_union_field_map_for_dtq(ctx, outputs),
ctx.unionfds,
ctx.ir)),
output_idx(create_output_vector_map(ctx, outputs)),
output_B(get_B(output_dtq)), output_G(get_G(output_dtq)),
output_d1d(get_D1D(output_dtq)), output_q1d(get_Q1D(output_dtq)),
output_vdim(get_vdim(outputs)),
input_is_dependent(compute_input_is_dependent(inputs, derivative_id)),
input_size_on_qp(
get_input_size_on_qp(inputs, std::make_index_sequence<n_inputs> {})),
out_op_dim(compute_out_op_dim(outputs)),
out_offsets(compute_out_offsets(output_vdim, out_op_dim)),
output_size_on_qp(
[&]
{
int s = 0;
for_constexpr<n_outputs>([&](auto o)
{ s += get<o>(outputs).size_on_qp; });
return s;
}()),
trial_vdim(compute_trial_vdim(inputs, derivative_id)),
total_trial_op_dim(compute_total_trial_op_dim(
inputs, input_is_dependent, input_size_on_qp)),
residual_size_on_qp(output_size_on_qp * trial_vdim * total_trial_op_dim),
dim(ctx.mesh.Dimension()), ne(ctx.nentities), nq(ctx.ir.GetNPoints()),
q1d(tensor_1d_size(nq, dim))
{
MFEM_ASSERT(ctx.unionfds.size() == nfields,
"LocalQFBackend: unionfds size mismatch");
int direction_field_idx = -1;
for (size_t uf = 0; uf < nfields; uf++)
{
if (static_cast<int>(ctx.unionfds[uf].id) == derivative_id)
{
direction_field_idx = static_cast<int>(uf);
break;
}
}
MFEM_ASSERT(direction_field_idx != -1,
"DerivativeApply: derivative direction field not found");
direction_fd = ctx.unionfds[static_cast<size_t>(direction_field_idx)];
}
//////////////////////////////////////////////////////////////////
template<typename Backend>
void run_kernels(std::vector<Vector *> &ye) const
{
Backend::Run(dim,
q1d,
ctx,
qp_cache,
// inputs
input_idx,
input_B,
input_G,
input_vdim,
input_d1d,
input_q1d,
input_size_on_qp,
input_is_dependent,
// outputs
output_idx,
output_B,
output_G,
output_vdim,
output_d1d,
output_q1d,
out_op_dim,
out_offsets,
trial_vdim,
total_trial_op_dim,
residual_size_on_qp,
output_size_on_qp,
direction_e,
ye,
// fallback arguments
dim,
q1d);
}
//////////////////////////////////////////////////////////////////
void operator()(const std::vector<Vector *> &,
const Vector *direction_l,
std::vector<Vector *> &ye) const
{
if (ctx.attr.Size() == 0) { return; }
MFEM_ASSERT(direction_l != nullptr,
"LocalQF DerivativeApply: direction vector is null");
restriction(direction_fd,
direction_rcache,
*direction_l,
direction_e,
ElementDofOrdering::LEXICOGRAPHIC);
if (q1d <= LocalQFLOBackendMQ1())
{
run_kernels<DerivativeApplyLO>(ye);
}
else if (q1d <= LocalQFHOBackendMQ1())
{
run_kernels<DerivativeApplyHO>(ye);
}
else
{
MFEM_ABORT("Unsupported quadrature order for LocalQF backend");
}
}
//////////////////////////////////////////////////////////////////
template<typename backend_t = LocalQFLOBackend<3>, int T_Q1D = 0>
static void
derivative_apply_callback(const IntegratorContext &ctx,
const Vector &qp_cache,
// inputs: idx, B, G, vdim, d1d, q1d
const std::array<size_t, n_inputs> & /*in_idx*/,
const std::array<const real_t *, n_inputs> in_B,
const std::array<const real_t *, n_inputs> in_G,
const std::array<int, n_inputs> &in_vdim,
const std::array<int, n_inputs> &in_d1d,
const std::array<int, n_inputs> &in_q1d,
const std::array<int, n_inputs> &in_size_on_qp,
const std::array<bool, n_inputs> &input_dep,
// outputs: idx, B, G, vdim, d1d, q1d
const std::array<size_t, n_outputs> &out_idx,
const std::array<const real_t *, n_outputs> out_B,
const std::array<const real_t *, n_outputs> out_G,
const std::array<int, n_outputs> &out_vdim,
const std::array<int, n_outputs> &out_d1d,
const std::array<int, n_outputs> &out_q1d,
const std::array<int, n_outputs> &out_op_dim,
const std::array<int, n_outputs> &out_offsets,
const int trial_vdim,
const int total_trial_op_dim,
const int residual_size_on_qp,
const int output_size_on_qp,
const Vector &direction_e,
std::vector<Vector *> &ye,
// fallback arguments
const int dim,
const int q1d)
{
MFEM_CONTRACT_VAR(input_dep);
MFEM_CONTRACT_VAR(in_size_on_qp);
MFEM_CONTRACT_VAR(out_vdim);
MFEM_CONTRACT_VAR(out_op_dim);
MFEM_CONTRACT_VAR(out_offsets);
MFEM_CONTRACT_VAR(trial_vdim);
MFEM_CONTRACT_VAR(total_trial_op_dim);
MFEM_VERIFY(dim == ctx.mesh.Dimension(), "Dimension mismatch");
if (ctx.attr.Size() == 0) { return; }
static constexpr auto B2D = backend_t::DIM == 2;
static constexpr auto MQ1 = T_Q1D ? T_Q1D : backend_t::MQ1;
static constexpr auto MTPB = backend_t::MAX_THREADS_PER_BLOCK();
const int ne = ctx.nentities;
const int nq = ctx.ir.GetNPoints();
MFEM_CONTRACT_VAR(output_size_on_qp);
constexpr auto k_dim = [](const int k) { return k * k * (B2D ? 1 : k); };
// --------------------------------------------------
// DIRECTION (trial): XE_dir for the dependent inputs
// --------------------------------------------------
const auto d_direction = direction_e.Read();
std::array<DeviceTensor<3 + 1 + 1, const real_t>, n_inputs> in_XE_dir;
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
const int d = in_d1d[i], q = in_q1d[i], v = in_vdim[i];
using FOP = tuple_element_t<i, inputs_t>;
if (!input_dep[i]) { return; }
if constexpr (is_value_fop_v<FOP> || is_gradient_fop_v<FOP>)
{
in_XE_dir[i] = Reshape(d_direction, d, d, B2D ? 1 : d, v, ne);
}
else if constexpr (is_identity_fop_v<FOP>)
{
in_XE_dir[i] = Reshape(d_direction, v, q, q, B2D ? 1 : q, ne);
}
else if constexpr (is_weight_fop_v<FOP>) { /* never a direction */ }
else
{
static_assert(false, "Unsupported");
}
});
// --------------------------------------------------
// OUTPUTS: YE, 3(max DIM) + 1(VDIM) + 1(number of elements)
// --------------------------------------------------
std::array<DeviceTensor<3 + 1 + 1, real_t>, n_outputs> out_YE;
for_constexpr<n_outputs>([&](auto ic)
{
constexpr size_t i = ic.value;
const size_t k = out_idx[i];
const int d = out_d1d[i], q = out_q1d[i], v = out_vdim[i];
using FOP = tuple_element_t<i, outputs_t>;
if constexpr (is_gradient_fop_v<FOP> || is_value_fop_v<FOP>)
{
MFEM_VERIFY(ye[k]->Size() == k_dim(d) * v * ne, "Size mismatch");
out_YE[i] = Reshape(ye[k]->ReadWrite(), d, d, B2D ? 1 : d, v, ne);
}
else if constexpr (is_identity_fop_v<FOP>)
{
MFEM_VERIFY(ye[k]->Size() == k_dim(q) * v * ne, "Size mismatch");
out_YE[i] = Reshape(ye[k]->ReadWrite(), v, q, q, B2D ? 1 : q, ne);
}
else
{
static_assert(false, "Unsupported FieldOperator");
}
});
auto cache_tensor = DeviceTensor<3, const real_t>(
qp_cache.Read(), nq, residual_size_on_qp, ne);
const auto d_attr = ctx.attr.Read();
const bool has_attr = ctx.attr.Size() > 0;
const auto d_elem_attr = ctx.elem_attr->Read();
dfem::forall<MTPB>(
[=] MFEM_HOST_DEVICE(const int e, void *)
{
if (has_attr && !d_attr[d_elem_attr[e] - 1]) { return; }
// -----------------------------------------------
// Output integration registers, trial direction (shadow) registers
// and shared memory. `rargs` only ever holds test-function data, so
// it is an output-only bank: slot `o` is q-function parameter
// `n_inputs + o`.
// -----------------------------------------------
output_args_reg_t<backend_t, qfunc_t, inputs_t, outputs_t, MQ1> rargs;
input_args_reg_t<backend_t, qfunc_t, inputs_t, outputs_t, MQ1> sargs;
MFEM_SHARED typename backend_t::Shared smem;
// -----------------------------------------------
// Load trial direction (sargs) for the dependent inputs
// -----------------------------------------------
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
if constexpr (!StaticInputDep<i>()) { return; }
const auto &XE = in_XE_dir[i];
const int d = in_d1d[i], q = in_q1d[i], Q1D = q1d;
const real_t *B = in_B[i], *G = in_G[i];
auto &sarg = get<i>(sargs);
using FOP = tuple_element_t<i, inputs_t>;
if constexpr (is_value_fop<FOP>::value)
{
backend_t::LoadValue(smem, e, d, q, Q1D, B, XE, sarg);
}
else if constexpr (is_gradient_fop_v<FOP>)
{
constexpr auto RNK = qf_param_slot<qfunc_t, i>::extents.size();
using FieldParamT =
typename qf_param_slot<qfunc_t, i>::qf_decay_param_t;
backend_t::template LoadGradient<RNK,
decltype(sarg),
decltype(XE),
FieldParamT>(
smem, e, d, q, Q1D, B, G, XE, sarg);
}
else if constexpr (is_identity_fop_v<FOP> || is_weight_fop_v<FOP>)
{
// identity read at qp; weight is never a trial direction
}
else
{
static_assert(false, "Unsupported");
}
});
MFEM_SYNC_THREAD;
// -----------------------------------------------
// Contract the cached Jacobian with the trial direction at each
// quadrature point and push the result into the test registers.
// -----------------------------------------------
MFEM_FOREACH_THREAD(qz, z, (B2D ? 1 : q1d))
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
const int q = qx + q1d * (qy + q1d * qz);
// The trial direction at this quadrature point is the same
// for every test row (i, k), so pull each dependent input
// slot out of the register bank once, here, instead of once
// per row inside the contraction below.
args_tuple_t dvecs {};
for_constexpr<n_inputs>([&](auto sc)
{
constexpr size_t s = sc.value;
if constexpr (StaticInputDep<s>())
{
using SARG =
typename qf_param_slot<qfunc_t, s>::qf_reg_param_t;
get<s>(dvecs) = backend_t::template qp_pull<SARG>(
get<s>(sargs), qx, qy, qz);
}
});
for_constexpr<n_outputs>([&](auto oc)
{
constexpr size_t o = oc.value, ao = n_inputs + o;
using FOP = tuple_element_t<o, outputs_t>;
using ARG =
typename qf_param_slot<qfunc_t, ao>::qf_reg_param_t;
constexpr int tv = StaticOutputVDim<o>();
constexpr int to = StaticOutputOpDim<o>();
constexpr int offset_o = StaticOutputOffset<o>();
constexpr int trial_vdim_ct = StaticTrialVDim();
constexpr int total_trial_op_dim_ct = StaticTotalTrialOpDim();
ARG fhat{};
MFEM_UNROLL(tv)
for (int i = 0; i < tv; i++)
{
MFEM_UNROLL(to)
for (int k = 0; k < to; k++)
{
const int row = offset_o + i * to + k;
const int cache_row =
row * trial_vdim_ct * total_trial_op_dim_ct;
real_t sum = 0.0;
for_constexpr<n_inputs>([&](auto sc)
{
constexpr size_t s = sc.value;
if constexpr (StaticInputDep<s>())
{
constexpr int op_dim_s = StaticInputOpDim<s>();
constexpr int m_offset = StaticInputOpOffset<s>();
const auto &dvec = get<s>(dvecs);
MFEM_UNROLL(trial_vdim_ct)
for (int j = 0; j < trial_vdim_ct; j++)
{
MFEM_UNROLL(op_dim_s)
for (int m = 0; m < op_dim_s; m++)
{
const int cache_idx =
cache_row + j * total_trial_op_dim_ct +
(m + m_offset);
sum += cache_tensor(q, cache_idx, e) *
qf_value_at(dvec, j, m);
}
}
}
});
qf_set_value_at(fhat, i, k, sum);
}
}
auto &YE = out_YE[o];
if constexpr (is_identity_fop_v<FOP>)
{
MFEM_UNROLL(tv)
for (int i = 0; i < tv; i++)
{
MFEM_UNROLL(to)
for (int k = 0; k < to; k++)
{
YE(i + tv * k, qx, qy, qz, e) =
qf_value_at(fhat, i, k);
}
}
}
else
{
backend_t::template qp_push<ARG>(
get<o>(rargs), qx, qy, qz, fhat);
}
});
}
}
}
MFEM_SYNC_THREAD;
// -----------------------------------------------
// Integrate value / gradient outputs to the test dofs
// -----------------------------------------------
for_constexpr<n_outputs>([&](auto ic)
{
constexpr size_t i = ic.value, o = n_inputs + i;
const int d = out_d1d[i], q = out_q1d[i], Q1D = q1d;
const auto B = out_B[i], G = out_G[i];
auto &YE = out_YE[i];
auto &rarg = get<i>(rargs);
using FOP = tuple_element_t<i, outputs_t>;
if constexpr (is_value_fop_v<FOP>)
{
backend_t::WriteValue(smem, e, d, q, Q1D, B, YE, rarg);
}
else if constexpr (is_gradient_fop_v<FOP>)
{
using YE_t = decltype(YE);
using rarg_t = decltype(rarg);
using qf_param_t =
typename qf_param_slot<qfunc_t, o>::qf_decay_param_t;
constexpr auto RNK = qf_param_slot<qfunc_t, o>::extents.size();
backend_t::template WriteGradient<RNK, rarg_t, YE_t, qf_param_t>(
smem, e, d, q, Q1D, B, G, YE, rarg);
}
else if constexpr (is_identity_fop_v<FOP>) { /* written at qp */ }
else
{
static_assert(false, "Unsupported");
}
});
},
ne,
backend_t::thread_blocks(compute_kernel_thread_1d<inputs_t, outputs_t>(
q1d, in_d1d, out_d1d)),
0,
nullptr);
}
using ApplyKernelType =
decltype(&DerivativeApply::derivative_apply_callback<>);
MFEM_REGISTER_KERNELS_HEADER_ONLY(DerivativeApplyLO,
ApplyKernelType,
(int, int) );
MFEM_REGISTER_KERNELS_HEADER_ONLY(DerivativeApplyHO,
ApplyKernelType,
(int, int) );
};
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
template<int DIM, int Q1D>
inline typename DerivativeApply<derivative_id, qfunc_t, inputs_t, outputs_t>::
ApplyKernelType
DerivativeApply<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeApplyLO::Kernel()
{
static_assert((DIM == 2 || DIM == 3) && Q1D <= 8);
using apply_t = DerivativeApply<derivative_id, qfunc_t, inputs_t, outputs_t>;
return apply_t::template derivative_apply_callback<
LocalQFLOBackend<DIM, Q1D>>;
}
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
inline typename DerivativeApply<derivative_id, qfunc_t, inputs_t, outputs_t>::
ApplyKernelType
DerivativeApply<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeApplyLO::Fallback(int dim, int q1d)
{
using apply_t = DerivativeApply<derivative_id, qfunc_t, inputs_t, outputs_t>;
using DerivativeApplyLO = typename apply_t::DerivativeApplyLO;
if (dim == 2)
{
return DispatchLOKernelByQ1D<DerivativeApplyLO, 2>(q1d);
}
else if (dim == 3)
{
return DispatchLOKernelByQ1D<DerivativeApplyLO, 3>(q1d);
}
else
{
MFEM_ABORT("Unsupported dimension");
return nullptr;
}
}
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
template<int DIM, int Q1D>
inline typename DerivativeApply<derivative_id, qfunc_t, inputs_t, outputs_t>::
ApplyKernelType
DerivativeApply<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeApplyHO::Kernel()
{
using apply_t = DerivativeApply<derivative_id, qfunc_t, inputs_t, outputs_t>;
return apply_t::template derivative_apply_callback<LocalQFHOBackend<DIM>,
Q1D>;
}
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
inline typename DerivativeApply<derivative_id, qfunc_t, inputs_t, outputs_t>::
ApplyKernelType
DerivativeApply<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeApplyHO::Fallback(int dim, int q1d)
{
using apply_t = DerivativeApply<derivative_id, qfunc_t, inputs_t, outputs_t>;
using DerivativeApplyHO = typename apply_t::DerivativeApplyHO;
if (dim == 2)
{
return DispatchHOKernelByQ1D<DerivativeApplyHO, 2>(q1d);
}
else if (dim == 3)
{
return DispatchHOKernelByQ1D<DerivativeApplyHO, 3>(q1d);
}
else
{
MFEM_ABORT("Unsupported dimension");
return nullptr;
}
}
} // namespace mfem::future::LocalQFImpl
@@ -0,0 +1,637 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../../integrator_ctx.hpp"
#include "kernels.hpp"
#include "util.hpp"
#include <array>
namespace mfem::future::LocalQFImpl
{
// Cached transposed Jacobian apply: Jᵀ·w from the qp_cache
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
class DerivativeApplyTranspose
{
static constexpr auto inout_tuple =
merge_mfem_tuples_as_empty_std_tuple(inputs_t {}, outputs_t{});
static constexpr auto filtered_inout_tuple = filter_fields(inout_tuple);
static constexpr size_t nfields =
count_unique_field_ids(filtered_inout_tuple);
using qf_signature = typename get_function_signature<qfunc_t>::type;
using qf_param_ts = typename qf_signature::parameter_ts;
using args_tuple_t = decay_tuple<qf_param_ts>;
static constexpr std::size_t n_inputs = tuple_size<inputs_t>::value;
static constexpr std::size_t n_outputs = tuple_size<outputs_t>::value;
static_assert(n_inputs + n_outputs == tuple_size<qf_param_ts>::value,
"LocalQF: q-function arity must match inputs + outputs");
// Input tuple slot referencing the derivative field (compile-time)
static constexpr size_t deriv_input_idx_ct = []() constexpr
{
size_t idx = SIZE_MAX;
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
using FOP = tuple_element_t<i, inputs_t>;
if (FOP::GetFieldId() == derivative_id) { idx = i; }
});
return idx;
}();
static_assert(deriv_input_idx_ct < n_inputs,
"DerivativeApplyTranspose: derivative input slot not found");
const inputs_t inputs;
const outputs_t outputs;
const IntegratorContext ctx;
const Vector &qp_cache; // Jacobian cache from DerivativeSetup
const std::vector<const DofToQuad *> dtqs;
// inputs: dtq, B, G, d1d, q1d, vdim (trial / derivative fields)
const std::array<DofToQuadMap, n_inputs> input_dtq;
const std::array<const real_t *, n_inputs> input_B, input_G;
const std::array<int, n_inputs> input_d1d, input_q1d, input_vdim;
// outputs: dtq, idx, B, G, d1d, q1d, vdim (test / cotangent fields)
const std::array<DofToQuadMap, n_outputs> output_dtq;
const std::array<size_t, n_outputs> output_idx;
const std::array<const real_t *, n_outputs> output_B, output_G;
const std::array<int, n_outputs> output_d1d, output_q1d, output_vdim;
// Jacobian cache metadata
const std::array<bool, n_inputs> input_is_dependent;
const std::array<int, n_inputs> input_size_on_qp;
const std::array<int, n_outputs> out_op_dim;
const std::array<int, n_outputs> out_offsets;
const int output_size_on_qp;
const int trial_vdim;
const int total_trial_op_dim;
const int residual_size_on_qp;
// other constants
const int dim, ne, nq, q1d;
const size_t deriv_infd_idx; // index of the derivative field in ye
// output cotangent restriction workspace (blocked by element)
std::array<int, n_outputs> out_elem_dof_size;
mutable Vector dir_out_e;
/// One restriction cache per output field, resolved on first use.
mutable std::array<RestrictionCache<Entity::Element>, n_outputs>
out_rcaches;
public:
//////////////////////////////////////////////////////////////////
DerivativeApplyTranspose() = delete;
DerivativeApplyTranspose(IntegratorContext ctx,
qfunc_t /*qfunc*/,
inputs_t inputs,
outputs_t outputs,
const Vector &qp_cache):
inputs(inputs), outputs(outputs), ctx(ctx), qp_cache(qp_cache),
dtqs(make_dtqs(ctx)), input_dtq(create_dtq_maps<Entity::Element>(
inputs,
dtqs,
create_union_field_map_for_dtq(ctx, inputs),
ctx.unionfds,
ctx.ir)),
input_B(get_B(input_dtq)), input_G(get_G(input_dtq)),
input_d1d(get_D1D(input_dtq)), input_q1d(get_Q1D(input_dtq)),
input_vdim(get_vdim(inputs)),
output_dtq(create_dtq_maps<Entity::Element>(
outputs,
dtqs,
create_union_field_map_for_dtq(ctx, outputs),
ctx.unionfds,
ctx.ir)),
output_idx(create_output_vector_map(ctx, outputs)),
output_B(get_B(output_dtq)), output_G(get_G(output_dtq)),
output_d1d(get_D1D(output_dtq)), output_q1d(get_Q1D(output_dtq)),
output_vdim(get_vdim(outputs)),
input_is_dependent(compute_input_is_dependent(inputs, derivative_id)),
input_size_on_qp(
get_input_size_on_qp(inputs, std::make_index_sequence<n_inputs> {})),
out_op_dim(compute_out_op_dim(outputs)),
out_offsets(compute_out_offsets(output_vdim, out_op_dim)),
output_size_on_qp(
[&]
{
int s = 0;
for_constexpr<n_outputs>([&](auto o)
{ s += get<o>(outputs).size_on_qp; });
return s;
}()),
trial_vdim(compute_trial_vdim(inputs, derivative_id)),
total_trial_op_dim(compute_total_trial_op_dim(
inputs, input_is_dependent, input_size_on_qp)),
residual_size_on_qp(output_size_on_qp * trial_vdim * total_trial_op_dim),
dim(ctx.mesh.Dimension()), ne(ctx.nentities), nq(ctx.ir.GetNPoints()),
q1d(tensor_1d_size(nq, dim)),
deriv_infd_idx(find_infd_index(ctx, derivative_id)), out_elem_dof_size{}
{
MFEM_ASSERT(ctx.unionfds.size() == nfields,
"LocalQFBackend: unionfds size mismatch");
MFEM_ASSERT(
deriv_infd_idx != SIZE_MAX,
"DerivativeApplyTranspose: derivative field not found in infds");
// Size the workspace that holds the output cotangent(s) in element
// layout.
int total_dir_e_size = 0;
for_constexpr<n_outputs>([&](auto o)
{
const int elem_sz = compute_element_dof_sz(
ctx.outfds[output_idx[o]], ne, ElementDofOrdering::LEXICOGRAPHIC);
out_elem_dof_size[o] = elem_sz;
total_dir_e_size += elem_sz;
});
dir_out_e.SetSize(total_dir_e_size * ne);
dir_out_e.UseDevice(true);
dir_out_e.Read();
}
//////////////////////////////////////////////////////////////////
template<typename Backend>
void run_kernels(std::vector<Vector *> &ye) const
{
Backend::Run(dim,
q1d,
ctx,
qp_cache,
dir_out_e,
// inputs (integration target metadata)
input_B,
input_G,
input_vdim,
input_d1d,
input_q1d,
input_size_on_qp,
input_is_dependent,
// outputs (direction interpolation metadata)
output_B,
output_G,
output_vdim,
output_d1d,
output_q1d,
out_op_dim,
out_offsets,
trial_vdim,
total_trial_op_dim,
residual_size_on_qp,
output_size_on_qp,
deriv_infd_idx,
ye,
// fallback arguments
dim,
q1d);
}
//////////////////////////////////////////////////////////////////
void operator()(const std::vector<Vector *> & /*xe*/,
const Vector *direction_l,
std::vector<Vector *> &ye) const
{
if (ctx.attr.Size() == 0) { return; }
MFEM_ASSERT(direction_l != nullptr,
"LocalQF DerivativeApplyTranspose: direction vector is null");
// Restrict output cotangent from L-vectors into element layout
// (dir_out_e).
int l_offset = 0;
int e_offset = 0;
for_constexpr<n_outputs>([&](auto o)
{
const size_t outfd = output_idx[o];
const auto &fd = ctx.outfds[outfd];
const int l_size = GetVSize(fd);
Vector dir_o_l(*const_cast<Vector *>(direction_l), l_offset, l_size);
dir_o_l.UseDevice(true);
const int elem_sz = out_elem_dof_size[o];
Vector dir_o_e(dir_out_e, e_offset, elem_sz * ne);
dir_o_e.UseDevice(true);
restriction(fd, out_rcaches[o], dir_o_l, dir_o_e,
ElementDofOrdering::LEXICOGRAPHIC);
l_offset += l_size;
e_offset += elem_sz * ne;
});
if (q1d <= LocalQFLOBackendMQ1())
{
run_kernels<DerivativeApplyTransposeLO>(ye);
}
else if (q1d <= LocalQFHOBackendMQ1())
{
run_kernels<DerivativeApplyTransposeHO>(ye);
}
else
{
MFEM_ABORT("Unsupported quadrature order for LocalQF backend");
}
}
//////////////////////////////////////////////////////////////////
template<typename backend_t = LocalQFLOBackend<3>, int T_Q1D = 0>
static void derivative_apply_transpose_callback(
const IntegratorContext &ctx,
const Vector &qp_cache,
const Vector &dir_e, // restricted, concatenated output cotangents
// inputs (integration target metadata)
const std::array<const real_t *, n_inputs> in_B,
const std::array<const real_t *, n_inputs> in_G,
const std::array<int, n_inputs> &in_vdim,
const std::array<int, n_inputs> &in_d1d,
const std::array<int, n_inputs> &in_q1d,
const std::array<int, n_inputs> &in_size_on_qp,
const std::array<bool, n_inputs> &input_dep,
// outputs (direction interpolation metadata)
const std::array<const real_t *, n_outputs> out_B,
const std::array<const real_t *, n_outputs> out_G,
const std::array<int, n_outputs> &out_vdim,
const std::array<int, n_outputs> &out_d1d,
const std::array<int, n_outputs> &out_q1d,
const std::array<int, n_outputs> &out_op_dim,
const std::array<int, n_outputs> &out_offsets,
const int trial_vdim,
const int total_trial_op_dim,
const int residual_size_on_qp,
const int output_size_on_qp,
const size_t deriv_infd_idx,
std::vector<Vector *> &ye,
// fallback arguments
const int dim,
const int q1d)
{
MFEM_VERIFY(dim == ctx.mesh.Dimension(), "Dimension mismatch");
if (ctx.attr.Size() == 0) { return; }
static constexpr auto B2D = backend_t::DIM == 2;
static constexpr auto MQ1 = T_Q1D ? T_Q1D : backend_t::MQ1;
static constexpr auto MTPB = backend_t::MAX_THREADS_PER_BLOCK();
const int ne = ctx.nentities;
const int nq = ctx.ir.GetNPoints();
MFEM_CONTRACT_VAR(output_size_on_qp);
MFEM_CONTRACT_VAR(in_q1d);
constexpr auto k_dim = [](const int k) { return k * k * (B2D ? 1 : k); };
// --------------------------------------------------
// DIRECTION (test cotangent): out_XE_dir, concatenated per output
// --------------------------------------------------
const auto d_dir = dir_e.Read();
std::array<DeviceTensor<3 + 1 + 1, const real_t>, n_outputs> out_XE_dir;
int e_offset = 0;
for_constexpr<n_outputs>([&](auto oc)
{
constexpr size_t o = oc.value;
const int d = out_d1d[o], q = out_q1d[o], v = out_vdim[o];
using FOP = tuple_element_t<o, outputs_t>;
if constexpr (is_value_fop_v<FOP> || is_gradient_fop_v<FOP>)
{
out_XE_dir[o] = Reshape(d_dir + e_offset, d, d, B2D ? 1 : d, v, ne);
e_offset += k_dim(d) * v * ne;
}
else if constexpr (is_identity_fop_v<FOP>)
{
out_XE_dir[o] = Reshape(d_dir + e_offset, v, q, q, B2D ? 1 : q, ne);
e_offset += k_dim(q) * v * ne;
}
else
{
static_assert(false, "Unsupported");
}
});
// --------------------------------------------------
// DERIVATIVE TRIAL FIELD: ye_XE (accumulates Jᵀ w)
// --------------------------------------------------
const int d_in = in_d1d[deriv_input_idx_ct];
const int v_in = in_vdim[deriv_input_idx_ct];
auto ye_XE = Reshape(
ye[deriv_infd_idx]->ReadWrite(), d_in, d_in, B2D ? 1 : d_in, v_in, ne);
auto cache_tensor = DeviceTensor<3, const real_t>(
qp_cache.Read(), nq, residual_size_on_qp, ne);
const auto d_attr = ctx.attr.Read();
const bool has_attr = ctx.attr.Size() > 0;
const auto d_elem_attr = ctx.elem_attr->Read();
dfem::forall<MTPB>(
[=] MFEM_HOST_DEVICE(const int e, void *)
{
if (has_attr && !d_attr[d_elem_attr[e] - 1]) { return; }
// -----------------------------------------------
// Output cotangent (direction) registers live in the output slots;
// the trial integration data is pushed into the input slots.
// -----------------------------------------------
args_reg_t<backend_t, qfunc_t, inputs_t, outputs_t, MQ1> rargs;
MFEM_SHARED typename backend_t::Shared smem;
// -----------------------------------------------
// Interpolate the test cotangent to quadrature points (output slots)
// -----------------------------------------------
for_constexpr<n_outputs>([&](auto oc)
{
constexpr size_t o = oc.value, ao = n_inputs + o;
using FOP = tuple_element_t<o, outputs_t>;
const auto &XE = out_XE_dir[o];
const int d = out_d1d[o], q = out_q1d[o], Q1D = q1d;
const real_t *B = out_B[o], *G = out_G[o];
auto &oarg = get<ao>(rargs);
if constexpr (is_value_fop_v<FOP>)
{
backend_t::LoadValue(smem, e, d, q, Q1D, B, XE, oarg);
}
else if constexpr (is_gradient_fop_v<FOP>)
{
constexpr auto RNK = qf_param_slot<qfunc_t, ao>::extents.size();
using FieldParamT =
typename qf_param_slot<qfunc_t, ao>::qf_decay_param_t;
backend_t::template LoadGradient<RNK,
decltype(oarg),
decltype(XE),
FieldParamT>(
smem, e, d, q, Q1D, B, G, XE, oarg);
}
else if constexpr (is_identity_fop_v<FOP>)
{
// identity cotangent is read directly at qp from out_XE_dir
}
else
{
static_assert(false, "Unsupported");
}
});
MFEM_SYNC_THREAD;
// -----------------------------------------------
// Contract the transposed cached Jacobian with the test cotangent at
// each quadrature point and push the trial result into the dependent
// input registers.
// -----------------------------------------------
MFEM_FOREACH_THREAD(qz, z, (B2D ? 1 : q1d))
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
const int q = qx + q1d * (qy + q1d * qz);
// The test cotangent at this quadrature point is the same
// for every trial column (j, m), so pull each interpolated
// output slot out of the register bank once, here, instead
// of once per column inside the contraction below. Identity
// outputs have no register bank and are read from
// out_XE_dir at the point of use.
args_tuple_t wvecs {};
for_constexpr<n_outputs>([&](auto oc)
{
constexpr size_t o = oc.value, ao = n_inputs + o;
using OFOP = tuple_element_t<o, outputs_t>;
if constexpr (is_value_fop_v<OFOP> ||
is_gradient_fop_v<OFOP>)
{
using OARG =
typename qf_param_slot<qfunc_t, ao>::qf_reg_param_t;
get<ao>(wvecs) = backend_t::template qp_pull<OARG>(
get<ao>(rargs), qx, qy, qz);
}
});
int m_offset = 0;
for_constexpr<n_inputs>([&](auto sc)
{
constexpr size_t s = sc.value;
if (!input_dep[s]) { return; }
using SARG =
typename qf_param_slot<qfunc_t, s>::qf_reg_param_t;
const int vdim_s = in_vdim[s];
const int op_dim_s = in_size_on_qp[s] / vdim_s;
SARG fhat{};
for (int j = 0; j < trial_vdim; j++)
{
for (int m = 0; m < op_dim_s; m++)
{
const int col =
j * total_trial_op_dim + (m + m_offset);
real_t sum = 0.0;
for_constexpr<n_outputs>([&](auto oc)
{
constexpr size_t o = oc.value, ao = n_inputs + o;
using OFOP = tuple_element_t<o, outputs_t>;
const int tv = out_vdim[o], to = out_op_dim[o];
const auto offset_o = out_offsets[o];
const auto &cache = cache_tensor;
if constexpr (is_value_fop_v<OFOP> ||
is_gradient_fop_v<OFOP>)
{
const auto &wvec = get<ao>(wvecs);
for (int i = 0; i < tv; i++)
{
for (int k = 0; k < to; k++)
{
const int row = offset_o + i * to + k;
const int cache_idx =
row * trial_vdim *
total_trial_op_dim +
col;
sum += cache(q, cache_idx, e) *
qf_value_at(wvec, i, k);
}
}
}
else if constexpr (is_identity_fop_v<OFOP>)
{
const auto &XEo = out_XE_dir[o];
for (int i = 0; i < tv; i++)
{
for (int k = 0; k < to; k++)
{
const int row = offset_o + i * to + k;
const int cache_idx =
row * trial_vdim *
total_trial_op_dim +
col;
sum += cache(q, cache_idx, e) *
XEo(i + tv * k, qx, qy, qz, e);
}
}
}
});
qf_set_value_at(fhat, j, m, sum);
}
}
backend_t::template qp_push<SARG>(
get<s>(rargs), qx, qy, qz, fhat);
m_offset += op_dim_s;
});
}
}
}
MFEM_SYNC_THREAD;
// -----------------------------------------------
// Integrate the trial result into the derivative field dofs. Multiple
// dependent input slots (e.g. value and gradient of the same field)
// accumulate into ye_XE via the writers' '+=' semantics.
// -----------------------------------------------
for_constexpr<n_inputs>([&](auto sc)
{
constexpr size_t s = sc.value;
if (!input_dep[s]) { return; }
using FOP = tuple_element_t<s, inputs_t>;
const int d = in_d1d[s], q = in_q1d[s], Q1D = q1d;
const real_t *B = in_B[s], *G = in_G[s];
auto &sarg = get<s>(rargs);
auto &YE = ye_XE;
if constexpr (is_value_fop_v<FOP>)
{
backend_t::WriteValue(smem, e, d, q, Q1D, B, YE, sarg);
}
else if constexpr (is_gradient_fop_v<FOP>)
{
using YE_t = decltype(YE);
using rarg_t = decltype(sarg);
using qf_param_t =
typename qf_param_slot<qfunc_t, s>::qf_decay_param_t;
constexpr auto RNK = qf_param_slot<qfunc_t, s>::extents.size();
backend_t::template WriteGradient<RNK, rarg_t, YE_t, qf_param_t>(
smem, e, d, q, Q1D, B, G, YE, sarg);
}
else
{
// identity / weight derivative targets are not produced here
}
});
},
ne,
backend_t::thread_blocks(compute_kernel_thread_1d<inputs_t, outputs_t>(
q1d, in_d1d, out_d1d)),
0,
nullptr);
}
using TransposeKernelType =
decltype(&DerivativeApplyTranspose::
derivative_apply_transpose_callback<>);
MFEM_REGISTER_KERNELS_HEADER_ONLY(DerivativeApplyTransposeLO,
TransposeKernelType,
(int, int) );
MFEM_REGISTER_KERNELS_HEADER_ONLY(DerivativeApplyTransposeHO,
TransposeKernelType,
(int, int) );
};
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
template<int DIM, int Q1D>
inline typename DerivativeApplyTranspose<derivative_id,
qfunc_t,
inputs_t,
outputs_t>::TransposeKernelType
DerivativeApplyTranspose<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeApplyTransposeLO::Kernel()
{
static_assert((DIM == 2 || DIM == 3) && Q1D <= 8);
using transpose_t =
DerivativeApplyTranspose<derivative_id, qfunc_t, inputs_t, outputs_t>;
return transpose_t::template derivative_apply_transpose_callback<
LocalQFLOBackend<DIM, Q1D>>;
}
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
inline typename DerivativeApplyTranspose<derivative_id,
qfunc_t,
inputs_t,
outputs_t>::TransposeKernelType
DerivativeApplyTranspose<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeApplyTransposeLO::Fallback(int dim, int q1d)
{
using transpose_t =
DerivativeApplyTranspose<derivative_id, qfunc_t, inputs_t, outputs_t>;
using DerivativeApplyTransposeLO =
typename transpose_t::DerivativeApplyTransposeLO;
if (dim == 2)
{
return DispatchLOKernelByQ1D<DerivativeApplyTransposeLO, 2>(q1d);
}
else if (dim == 3)
{
return DispatchLOKernelByQ1D<DerivativeApplyTransposeLO, 3>(q1d);
}
else
{
MFEM_ABORT("Unsupported dimension");
return nullptr;
}
}
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
template<int DIM, int Q1D>
inline typename DerivativeApplyTranspose<derivative_id,
qfunc_t,
inputs_t,
outputs_t>::TransposeKernelType
DerivativeApplyTranspose<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeApplyTransposeHO::Kernel()
{
using transpose_t =
DerivativeApplyTranspose<derivative_id, qfunc_t, inputs_t, outputs_t>;
return transpose_t::
template derivative_apply_transpose_callback<LocalQFHOBackend<DIM>, Q1D>;
}
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
inline typename DerivativeApplyTranspose<derivative_id,
qfunc_t,
inputs_t,
outputs_t>::TransposeKernelType
DerivativeApplyTranspose<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeApplyTransposeHO::Fallback(int dim, int q1d)
{
using transpose_t =
DerivativeApplyTranspose<derivative_id, qfunc_t, inputs_t, outputs_t>;
using DerivativeApplyTransposeHO =
typename transpose_t::DerivativeApplyTransposeHO;
if (dim == 2)
{
return DispatchHOKernelByQ1D<DerivativeApplyTransposeHO, 2>(q1d);
}
else if (dim == 3)
{
return DispatchHOKernelByQ1D<DerivativeApplyTransposeHO, 3>(q1d);
}
else
{
MFEM_ABORT("Unsupported dimension");
return nullptr;
}
}
} // namespace mfem::future::LocalQFImpl
@@ -0,0 +1,910 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../../integrator_ctx.hpp"
#include "../../../kernels.hpp"
#include "kernels.hpp"
#include "util.hpp"
#include <array>
#include <type_traits>
namespace ker = mfem::kernels::internal;
namespace mfem::future::LocalQFImpl
{
namespace detail
{
template<int DIM>
MFEM_HOST_DEVICE inline int tensor_idx(int x, int y, int z, int N)
{
static_assert(DIM == 2 || DIM == 3);
if constexpr (DIM == 2) { assert(z == 0); }
return x + N * (y + N * z);
}
template<int DIM>
MFEM_HOST_DEVICE inline real_t
trial_basis_weight_value(const DeviceTensor<3, const real_t> &B,
const int qx,
const int qy,
const int qz,
const int Jx,
const int Jy,
const int Jz)
{
static_assert(DIM == 2 || DIM == 3);
return B(qx, 0, Jx) * B(qy, 0, Jy) * ((DIM == 3) ? B(qz, 0, Jz) : 1.0);
}
template<int DIM>
MFEM_HOST_DEVICE inline real_t
trial_basis_weight_gradient(const DeviceTensor<3, const real_t> &B,
const DeviceTensor<3, const real_t> &G,
const int m,
const int qx,
const int qy,
const int qz,
const int Jx,
const int Jy,
const int Jz)
{
const auto Gx = G(qx, 0, Jx), Gy = G(qy, 0, Jy);
const auto Bx = B(qx, 0, Jx), By = B(qy, 0, Jy);
if constexpr (DIM == 2)
{
MFEM_CONTRACT_VAR(qz & Jz);
return (m == 0) ? Gx * By : Bx * Gy;
}
else
{
const auto Bz = B(qz, 0, Jz), Gz = G(qz, 0, Jz);
return (m == 0) ? Gx * By * Bz
: (m == 1) ? Bx * Gy * Bz
: (m == 2) ? Bx * By * Gz
: (assert(false), 0.0);
}
}
template<int DIM, int MQ1, typename Shared, typename output_t>
MFEM_HOST_DEVICE void
map_quadrature_data_to_fields(DeviceTensor<2, real_t> &y,
const DeviceTensor<3, real_t> &f,
const output_t &output,
const DofToQuadMap &dtq,
Shared &s,
const int tv_dof = -1)
{
using output_fop_t = std::decay_t<output_t>;
const auto B = dtq.B, G = dtq.G;
const bool f_slab = (tv_dof >= 0);
const int vdim = output.vdim;
const int vd_begin = f_slab ? tv_dof : 0;
const int vd_end = f_slab ? tv_dof + 1 : vdim;
if constexpr (is_value_fop_v<output_fop_t>)
{
const auto [q1d, unused, d1d] = B.GetShape();
MFEM_CONTRACT_VAR(unused);
const int test_dim = output.size_on_qp / vdim;
MFEM_CONTRACT_VAR(test_dim);
const int f_vdim = f_slab ? 1 : vdim;
if constexpr (DIM == 2)
{
const auto fqp = Reshape(&f(0, 0, 0), f_vdim, test_dim, q1d, q1d);
auto yd = Reshape(&y(0, 0), d1d, d1d, vdim);
ker::LoadMatrix(d1d, q1d, B, s.B);
ker::s_regs2d_t<MQ1> r_qp, Y;
for (int vd = vd_begin; vd < vd_end; vd++)
{
const int fi = f_slab ? 0 : vd;
MFEM_FOREACH_THREAD(qy, y, q1d)
MFEM_FOREACH_THREAD(qx, x, q1d)
{ r_qp[qy][qx] = fqp(fi, 0, qx, qy); }
MFEM_SYNC_THREAD;
ker::Eval2d<MQ1, true>(d1d, q1d, s.M, s.B, r_qp, Y);
MFEM_FOREACH_THREAD(dy, y, d1d)
MFEM_FOREACH_THREAD(dx, x, d1d) { yd(dx, dy, vd) += Y[dy][dx]; }
MFEM_SYNC_THREAD;
}
}
else
{
const auto fqp = Reshape(&f(0, 0, 0), f_vdim, test_dim, q1d, q1d, q1d);
auto yd = Reshape(&y(0, 0), d1d, d1d, d1d, vdim);
ker::LoadMatrix(d1d, q1d, B, s.B);
ker::s_regs3d_t<MQ1> f_qp, Y;
for (int vd = vd_begin; vd < vd_end; vd++)
{
const int fi = f_slab ? 0 : vd;
for (int qz = 0; qz < q1d; qz++)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
MFEM_FOREACH_THREAD(qx, x, q1d)
{ f_qp[qz][qy][qx] = fqp(fi, 0, qx, qy, qz); }
}
MFEM_SYNC_THREAD;
ker::Eval3d<MQ1, true>(d1d, q1d, s.M, s.B, f_qp, Y);
for (int dz = 0; dz < d1d; dz++)
{
MFEM_FOREACH_THREAD(dy, y, d1d)
MFEM_FOREACH_THREAD(dx, x, d1d)
{ yd(dx, dy, dz, vd) += Y[dz][dy][dx]; }
}
MFEM_SYNC_THREAD;
}
}
}
else if constexpr (is_gradient_fop_v<output_fop_t>)
{
const auto [q1d, unused, d1d] = G.GetShape();
MFEM_CONTRACT_VAR(unused);
const int test_dim = output.size_on_qp / vdim;
const int f_vdim = f_slab ? 1 : vdim;
if constexpr (DIM == 2)
{
const auto fqp = Reshape(&f(0, 0, 0), f_vdim, test_dim, q1d, q1d);
auto yd = Reshape(&y(0, 0), d1d, d1d, vdim);
ker::LoadMatrix(d1d, q1d, B, s.B);
ker::LoadMatrix(d1d, q1d, G, s.G);
ker::vd_regs2d_t<1, DIM, MQ1> X, Y;
for (int vd = vd_begin; vd < vd_end; vd++)
{
const int fi = f_slab ? 0 : vd;
MFEM_FOREACH_THREAD(qx, x, q1d)
MFEM_FOREACH_THREAD(qy, y, q1d)
for (int k = 0; k < DIM; k++)
{
X[0][k][qy][qx] = fqp(fi, k, qx, qy);
}
MFEM_SYNC_THREAD;
ker::Grad2d<1, DIM, MQ1, true>(d1d, q1d, s.M, s.B, s.G, X, Y);
MFEM_FOREACH_THREAD(dy, y, d1d)
MFEM_FOREACH_THREAD(dx, x, d1d)
{
real_t u = 0.0;
for (int k = 0; k < DIM; k++) { u += Y[0][k][dy][dx]; }
yd(dx, dy, vd) += u;
}
MFEM_SYNC_THREAD;
}
}
else
{
const auto fqp = Reshape(&f(0, 0, 0), f_vdim, test_dim, q1d, q1d, q1d);
auto yd = Reshape(&y(0, 0), d1d, d1d, d1d, vdim);
ker::LoadMatrix(d1d, q1d, B, s.B);
ker::LoadMatrix(d1d, q1d, G, s.G);
ker::vd_regs3d_t<1, DIM, MQ1> X, Y;
for (int vd = vd_begin; vd < vd_end; vd++)
{
const int fi = f_slab ? 0 : vd;
for (int qz = 0; qz < q1d; qz++)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
MFEM_FOREACH_THREAD(qx, x, q1d)
for (int k = 0; k < DIM; k++)
{
X[0][k][qz][qy][qx] = fqp(fi, k, qx, qy, qz);
}
}
MFEM_SYNC_THREAD;
ker::Grad3d<1, DIM, MQ1, true>(d1d, q1d, s.M, s.B, s.G, X, Y);
for (int dz = 0; dz < d1d; dz++)
{
MFEM_FOREACH_THREAD(dy, y, d1d)
MFEM_FOREACH_THREAD(dx, x, d1d)
{
real_t u = 0.0;
for (int k = 0; k < DIM; k++) { u += Y[0][k][dz][dy][dx]; }
yd(dx, dy, dz, vd) += u;
}
}
MFEM_SYNC_THREAD;
}
}
}
else if constexpr (is_identity_fop_v<output_fop_t>)
{
const auto [q1d, unused, d1d] = B.GetShape();
MFEM_CONTRACT_VAR(unused);
MFEM_CONTRACT_VAR(d1d);
const int f_sq = f_slab ? 1 : output.size_on_qp;
const int sq_begin = f_slab ? tv_dof : 0;
const int sq_end = f_slab ? tv_dof + 1 : output.size_on_qp;
if constexpr (DIM == 2)
{
const auto fqp = Reshape(&f(0, 0, 0), f_sq, q1d, q1d);
auto yqp = Reshape(&y(0, 0), output.size_on_qp, q1d, q1d);
for (int sq = sq_begin; sq < sq_end; sq++)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
MFEM_FOREACH_THREAD(qx, x, q1d)
{
int qz = 0;
MFEM_CONTRACT_VAR(qz);
yqp(sq, qx, qy) = fqp(0, qx, qy);
}
MFEM_SYNC_THREAD;
}
}
else
{
const auto fqp = Reshape(&f(0, 0, 0), f_sq, q1d, q1d, q1d);
auto yqp = Reshape(&y(0, 0), output.size_on_qp, q1d, q1d, q1d);
for (int sq = sq_begin; sq < sq_end; sq++)
{
for (int qz = 0; qz < q1d; qz++)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
MFEM_FOREACH_THREAD(qx, x, q1d)
{ yqp(sq, qx, qy, qz) = fqp(0, qx, qy, qz); }
}
MFEM_SYNC_THREAD;
}
}
}
else
{
MFEM_ABORT_KERNEL("quadrature data mapping to field is not implemented"
" for this field descriptor with sum factorization on"
" tensor product elements");
}
}
template<int DIM,
int MQ1,
typename Shared,
typename input_fop_ts,
std::size_t n_inputs,
typename output_fop_t>
MFEM_HOST_DEVICE void assemble_element_mat_sumfact(
const DeviceTensor<5, real_t> &Ae,
const DeviceTensor<6, const real_t> &qpdc,
const int e,
const DeviceTensor<1, const real_t> &itod,
const input_fop_ts &inputs,
const output_fop_t &output,
const std::array<DofToQuadMap, n_inputs> &input_dtq_maps,
const DofToQuadMap &output_dtq,
const int q1d,
const int num_trial_dof_1d,
Shared &smem)
{
static constexpr int MQN = (DIM == 2) ? MQ1 * MQ1 : MQ1 * MQ1 * MQ1;
// Slab must hold full (test_vdim, test_op_dim, nq) fhat
static constexpr int FHAT_SLAB_MAX = MQN * 4;
static constexpr bool grad_out = is_gradient_fop_v<output_fop_t>;
static constexpr bool ident_out = is_identity_fop_v<output_fop_t>;
// qpdc shape: (nq, total_trial_op_dim, trial_vdim, test_op_dim, test_vdim, ne)
const int test_vdim = qpdc.GetShape()[4];
const int test_op_dim = qpdc.GetShape()[3];
const int trial_vdim = qpdc.GetShape()[2];
const int num_test_dof = Ae.GetShape()[0];
const int nq = qpdc.GetShape()[0];
const int size_on_qp = output.size_on_qp;
#if !(defined(MFEM_USE_CUDA) || defined(MFEM_USE_HIP))
MFEM_VERIFY(test_op_dim <= DIM,
"DerivativeAssemble: test_op_dim exceeds spatial DIM");
MFEM_VERIFY(test_op_dim * nq <= FHAT_SLAB_MAX,
"DerivativeAssemble: fhat slab exceeds capacity");
#endif
MFEM_SHARED real_t fhat_storage[FHAT_SLAB_MAX];
const auto &inputs_ref = inputs;
// Iterate quadrature points using the thread-block mapping
const auto foreach_qp = [&](auto &&body)
{
if constexpr (DIM == 2)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
MFEM_FOREACH_THREAD(qy, y, q1d) { body(qx, qy, 0); }
}
else
{
for (int qz = 0; qz < q1d; qz++)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
MFEM_FOREACH_THREAD(qx, x, q1d) { body(qx, qy, qz); }
}
}
};
const auto zero_slab = [&](const int n_comp)
{
foreach_qp([&](const int qx, const int qy, const int qz)
{
const int q = tensor_idx<DIM>(qx, qy, qz, q1d);
for (int k = 0; k < n_comp; k++) { fhat_storage[k * nq + q] = 0.0; }
});
MFEM_SYNC_THREAD;
};
const auto accumulate_tv = [&](const int Jx,
const int Jy,
const int Jz,
const int j,
const int tv,
const int tod_only = -1)
{
int m_offset = 0;
for_constexpr<n_inputs>([&](auto inp)
{
using fop_t = std::decay_t<decltype(get<inp>(inputs_ref))>;
const int trial_op_dim = static_cast<int>(itod(static_cast<int>(inp)));
if (trial_op_dim == 0) { return; }
const auto &B = input_dtq_maps[inp].B;
const auto &G = input_dtq_maps[inp].G;
if constexpr (is_value_fop<fop_t>::value)
{
foreach_qp([&](const int qx, const int qy, const int qz)
{
const int q = tensor_idx<DIM>(qx, qy, qz, q1d);
const real_t w =
trial_basis_weight_value<DIM>(B, qx, qy, qz, Jx, Jy, Jz);
for (int m = 0; m < trial_op_dim; m++)
{
for (int k = 0; k < test_op_dim; k++)
{
if (tod_only >= 0 && k != tod_only) { continue; }
const real_t f = qpdc(q, m + m_offset, j, k, tv, e);
if constexpr (grad_out && !ident_out)
{
fhat_storage[k * nq + q] += f * w;
}
else
{
fhat_storage[q] += f * w;
}
}
}
});
}
else if constexpr (is_gradient_fop<fop_t>::value)
{
foreach_qp([&](const int qx, const int qy, const int qz)
{
const int q = tensor_idx<DIM>(qx, qy, qz, q1d);
for (int m = 0; m < trial_op_dim; m++)
{
const real_t w = trial_basis_weight_gradient<DIM>(
B, G, m, qx, qy, qz, Jx, Jy, Jz);
for (int k = 0; k < test_op_dim; k++)
{
if (tod_only >= 0 && k != tod_only) { continue; }
const real_t f = qpdc(q, m + m_offset, j, k, tv, e);
if constexpr (grad_out && !ident_out)
{
fhat_storage[k * nq + q] += f * w;
}
else
{
fhat_storage[q] += f * w;
}
}
}
});
}
else
{
MFEM_ABORT_KERNEL("sum factorized sparse matrix assemble routine "
"not implemented for field operator");
}
MFEM_SYNC_THREAD;
m_offset += trial_op_dim;
});
};
for (int Jz = 0; Jz < ((DIM == 2) ? 1 : num_trial_dof_1d); Jz++)
{
for (int Jy = 0; Jy < num_trial_dof_1d; Jy++)
{
for (int Jx = 0; Jx < num_trial_dof_1d; Jx++)
{
const int J = tensor_idx<DIM>(Jx, Jy, Jz, num_trial_dof_1d);
for (int j = 0; j < trial_vdim; j++)
{
auto bvtfhat =
Reshape(&Ae(0, 0, J, j, e), num_test_dof, test_vdim);
const int fhat_size = test_vdim * test_op_dim * nq;
if (fhat_size <= FHAT_SLAB_MAX)
{
auto fhat =
Reshape(&fhat_storage[0], test_vdim, test_op_dim, nq);
for (int tv = 0; tv < test_vdim; tv++)
{
for (int tod = 0; tod < test_op_dim; tod++)
{
foreach_qp([&](const int qx, const int qy, const int qz)
{
const int q = tensor_idx<DIM>(qx, qy, qz, q1d);
fhat(tv, tod, q) = 0.0;
});
}
}
MFEM_SYNC_THREAD;
int m_offset = 0;
for_constexpr<n_inputs>([&](auto inp)
{
using fop_t = std::decay_t<decltype(get<inp>(inputs_ref))>;
const int trial_op_dim =
static_cast<int>(itod(static_cast<int>(inp)));
if (trial_op_dim == 0) { return; }
const auto &B = input_dtq_maps[inp].B;
const auto &G = input_dtq_maps[inp].G;
if constexpr (is_value_fop<fop_t>::value)
{
foreach_qp([&](const int qx, const int qy, const int qz)
{
const int q = tensor_idx<DIM>(qx, qy, qz, q1d);
const real_t w = trial_basis_weight_value<DIM>(
B, qx, qy, qz, Jx, Jy, Jz);
for (int m = 0; m < trial_op_dim; m++)
{
for (int i = 0; i < test_vdim; i++)
{
for (int k = 0; k < test_op_dim; k++)
{
const real_t f =
qpdc(q, m + m_offset, j, k, i, e);
fhat(i, k, q) += f * w;
}
}
}
});
}
else if constexpr (is_gradient_fop<fop_t>::value)
{
foreach_qp([&](const int qx, const int qy, const int qz)
{
const int q = tensor_idx<DIM>(qx, qy, qz, q1d);
for (int m = 0; m < trial_op_dim; m++)
{
const real_t w = trial_basis_weight_gradient<DIM>(
B, G, m, qx, qy, qz, Jx, Jy, Jz);
for (int i = 0; i < test_vdim; i++)
{
for (int k = 0; k < test_op_dim; k++)
{
const real_t f =
qpdc(q, m + m_offset, j, k, i, e);
fhat(i, k, q) += f * w;
}
}
}
});
}
else
{
MFEM_ABORT_KERNEL(
"sum factorized sparse matrix assemble routine "
"not implemented for field operator");
}
MFEM_SYNC_THREAD;
m_offset += trial_op_dim;
});
map_quadrature_data_to_fields<DIM, MQ1>(
bvtfhat, fhat, output, output_dtq, smem);
}
else if constexpr (ident_out)
{
for (int sq = 0; sq < size_on_qp; sq++)
{
const int tv = sq / test_op_dim;
const int tod = sq % test_op_dim;
zero_slab(1);
accumulate_tv(Jx, Jy, Jz, j, tv, tod);
auto f_slab = Reshape(&fhat_storage[0], 1, 1, nq);
map_quadrature_data_to_fields<DIM, MQ1>(
bvtfhat, f_slab, output, output_dtq, smem, sq);
}
}
else if constexpr (grad_out)
{
for (int tv = 0; tv < test_vdim; tv++)
{
zero_slab(test_op_dim);
accumulate_tv(Jx, Jy, Jz, j, tv);
auto f_slab =
Reshape(&fhat_storage[0], 1, test_op_dim, nq);
map_quadrature_data_to_fields<DIM, MQ1>(
bvtfhat, f_slab, output, output_dtq, smem, tv);
}
}
else
{
for (int tv = 0; tv < test_vdim; tv++)
{
zero_slab(1);
accumulate_tv(Jx, Jy, Jz, j, tv);
auto f_slab = Reshape(&fhat_storage[0], 1, 1, nq);
map_quadrature_data_to_fields<DIM, MQ1>(
bvtfhat, f_slab, output, output_dtq, smem, tv);
}
}
}
}
}
}
}
} // namespace detail
// ────────────────────────────────────────────────────────────────────────────
// Assemble sparse Jacobian from cached quadrature derivatives (tensor 2D/3D)
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
class DerivativeAssemble
{
static constexpr auto inout_tuple =
merge_mfem_tuples_as_empty_std_tuple(inputs_t {}, outputs_t{});
static constexpr auto filtered_inout_tuple = filter_fields(inout_tuple);
static constexpr size_t nfields =
count_unique_field_ids(filtered_inout_tuple);
static constexpr std::size_t n_inputs = tuple_size<inputs_t>::value;
static constexpr std::size_t n_outputs = tuple_size<outputs_t>::value;
const IntegratorContext ctx;
const Vector &qp_cache;
inputs_t inputs;
outputs_t outputs;
const bool use_sum_factorization;
const std::vector<const DofToQuad *> dtqs;
const std::array<DofToQuadMap, n_inputs> input_dtq_maps;
const std::array<DofToQuadMap, n_outputs> output_dtq_maps;
const std::array<bool, n_inputs> input_is_dependent;
const size_t trial_field_uf;
const size_t test_field_uf;
const ParFiniteElementSpace *test_fes;
const ParFiniteElementSpace *trial_fes;
const int test_vdim;
const int test_op_dim;
const int num_test_dof;
const int trial_vdim;
const int trial_op_dim;
const int num_trial_dof;
const int dim, ne, nq, q1d;
const int num_trial_dof_1d;
const int total_trial_op_dim;
mutable Vector inputs_trial_op_dim;
mutable Vector Ae_mem;
public:
DerivativeAssemble() = delete;
DerivativeAssemble(IntegratorContext ctx_in,
qfunc_t /*qfunc*/,
inputs_t inputs_in,
outputs_t outputs_in,
const Vector &qp_cache_in):
ctx(ctx_in), qp_cache(qp_cache_in), inputs(inputs_in),
outputs(outputs_in), use_sum_factorization(
[&]
{
const Element::Type etype =
Element::TypeFromGeometry(ctx_in.mesh.GetTypicalElementGeometry());
return (etype == Element::QUADRILATERAL || etype == Element::HEXAHEDRON);
}()),
dtqs(
[&]
{
const DofToQuad::Mode dtq_mode = use_sum_factorization
? DofToQuad::Mode::TENSOR
: DofToQuad::Mode::FULL;
std::vector<const DofToQuad *> maps;
maps.reserve(ctx_in.unionfds.size());
for (const auto &field : ctx_in.unionfds)
{
maps.emplace_back(
GetDofToQuad<Entity::Element>(field, ctx_in.ir, dtq_mode));
}
return maps;
}()),
input_dtq_maps(create_dtq_maps<Entity::Element>(
inputs,
dtqs,
create_union_field_map_for_dtq(ctx_in, inputs),
ctx_in.unionfds,
ctx_in.ir)),
output_dtq_maps(create_dtq_maps<Entity::Element>(
outputs,
dtqs,
create_union_field_map_for_dtq(ctx_in, outputs),
ctx_in.unionfds,
ctx_in.ir)),
input_is_dependent(compute_input_is_dependent(inputs, derivative_id)),
trial_field_uf(find_union_field_index(ctx_in, derivative_id)),
test_field_uf(
find_union_field_index(ctx_in, get<0>(outputs).GetFieldId())),
test_fes(
[&]
{
const auto *fes = std::get_if<const ParFiniteElementSpace *>(
&ctx_in.unionfds[test_field_uf].data);
MFEM_ASSERT(fes != nullptr && *fes != nullptr,
"LocalQFBackend: test space is not a ParFiniteElementSpace");
return *fes;
}()),
trial_fes(
[&]
{
const auto *fes = std::get_if<const ParFiniteElementSpace *>(
&ctx_in.unionfds[trial_field_uf].data);
MFEM_ASSERT(fes != nullptr && *fes != nullptr,
"LocalQFBackend: trial space is not a ParFiniteElementSpace");
return *fes;
}()),
test_vdim(get<0>(outputs).vdim),
test_op_dim(get<0>(outputs).size_on_qp / test_vdim),
num_test_dof(test_fes->GetFE(0)->GetDof()),
trial_vdim(compute_trial_vdim(inputs, derivative_id)), trial_op_dim(
[&]
{
int top = 0;
for_constexpr<n_inputs>([&](auto i)
{
if (get<i>(inputs).GetFieldId() == derivative_id)
{
top = get<i>(inputs).size_on_qp / get<i>(inputs).vdim;
}
});
return top;
}()),
num_trial_dof(trial_fes->GetFE(0)->GetDof()),
dim(ctx_in.mesh.Dimension()), ne(ctx_in.nentities),
nq(ctx_in.ir.GetNPoints()), q1d(tensor_1d_size(nq, dim)),
num_trial_dof_1d(tensor_1d_size(num_trial_dof, dim)), total_trial_op_dim(
[&]
{
const auto in_qp_sizes =
get_input_size_on_qp(inputs, std::make_index_sequence<n_inputs>{});
return compute_total_trial_op_dim(
inputs, input_is_dependent, in_qp_sizes);
}()),
inputs_trial_op_dim(), Ae_mem()
{
MFEM_ASSERT(ctx.unionfds.size() == nfields,
"LocalQFBackend: unionfds size mismatch");
MFEM_ASSERT(trial_field_uf != SIZE_MAX,
"DerivativeAssemble: trial field not found in unionfds");
MFEM_ASSERT(test_field_uf != SIZE_MAX,
"DerivativeAssemble: test field not found in unionfds");
MFEM_ASSERT(trial_vdim > 0,
"LocalQFBackend: could not determine trial vdim");
MFEM_ASSERT(total_trial_op_dim > 0,
"LocalQFBackend: no dependent inputs found");
inputs_trial_op_dim.UseDevice(true);
inputs_trial_op_dim.SetSize(n_inputs);
auto inputs_trial_op_dim_host = inputs_trial_op_dim.HostWrite();
for_constexpr<n_inputs>([&](auto i)
{
inputs_trial_op_dim_host[i] =
input_is_dependent[i]
? get<i>(inputs).size_on_qp / get<i>(inputs).vdim
: 0;
});
const int elem_mat_size =
num_test_dof * test_vdim * num_trial_dof * trial_vdim;
Ae_mem.SetSize(elem_mat_size * ne, Device::GetDeviceMemoryType());
Ae_mem.UseDevice(true);
Ae_mem = 0.0;
}
void operator()(SparseMatrix *&A) const
{
if (ctx.attr.Size() == 0) { return; }
if (!(use_sum_factorization && (dim == 2 || dim == 3)))
{
MFEM_ABORT("DerivativeAssemble optimized path is implemented "
"for tensor-product 2D/3D elements only");
}
DerivativeAssembleHO::Run(dim,
q1d,
ctx,
qp_cache,
Ae_mem,
inputs,
outputs,
input_dtq_maps,
output_dtq_maps[0],
inputs_trial_op_dim,
test_vdim,
test_op_dim,
num_test_dof,
num_trial_dof,
num_trial_dof_1d,
trial_vdim,
total_trial_op_dim,
nq,
ne,
q1d,
dim);
A = new SparseMatrix;
A->OverrideSize(test_fes->GetVSize(), trial_fes->GetVSize());
const auto *test_restr = dynamic_cast<const ElementRestriction *>(
test_fes->GetElementRestriction(ElementDofOrdering::LEXICOGRAPHIC));
const auto *trial_restr = dynamic_cast<const ElementRestriction *>(
trial_fes->GetElementRestriction(ElementDofOrdering::LEXICOGRAPHIC));
MFEM_VERIFY(test_restr != nullptr && trial_restr != nullptr,
"DerivativeAssemble SparseMatrix assembly requires "
"H1/conforming ElementRestriction spaces");
test_restr->FillSparseMatrix(Ae_mem, *A, *trial_restr);
}
template<typename backend_t = LocalQFHOBackend<3>, int T_Q1D = 0>
static void derivative_assemble_callback(
const IntegratorContext &ctx,
const Vector &qp_cache,
Vector &Ae_mem,
const inputs_t &inputs,
const outputs_t &outputs,
const std::array<DofToQuadMap, n_inputs> &input_dtq_maps,
const DofToQuadMap &output_dtq,
const Vector &inputs_trial_op_dim,
const int test_vdim,
const int test_op_dim,
const int num_test_dof,
const int num_trial_dof,
const int num_trial_dof_1d,
const int trial_vdim,
const int total_trial_op_dim,
const int nq,
const int ne,
const int q1d,
const int dim)
{
static constexpr int DIM = backend_t::DIM;
static constexpr int MQ1 = T_Q1D ? T_Q1D : backend_t::MQ1;
static constexpr int MNQ = (DIM == 2) ? MQ1 * MQ1 : MQ1 * MQ1 * MQ1;
MFEM_VERIFY(dim == DIM,
"DerivativeAssemble: mesh dim does not match backend");
MFEM_VERIFY(dim == ctx.mesh.Dimension(), "Dimension mismatch");
MFEM_VERIFY(q1d <= MQ1, "q1d exceeds backend MQ1 limit");
MFEM_VERIFY(nq <= MNQ,
"DerivativeAssemble: nq exceeds backend quadrature capacity");
MFEM_VERIFY(test_op_dim <= DIM,
"DerivativeAssemble: test_op_dim exceeds spatial DIM");
if (ctx.attr.Size() == 0) { return; }
const auto d_attr = ctx.attr.Read();
const bool has_attr = ctx.attr.Size() > 0;
const auto d_elem_attr = ctx.elem_attr->Read();
const auto qpdc = Reshape(qp_cache.Read(),
nq,
total_trial_op_dim,
trial_vdim,
test_op_dim,
test_vdim,
ne);
const auto itod = Reshape(inputs_trial_op_dim.Read(), n_inputs);
auto Ae = Reshape(Ae_mem.ReadWrite(),
num_test_dof,
test_vdim,
num_trial_dof,
trial_vdim,
ne);
dfem::forall(
[=] MFEM_HOST_DEVICE(const int e, void *)
{
if (has_attr && !d_attr[d_elem_attr[e] - 1]) { return; }
static constexpr int DIM = backend_t::DIM;
static constexpr int MQ1 = T_Q1D ? T_Q1D : backend_t::MQ1;
MFEM_SHARED typename backend_t::Shared s;
detail::assemble_element_mat_sumfact<DIM, MQ1>(Ae,
qpdc,
e,
itod,
inputs,
get<0>(outputs),
input_dtq_maps,
output_dtq,
q1d,
num_trial_dof_1d,
s);
},
ne,
backend_t::thread_blocks(q1d),
0,
nullptr);
}
using AssembleKernelType =
decltype(&DerivativeAssemble::derivative_assemble_callback<>);
MFEM_REGISTER_KERNELS_HEADER_ONLY(DerivativeAssembleHO,
AssembleKernelType,
(int, int));
};
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
template<int DIM, int Q1D>
inline
typename DerivativeAssemble<derivative_id, qfunc_t, inputs_t, outputs_t>::
AssembleKernelType
DerivativeAssemble<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeAssembleHO::Kernel()
{
static_assert(DIM == 2 || DIM == 3);
using assemble_t =
DerivativeAssemble<derivative_id, qfunc_t, inputs_t, outputs_t>;
return assemble_t::template derivative_assemble_callback<
LocalQFHOBackend<DIM, Q1D>>;
}
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
inline
typename DerivativeAssemble<derivative_id, qfunc_t, inputs_t, outputs_t>::
AssembleKernelType
DerivativeAssemble<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeAssembleHO::Fallback(int dim, int q1d)
{
using assemble_t =
DerivativeAssemble<derivative_id, qfunc_t, inputs_t, outputs_t>;
using DerivativeAssembleHO = typename assemble_t::DerivativeAssembleHO;
if (dim == 2)
{
return DispatchHOKernelByQ1D<DerivativeAssembleHO, 2>(q1d);
}
else if (dim == 3)
{
return DispatchHOKernelByQ1D<DerivativeAssembleHO, 3, 8>(q1d);
}
else
{
MFEM_ABORT("Unsupported dimension");
return nullptr;
}
}
} // namespace mfem::future::LocalQFImpl
@@ -0,0 +1,540 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../../integrator_ctx.hpp"
#include "kernels.hpp"
#include "util.hpp"
#include <array>
namespace mfem::future::LocalQFImpl
{
// Assemble diagonal of cached Jacobian (square trial == test, tensor 2D/3D)
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
class DerivativeAssembleDiagonal
{
static constexpr auto inout_tuple =
merge_mfem_tuples_as_empty_std_tuple(inputs_t {}, outputs_t{});
static constexpr auto filtered_inout_tuple = filter_fields(inout_tuple);
static constexpr size_t nfields =
count_unique_field_ids(filtered_inout_tuple);
static constexpr std::size_t n_inputs = tuple_size<inputs_t>::value;
static constexpr std::size_t n_outputs = tuple_size<outputs_t>::value;
const IntegratorContext ctx;
const Vector &qp_cache;
inputs_t inputs;
outputs_t outputs;
const bool use_sum_factorization;
const std::vector<const DofToQuad *> dtqs;
const std::array<DofToQuadMap, n_inputs> input_dtq_maps;
const std::array<DofToQuadMap, n_outputs> output_dtq_maps;
const std::array<bool, n_inputs> input_is_dependent;
const size_t trial_field_uf;
const size_t test_field_uf;
const bool is_square;
const int test_vdim;
const std::array<int, n_outputs> out_vdim;
const std::array<int, n_outputs> out_op_dim;
const std::array<int, n_outputs> out_offsets;
const int output_size_on_qp;
const int num_test_dof;
const int num_test_dof_1d;
const int trial_vdim;
const int total_trial_op_dim;
const int num_trial_dof_1d;
const int residual_size_on_qp;
const int dim, ne, nq, q1d;
const std::array<int, n_inputs> inputs_trial_op_dim;
mutable Vector Ye_mem;
public:
DerivativeAssembleDiagonal() = delete;
DerivativeAssembleDiagonal(IntegratorContext ctx_in,
qfunc_t /*qfunc*/,
inputs_t inputs_in,
outputs_t outputs_in,
const Vector &qp_cache_in):
ctx(ctx_in), qp_cache(qp_cache_in), inputs(inputs_in),
outputs(outputs_in), use_sum_factorization(
[&]
{
const Element::Type etype =
Element::TypeFromGeometry(ctx_in.mesh.GetTypicalElementGeometry());
return (etype == Element::QUADRILATERAL || etype == Element::HEXAHEDRON);
}()),
dtqs(
[&]
{
const DofToQuad::Mode dtq_mode = use_sum_factorization
? DofToQuad::Mode::TENSOR
: DofToQuad::Mode::FULL;
std::vector<const DofToQuad *> maps;
maps.reserve(ctx_in.unionfds.size());
for (const auto &field : ctx_in.unionfds)
{
maps.emplace_back(
GetDofToQuad<Entity::Element>(field, ctx_in.ir, dtq_mode));
}
return maps;
}()),
input_dtq_maps(create_dtq_maps<Entity::Element>(
inputs,
dtqs,
create_union_field_map_for_dtq(ctx_in, inputs),
ctx_in.unionfds,
ctx_in.ir)),
output_dtq_maps(create_dtq_maps<Entity::Element>(
outputs,
dtqs,
create_union_field_map_for_dtq(ctx_in, outputs),
ctx_in.unionfds,
ctx_in.ir)),
input_is_dependent(compute_input_is_dependent(inputs, derivative_id)),
trial_field_uf(find_union_field_index(ctx_in, derivative_id)),
test_field_uf(
find_union_field_index(ctx_in, get<0>(outputs).GetFieldId())),
is_square(
[&]
{
const auto *test_fes = std::get_if<const ParFiniteElementSpace *>(
&ctx_in.unionfds[test_field_uf].data);
const auto *trial_fes = std::get_if<const ParFiniteElementSpace *>(
&ctx_in.unionfds[trial_field_uf].data);
return test_fes && trial_fes && *test_fes && *trial_fes &&
(*test_fes == *trial_fes);
}()),
test_vdim(get<0>(outputs).vdim),
out_vdim(get_vdim(outputs_in)),
out_op_dim(compute_out_op_dim(outputs_in)),
out_offsets(compute_out_offsets(out_vdim, out_op_dim)),
output_size_on_qp(
[&]
{
int s = 0;
for_constexpr<n_outputs>([&](auto o)
{ s += get<o>(outputs_in).size_on_qp; });
return s;
}()), num_test_dof(
[&]
{
const auto *test_fes = std::get_if<const ParFiniteElementSpace *>(
&ctx_in.unionfds[test_field_uf].data);
MFEM_ASSERT(test_fes != nullptr && *test_fes != nullptr,
"LocalQFBackend: test space is not a ParFiniteElementSpace");
return (*test_fes)->GetFE(0)->GetDof();
}()),
num_test_dof_1d(tensor_1d_size(num_test_dof, ctx_in.mesh.Dimension())),
trial_vdim(compute_trial_vdim(inputs, derivative_id)), total_trial_op_dim(
[&]
{
const auto input_size_on_qp =
get_input_size_on_qp(inputs, std::make_index_sequence<n_inputs>{});
return compute_total_trial_op_dim(
inputs, input_is_dependent, input_size_on_qp);
}()),
num_trial_dof_1d(
[&]
{
const auto *trial_fes = std::get_if<const ParFiniteElementSpace *>(
&ctx_in.unionfds[trial_field_uf].data);
MFEM_ASSERT(trial_fes != nullptr && *trial_fes != nullptr,
"LocalQFBackend: trial space is not a ParFiniteElementSpace");
const int num_trial_dof = (*trial_fes)->GetFE(0)->GetDof();
return tensor_1d_size(num_trial_dof, ctx_in.mesh.Dimension());
}()),
residual_size_on_qp(output_size_on_qp * trial_vdim * total_trial_op_dim),
dim(ctx_in.mesh.Dimension()), ne(ctx_in.nentities),
nq(ctx_in.ir.GetNPoints()), q1d(tensor_1d_size(nq, dim)),
inputs_trial_op_dim(
[&]
{
std::array<int, n_inputs> itod{};
for_constexpr<n_inputs>([&](auto i)
{
itod[i] = input_is_dependent[i]
? get<i>(inputs).size_on_qp / get<i>(inputs).vdim
: 0;
});
return itod;
}()),
Ye_mem()
{
MFEM_ASSERT(ctx.unionfds.size() == nfields,
"LocalQFBackend: unionfds size mismatch");
MFEM_ASSERT(
trial_field_uf != SIZE_MAX,
"DerivativeAssembleDiagonal: trial field not found in unionfds");
MFEM_ASSERT(
test_field_uf != SIZE_MAX,
"DerivativeAssembleDiagonal: test field not found in unionfds");
MFEM_ASSERT(trial_vdim > 0,
"LocalQFBackend: could not determine trial vdim");
MFEM_ASSERT(total_trial_op_dim > 0,
"LocalQFBackend: no dependent inputs found");
for_constexpr<n_outputs>([&](auto o)
{
MFEM_CONTRACT_VAR(o);
MFEM_ASSERT(out_vdim[o] == test_vdim,
"DerivativeAssembleDiagonal: all outputs must share the "
"test field vdim");
});
if (is_square)
{
Ye_mem.SetSize(num_test_dof * test_vdim * ne);
Ye_mem.UseDevice(true);
}
}
template<typename Backend>
void run_kernels() const
{
Backend::Run(dim,
q1d,
ctx,
qp_cache,
Ye_mem,
inputs,
outputs,
output_dtq_maps,
input_dtq_maps,
test_vdim,
out_op_dim,
out_offsets,
output_size_on_qp,
num_test_dof,
num_test_dof_1d,
trial_vdim,
total_trial_op_dim,
residual_size_on_qp,
inputs_trial_op_dim,
nq,
ne,
q1d,
dim);
}
void operator()(Vector &diag_e) const
{
if (!is_square) { return; }
if (ctx.attr.Size() == 0) { return; }
if (!(use_sum_factorization && (dim == 2 || dim == 3)))
{
MFEM_ABORT("DerivativeAssembleDiagonal optimized path is implemented "
"for tensor-product 2D/3D elements only");
}
MFEM_VERIFY(num_test_dof_1d == num_trial_dof_1d,
"DerivativeAssembleDiagonal requires matching tensor dofs");
MFEM_VERIFY(num_test_dof_1d <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(q1d <= DeviceDofQuadLimits::Get().MAX_Q1D, "");
Ye_mem = 0.0;
if (q1d <= LocalQFLOBackendMQ1())
{
run_kernels<DerivativeAssembleDiagonalLO>();
}
else if (q1d <= LocalQFHOBackendMQ1())
{
run_kernels<DerivativeAssembleDiagonalHO>();
}
else
{
MFEM_ABORT("Unsupported quadrature order for LocalQF backend");
}
diag_e += Ye_mem;
}
template<typename backend_t = LocalQFLOBackend<3>, int T_Q1D = 0>
static void derivative_assemble_diagonal_callback(
const IntegratorContext &ctx,
const Vector &qp_cache,
Vector &Ye_mem,
const inputs_t &inputs,
const outputs_t &outputs,
const std::array<DofToQuadMap, n_outputs> &output_dtq_maps,
const std::array<DofToQuadMap, n_inputs> &input_dtq_maps,
const int test_vdim,
const std::array<int, n_outputs> &out_op_dim,
const std::array<int, n_outputs> &out_offsets,
const int output_size_on_qp,
const int num_test_dof,
const int num_test_dof_1d,
const int trial_vdim,
const int total_trial_op_dim,
const int residual_size_on_qp,
const std::array<int, n_inputs> &inputs_trial_op_dim,
const int nq,
const int ne,
const int q1d,
const int dim)
{
MFEM_VERIFY(dim == ctx.mesh.Dimension(), "Dimension mismatch");
if (ctx.attr.Size() == 0) { return; }
static constexpr bool B2D = backend_t::DIM == 2;
static constexpr int MTPB = backend_t::MAX_THREADS_PER_BLOCK();
const auto d_attr = ctx.attr.Read();
const bool has_attr = ctx.attr.Size() > 0;
const auto d_elem_attr = ctx.elem_attr->Read();
auto cache_tensor = DeviceTensor<3, const real_t>(
qp_cache.Read(), nq, residual_size_on_qp, ne);
const int num_dofs_per_elem = num_test_dof * test_vdim;
auto Ye = Reshape(Ye_mem.ReadWrite(), num_dofs_per_elem, ne);
dfem::forall<MTPB>(
[=] MFEM_HOST_DEVICE(const int e, void *)
{
if (has_attr && !d_attr[d_elem_attr[e] - 1]) { return; }
// The cache is written with the quadrature index fastest, then the
// trial op index, then the (test vdim, test op) rows of all outputs
// stacked via out_offsets.
auto qpdc = Reshape(&cache_tensor(0, 0, e),
nq,
total_trial_op_dim,
trial_vdim,
output_size_on_qp);
// Backend-owned shared scratch for the sum-factorized contraction.
MFEM_SHARED typename backend_t::Shared s_diag;
const int nz_dof = B2D ? 1 : num_test_dof_1d;
for (int vd = 0; vd < test_vdim; vd++)
{
auto Y = Reshape(&Ye(vd * num_test_dof, e),
num_test_dof_1d,
num_test_dof_1d,
nz_dof);
MFEM_FOREACH_THREAD(dz_t, z, nz_dof)
{
MFEM_FOREACH_THREAD_DIRECT(dy_t, y, num_test_dof_1d)
{
MFEM_FOREACH_THREAD_DIRECT(dx_t, x, num_test_dof_1d)
{ Y(dx_t, dy_t, dz_t) = 0.0; }
}
}
MFEM_SYNC_THREAD;
// Accumulate every (output o, test op k, dependent input s,
// trial op m) block of the cached Jacobian into the diagonal via
// the backend driver.
for_constexpr<n_outputs>([&](auto o)
{
using test_fop_t = std::decay_t<decltype(get<o>(outputs))>;
const auto &out_dtq = output_dtq_maps[o];
const int test_op_dim = out_op_dim[static_cast<int>(o)];
// Test-basis factor along a spatial axis
const auto eval_test =
[&](const int k, const int axis, const int q, const int d)
{
const auto &B = out_dtq.B;
const auto &G = out_dtq.G;
if constexpr (is_value_fop<test_fop_t>::value)
{
return (k == 0) ? B(q, 0, d) : 0.0;
}
else if constexpr (is_gradient_fop<test_fop_t>::value)
{
return (k == axis) ? G(q, 0, d) : B(q, 0, d);
}
else
{
return 0.0;
}
};
for (int k = 0; k < test_op_dim; k++)
{
const int row =
out_offsets[static_cast<int>(o)] + vd * test_op_dim + k;
int m_offset = 0;
for_constexpr<n_inputs>([&](auto s)
{
using fop_t = std::decay_t<decltype(get<s>(inputs))>;
const int trial_op_dim =
inputs_trial_op_dim[static_cast<int>(s)];
if (trial_op_dim == 0) { return; }
const auto &in_dtq = input_dtq_maps[s];
const auto eval_input =
[&](const int m, const int axis, const int q,
const int d)
{
if constexpr (is_value_fop<fop_t>::value)
{
return (m == 0) ? in_dtq.B(q, 0, d) : 0.0;
}
else if constexpr (is_gradient_fop<fop_t>::value)
{
return (m == axis) ? in_dtq.G(q, 0, d)
: in_dtq.B(q, 0, d);
}
else
{
return 0.0;
}
};
for (int m = 0; m < trial_op_dim; m++)
{
const int col = m_offset + m;
backend_t::DiagContract(
s_diag,
num_test_dof_1d,
q1d,
nz_dof,
[&](int axis, int q, int d)
{ return eval_test(k, axis, q, d); },
[&](int axis, int q, int d)
{ return eval_input(m, axis, q, d); },
[&](int q) { return qpdc(q, col, vd, row); },
[&](int dx, int dy, int dz, real_t u)
{ Y(dx, dy, dz) += u; });
}
m_offset += trial_op_dim;
});
}
});
}
},
ne,
backend_t::thread_blocks(std::max(q1d, num_test_dof_1d)),
0,
nullptr);
}
using DiagonalKernelType =
decltype(&DerivativeAssembleDiagonal::
derivative_assemble_diagonal_callback<>);
MFEM_REGISTER_KERNELS_HEADER_ONLY(DerivativeAssembleDiagonalLO,
DiagonalKernelType,
(int, int) );
MFEM_REGISTER_KERNELS_HEADER_ONLY(DerivativeAssembleDiagonalHO,
DiagonalKernelType,
(int, int) );
};
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
template<int DIM, int Q1D>
inline typename DerivativeAssembleDiagonal<derivative_id,
qfunc_t,
inputs_t,
outputs_t>::DiagonalKernelType
DerivativeAssembleDiagonal<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeAssembleDiagonalLO::Kernel()
{
static_assert((DIM == 2 || DIM == 3) && Q1D <= 8);
using diag_t =
DerivativeAssembleDiagonal<derivative_id, qfunc_t, inputs_t, outputs_t>;
return diag_t::template derivative_assemble_diagonal_callback<
LocalQFLOBackend<DIM, Q1D>>;
}
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
inline typename DerivativeAssembleDiagonal<derivative_id,
qfunc_t,
inputs_t,
outputs_t>::DiagonalKernelType
DerivativeAssembleDiagonal<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeAssembleDiagonalLO::Fallback(int dim, int q1d)
{
using diag_t =
DerivativeAssembleDiagonal<derivative_id, qfunc_t, inputs_t, outputs_t>;
using DerivativeAssembleDiagonalLO =
typename diag_t::DerivativeAssembleDiagonalLO;
if (dim == 2)
{
return DispatchLOKernelByQ1D<DerivativeAssembleDiagonalLO, 2>(q1d);
}
else if (dim == 3)
{
return DispatchLOKernelByQ1D<DerivativeAssembleDiagonalLO, 3>(q1d);
}
else
{
MFEM_ABORT("Unsupported dimension");
return nullptr;
}
}
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
template<int DIM, int Q1D>
inline typename DerivativeAssembleDiagonal<derivative_id,
qfunc_t,
inputs_t,
outputs_t>::DiagonalKernelType
DerivativeAssembleDiagonal<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeAssembleDiagonalHO::Kernel()
{
using diag_t =
DerivativeAssembleDiagonal<derivative_id, qfunc_t, inputs_t, outputs_t>;
return diag_t::template derivative_assemble_diagonal_callback<
LocalQFHOBackend<DIM>,
Q1D>;
}
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
inline typename DerivativeAssembleDiagonal<derivative_id,
qfunc_t,
inputs_t,
outputs_t>::DiagonalKernelType
DerivativeAssembleDiagonal<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeAssembleDiagonalHO::Fallback(int dim, int q1d)
{
using diag_t =
DerivativeAssembleDiagonal<derivative_id, qfunc_t, inputs_t, outputs_t>;
using DerivativeAssembleDiagonalHO =
typename diag_t::DerivativeAssembleDiagonalHO;
if (dim == 2)
{
return DispatchHOKernelByQ1D<DerivativeAssembleDiagonalHO, 2>(q1d);
}
else if (dim == 3)
{
return DispatchHOKernelByQ1D<DerivativeAssembleDiagonalHO, 3>(q1d);
}
else
{
MFEM_ABORT("Unsupported dimension");
return nullptr;
}
}
} // namespace mfem::future::LocalQFImpl
@@ -0,0 +1,600 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../../integrator_ctx.hpp"
#include "kernels.hpp"
#include "util.hpp"
#include <array>
namespace mfem::future::LocalQFImpl
{
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
class DerivativeSetup
{
static constexpr auto inout_tuple =
merge_mfem_tuples_as_empty_std_tuple(inputs_t {}, outputs_t{});
static constexpr auto filtered_inout_tuple = filter_fields(inout_tuple);
static constexpr size_t nfields =
count_unique_field_ids(filtered_inout_tuple);
using qf_signature = typename get_function_signature<qfunc_t>::type;
using qf_param_ts = typename qf_signature::parameter_ts;
using args_tuple_t = decay_tuple<qf_param_ts>;
static constexpr std::size_t n_inputs = tuple_size<inputs_t>::value;
static constexpr std::size_t n_outputs = tuple_size<outputs_t>::value;
static_assert(n_inputs + n_outputs == tuple_size<qf_param_ts>::value,
"LocalQF: q-function arity must match inputs + outputs");
qfunc_t qfunc;
const inputs_t inputs;
const outputs_t outputs;
const IntegratorContext ctx;
Vector &qp_cache;
const std::vector<const DofToQuad *> dtqs;
// inputs: dtq, idx, B, G, d1d, q1d, vdim
const std::array<DofToQuadMap, n_inputs> input_dtq;
const std::array<size_t, n_inputs> input_idx;
const std::array<const real_t *, n_inputs> input_B, input_G;
const std::array<int, n_inputs> input_d1d, input_q1d, input_vdim;
// Jacobian cache metadata
const std::array<bool, n_inputs> input_is_dependent;
const std::array<int, n_inputs> input_size_on_qp;
const std::array<int, n_outputs> out_vdim;
const std::array<int, n_outputs> out_op_dim;
const std::array<int, n_outputs> out_offsets;
const int output_size_on_qp;
const int trial_vdim;
const int total_trial_op_dim;
const int residual_size_on_qp;
// other constants
const int dim, ne, nq, q1d;
public:
//////////////////////////////////////////////////////////////////
DerivativeSetup() = delete;
DerivativeSetup(IntegratorContext ctx,
qfunc_t qfunc,
inputs_t inputs,
outputs_t outputs,
Vector &qp_cache):
qfunc(std::move(qfunc)), inputs(inputs), outputs(outputs), ctx(ctx),
qp_cache(qp_cache), dtqs(make_dtqs(ctx)),
input_dtq(create_dtq_maps<Entity::Element>(
inputs,
dtqs,
create_union_field_map_for_dtq(ctx, inputs),
ctx.unionfds,
ctx.ir)),
input_idx(create_input_vector_map(ctx, inputs)),
input_B(get_B(input_dtq)), input_G(get_G(input_dtq)),
input_d1d(get_D1D(input_dtq)), input_q1d(get_Q1D(input_dtq)),
input_vdim(get_vdim(inputs)),
input_is_dependent(compute_input_is_dependent(inputs, derivative_id)),
input_size_on_qp(
get_input_size_on_qp(inputs, std::make_index_sequence<n_inputs> {})),
out_vdim(get_vdim(outputs)), out_op_dim(compute_out_op_dim(outputs)),
out_offsets(compute_out_offsets(out_vdim, out_op_dim)), output_size_on_qp(
[&]
{
int s = 0;
for_constexpr<n_outputs>([&](auto o)
{ s += get<o>(outputs).size_on_qp; });
return s;
}()),
trial_vdim(compute_trial_vdim(inputs, derivative_id)),
total_trial_op_dim(compute_total_trial_op_dim(
inputs, input_is_dependent, input_size_on_qp)),
residual_size_on_qp(output_size_on_qp * trial_vdim * total_trial_op_dim),
dim(ctx.mesh.Dimension()), ne(ctx.nentities), nq(ctx.ir.GetNPoints()),
q1d(tensor_1d_size(nq, dim))
{
MFEM_ASSERT(ctx.unionfds.size() == nfields,
"LocalQFBackend: unionfds size mismatch");
qp_cache.SetSize(ne * nq * residual_size_on_qp);
qp_cache.UseDevice(true);
}
//////////////////////////////////////////////////////////////////
void operator()(const std::vector<Vector *> &xe)
{
if (ctx.attr.Size() == 0) { return; }
// Quadrature index is fastest-varying so that adjacent threads (one per
// quadrature point) touch adjacent addresses.
auto cache_tensor = DeviceTensor<3, real_t>(
qp_cache.ReadWrite(), nq, residual_size_on_qp, ne);
if (q1d <= LocalQFLOBackendMQ1())
{
run_kernels<DerivativeSetupLO>(xe, cache_tensor);
}
else if (q1d <= LocalQFHOBackendMQ1())
{
run_kernels<DerivativeSetupHO>(xe, cache_tensor);
}
else
{
MFEM_ABORT("Unsupported quadrature order for LocalQF backend");
}
}
//////////////////////////////////////////////////////////////////
template<typename Backend>
void run_kernels(const std::vector<Vector *> &xe,
DeviceTensor<3, real_t> &cache_tensor)
{
Backend::Run(dim,
q1d,
ctx,
qfunc,
// inputs
input_idx,
input_B,
input_G,
input_vdim,
input_d1d,
input_q1d,
input_size_on_qp,
input_is_dependent,
// outputs / cache metadata
out_vdim,
out_op_dim,
out_offsets,
trial_vdim,
total_trial_op_dim,
residual_size_on_qp,
// vectors
xe,
cache_tensor,
// fallback arguments
dim,
q1d);
}
//////////////////////////////////////////////////////////////////
/// Zeroes the q-function *output* slots of an argument tuple.
///
/// The argument tuple is built once per quadrature point and reused for
/// every trial seed. The q-function writes through its output parameters,
/// so those slots have to be restored before each call to give every seed
/// the same starting state a freshly value-initialized tuple would.
static MFEM_HOST_DEVICE inline void reset_output_args(args_tuple_t &args)
{
for_constexpr<n_outputs>([&](auto oc)
{
constexpr size_t ao = n_inputs + oc.value;
auto &oarg = get<ao>(args);
oarg = std::remove_reference_t<decltype(oarg)> {};
});
}
//////////////////////////////////////////////////////////////////
template<typename backend_t = LocalQFLOBackend<3>, int T_Q1D = 0>
static void
derivative_setup_callback(const IntegratorContext &ctx,
qfunc_t &qfunc,
// inputs: idx, B, G, vdim, d1d, q1d
const std::array<size_t, n_inputs> &in_idx,
const std::array<const real_t *, n_inputs> in_B,
const std::array<const real_t *, n_inputs> in_G,
const std::array<int, n_inputs> &in_vdim,
const std::array<int, n_inputs> &in_d1d,
const std::array<int, n_inputs> &in_q1d,
const std::array<int, n_inputs> &in_size_on_qp,
const std::array<bool, n_inputs> &input_dep,
// outputs / cache metadata
const std::array<int, n_outputs> &out_vdim,
const std::array<int, n_outputs> &out_op_dim,
const std::array<int, n_outputs> &out_offsets,
const int trial_vdim,
const int total_trial_op_dim,
const int residual_size_on_qp,
const std::vector<Vector *> &xe,
DeviceTensor<3, real_t> &cache_tensor,
// fallback arguments
const int dim,
const int q1d)
{
MFEM_VERIFY(dim == ctx.mesh.Dimension(), "Dimension mismatch");
if (ctx.attr.Size() == 0) { return; }
static constexpr auto B2D = backend_t::DIM == 2;
static constexpr auto MQ1 = T_Q1D ? T_Q1D : backend_t::MQ1;
static constexpr auto MTPB = backend_t::MAX_THREADS_PER_BLOCK();
const int ne = ctx.nentities;
MFEM_CONTRACT_VAR(residual_size_on_qp);
constexpr auto k_dim = [](const int k) { return k * k * (B2D ? 1 : k); };
// --------------------------------------------------
// INPUTS: XE, 3(max DIM) + 1(VDIM) + 1(number of elements)
// --------------------------------------------------
std::array<DeviceTensor<3 + 1 + 1, const real_t>, n_inputs> in_XE;
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
const size_t k = in_idx[i];
const int d = in_d1d[i], q = in_q1d[i], v = in_vdim[i];
using FOP = tuple_element_t<i, inputs_t>;
if constexpr (is_value_fop_v<FOP> || is_gradient_fop_v<FOP>)
{
MFEM_VERIFY(xe[k]->Size() == k_dim(d) * v * ne, "Size mismatch");
in_XE[i] = Reshape(xe[k]->Read(), d, d, B2D ? 1 : d, v, ne);
}
else if constexpr (is_identity_fop_v<FOP>)
{
MFEM_VERIFY(xe[k]->Size() == k_dim(q) * v * ne, "Size mismatch");
in_XE[i] = Reshape(xe[k]->Read(), v, q, q, B2D ? 1 : q, ne);
}
else if constexpr (is_weight_fop_v<FOP>)
{
MFEM_VERIFY(ctx.ir.GetNPoints() == k_dim(q1d),
"tensor-product IR expected");
in_XE[i] = Reshape(
ctx.ir.GetWeights().Read(), q1d, q1d, B2D ? 1 : q1d, 1, 1);
}
else
{
static_assert(false, "Unsupported");
}
});
const auto d_attr = ctx.attr.Read();
const bool has_attr = ctx.attr.Size() > 0;
const auto d_elem_attr = ctx.elem_attr->Read();
dfem::forall<MTPB>(
[=] MFEM_HOST_DEVICE(const int e, void *)
{
if (has_attr && !d_attr[d_elem_attr[e] - 1]) { return; }
// -----------------------------------------------
// Inputs argument registers + shared memory
// -----------------------------------------------
input_args_reg_t<backend_t, qfunc_t, inputs_t, outputs_t, MQ1> rargs;
MFEM_SHARED typename backend_t::Shared smem;
// -----------------------------------------------
// Load primal inputs (rargs) once for this element
// -----------------------------------------------
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
const auto &XE = in_XE[i];
const int d = in_d1d[i], q = in_q1d[i], Q1D = q1d;
const real_t *B = in_B[i], *G = in_G[i];
auto &rarg = get<i>(rargs);
using XE_t = decltype(XE);
using rarg_t = decltype(rarg);
using FOP = tuple_element_t<i, inputs_t>;
if constexpr (is_value_fop<FOP>::value)
{
backend_t::template LoadValue<rarg_t, XE_t>(
smem, e, d, q, Q1D, B, XE, rarg);
}
else if constexpr (is_gradient_fop_v<FOP>)
{
constexpr auto RNK = qf_param_slot<qfunc_t, i>::extents.size();
using FieldParamT =
typename qf_param_slot<qfunc_t, i>::qf_decay_param_t;
backend_t::template LoadGradient<RNK, rarg_t, XE_t, FieldParamT>(
smem, e, d, q, q1d, B, G, XE, rarg);
}
else if constexpr (is_weight_fop_v<FOP> || is_identity_fop_v<FOP>)
{
// qp values are read directly from in_XE / IR
}
else
{
static_assert(false, "Unsupported");
}
});
MFEM_SYNC_THREAD;
// -----------------------------------------------
// Build the primal arguments once per quadrature point, then, for
// each trial seed (j, dependent input s, m), differentiate the
// q-function with a unit tangent and store the result row in the
// cache. Nothing in the primal pull depends on the seed, so the
// thread loop is the outermost one here. The seed loops only touch
// per-thread state, hence no barrier inside them.
// Warning: no 'DIRECT' on the 'Z' direction,
// as one backend may need to iterate over it.
// -----------------------------------------------
MFEM_FOREACH_THREAD(qz, z, (B2D ? 1 : q1d))
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
const int q = qx + q1d * (qy + q1d * qz);
#ifdef MFEM_USE_ENZYME
args_tuple_t primal_args {};
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
auto &parg = get<i>(primal_args);
const auto &XE = in_XE[i];
using FOP = tuple_element_t<i, inputs_t>;
using ARG =
typename qf_param_slot<qfunc_t, i>::qf_reg_param_t;
if constexpr (is_identity_fop_v<FOP>)
{
parg = as_tensor<ARG>(&XE(0, qx, qy, qz, e));
}
else if constexpr (is_weight_fop_v<FOP>)
{
parg = XE(qx, qy, qz, 0, 0);
}
else if constexpr (is_value_fop_v<FOP> ||
is_gradient_fop_v<FOP>)
{
parg = backend_t::template qp_pull<ARG>(
get<i>(rargs), qx, qy, qz);
}
else
{
static_assert(false, "Unsupported");
}
});
for (int j = 0; j < trial_vdim; j++)
{
int m_offset = 0;
for_constexpr<n_inputs>([&](auto sc)
{
constexpr size_t s = sc.value;
if (!input_dep[s]) { return; }
const int vdim_s = in_vdim[s];
const int op_dim_s = in_size_on_qp[s] / vdim_s;
for (int m = 0; m < op_dim_s; m++)
{
const int col_m = m + m_offset;
// Enzyme writes through the output slots of the
// primal tuple, so they are reset per seed.
reset_output_args(primal_args);
args_tuple_t shadow_args {};
qf_set_value_at(get<s>(shadow_args), j, m, 1.0);
call_enzyme_fwddiff(qfunc, primal_args, shadow_args);
for_constexpr<n_outputs>([&](auto oc)
{
constexpr size_t o = oc.value, ao = n_inputs + o;
const auto &tangent = get<ao>(shadow_args);
const int tv = out_vdim[o], to = out_op_dim[o];
for (int i = 0; i < tv; i++)
{
for (int k = 0; k < to; k++)
{
const int row = out_offsets[o] + i * to + k;
const int cache_idx =
row * trial_vdim * total_trial_op_dim +
j * total_trial_op_dim + col_m;
cache_tensor(q, cache_idx, e) =
qf_value_at(tangent, i, k);
}
}
});
}
m_offset += op_dim_s;
});
}
#else // MFEM_USE_ENZYME
args_tuple_t qargs {};
for_constexpr<n_inputs>([&](auto ic)
{
constexpr size_t i = ic.value;
auto &qarg = get<i>(qargs);
const auto &XE = in_XE[i];
using FOP = tuple_element_t<i, inputs_t>;
using ARG =
typename qf_param_slot<qfunc_t, i>::qf_reg_param_t;
if constexpr (is_identity_fop_v<FOP>)
{
using DT =
typename qf_param_slot<qfunc_t, i>::qf_decay_param_t;
if constexpr (qf_param_uses_dual_v<DT>)
{
qarg = backend_t::template identity_qp_pull_dual<DT>(
false, XE, XE, qx, qy, qz, e);
}
else
{
qarg = as_tensor<ARG>(&XE(0, qx, qy, qz, e));
}
}
else if constexpr (is_weight_fop_v<FOP>)
{
qarg = XE(qx, qy, qz, 0, 0);
}
else if constexpr (is_value_fop_v<FOP> ||
is_gradient_fop_v<FOP>)
{
qarg = backend_t::template qp_pull<ARG>(
get<i>(rargs), qx, qy, qz);
}
else
{
static_assert(false, "Unsupported");
}
});
for (int j = 0; j < trial_vdim; j++)
{
int m_offset = 0;
for_constexpr<n_inputs>([&](auto sc)
{
constexpr size_t s = sc.value;
if (!input_dep[s]) { return; }
const int vdim_s = in_vdim[s];
const int op_dim_s = in_size_on_qp[s] / vdim_s;
for (int m = 0; m < op_dim_s; m++)
{
const int col_m = m + m_offset;
// The q-function writes through the output slots,
// so they are reset per seed.
reset_output_args(qargs);
qf_set_gradient_at(get<s>(qargs), j, m, 1.0);
call_qfunc_no_move(qfunc, qargs);
for_constexpr<n_outputs>([&](auto oc)
{
constexpr size_t o = oc.value, ao = n_inputs + o;
const auto &tangent = get<ao>(qargs);
const int tv = out_vdim[o], to = out_op_dim[o];
for (int i = 0; i < tv; i++)
{
for (int k = 0; k < to; k++)
{
const int row = out_offsets[o] + i * to + k;
const int cache_idx =
row * trial_vdim * total_trial_op_dim +
j * total_trial_op_dim + col_m;
cache_tensor(q, cache_idx, e) =
qf_gradient_at(tangent, i, k);
}
}
});
// Clear the seed so the next direction starts from
// the pristine (zero-tangent) primal state.
qf_set_gradient_at(get<s>(qargs), j, m, 0.0);
}
m_offset += op_dim_s;
});
}
#endif // MFEM_USE_ENZYME
}
}
}
},
ne,
backend_t::thread_blocks(
compute_kernel_thread_1d<inputs_t>(q1d, in_d1d)),
0,
nullptr);
}
using SetupKernelType =
decltype(&DerivativeSetup::derivative_setup_callback<>);
MFEM_REGISTER_KERNELS_HEADER_ONLY(DerivativeSetupLO,
SetupKernelType,
(int, int) );
MFEM_REGISTER_KERNELS_HEADER_ONLY(DerivativeSetupHO,
SetupKernelType,
(int, int) );
};
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
template<int DIM, int Q1D>
inline typename DerivativeSetup<derivative_id, qfunc_t, inputs_t, outputs_t>::
SetupKernelType
DerivativeSetup<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeSetupLO::Kernel()
{
static_assert((DIM == 2 || DIM == 3) && Q1D <= 8);
using setup_t = DerivativeSetup<derivative_id, qfunc_t, inputs_t, outputs_t>;
return setup_t::template derivative_setup_callback<
LocalQFLOBackend<DIM, Q1D>>;
}
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
inline typename DerivativeSetup<derivative_id, qfunc_t, inputs_t, outputs_t>::
SetupKernelType
DerivativeSetup<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeSetupLO::Fallback(int dim, int q1d)
{
using setup_t = DerivativeSetup<derivative_id, qfunc_t, inputs_t, outputs_t>;
using DerivativeSetupLO = typename setup_t::DerivativeSetupLO;
if (dim == 2)
{
return DispatchLOKernelByQ1D<DerivativeSetupLO, 2>(q1d);
}
else if (dim == 3)
{
return DispatchLOKernelByQ1D<DerivativeSetupLO, 3>(q1d);
}
else
{
MFEM_ABORT("Unsupported dimension");
return nullptr;
}
}
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
template<int DIM, int Q1D>
inline typename DerivativeSetup<derivative_id, qfunc_t, inputs_t, outputs_t>::
SetupKernelType
DerivativeSetup<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeSetupHO::Kernel()
{
using setup_t = DerivativeSetup<derivative_id, qfunc_t, inputs_t, outputs_t>;
return setup_t::template derivative_setup_callback<LocalQFHOBackend<DIM>,
Q1D>;
}
template<int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
inline typename DerivativeSetup<derivative_id, qfunc_t, inputs_t, outputs_t>::
SetupKernelType
DerivativeSetup<derivative_id, qfunc_t, inputs_t, outputs_t>::
DerivativeSetupHO::Fallback(int dim, int q1d)
{
using setup_t = DerivativeSetup<derivative_id, qfunc_t, inputs_t, outputs_t>;
using DerivativeSetupHO = typename setup_t::DerivativeSetupHO;
if (dim == 2)
{
return DispatchHOKernelByQ1D<DerivativeSetupHO, 2>(q1d);
}
else if (dim == 3)
{
return DispatchHOKernelByQ1D<DerivativeSetupHO, 3>(q1d);
}
else
{
MFEM_ABORT("Unsupported dimension");
return nullptr;
}
}
} // namespace mfem::future::LocalQFImpl
@@ -0,0 +1,274 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../util.hpp"
#ifdef MFEM_USE_ENZYME
namespace mfem::future
{
template <typename T> struct function_traits;
template <typename R, typename C, typename... Args>
struct function_traits<R (C::*)(Args...) const>
{
using primal_return_type = R;
using args_tuple = std::tuple<Args...>;
static constexpr size_t arity = sizeof...(Args);
};
// Component count and writable counterpart of a per-point argument, which
// is either a tensor or a plain scalar.
template <typename Arg> struct qp_traits
{
static_assert(std::is_arithmetic_v<Arg>,
"per-point arguments must be tensors or scalars");
using view_type = Arg;
static constexpr int components = 1;
};
template <typename T, int... Sizes> struct qp_traits<tensor<T, Sizes...>>
{
using view_type = tensor<std::remove_const_t<T>, Sizes...>;
static constexpr int components = (Sizes * ... * 1);
};
// Generic FwdDiff: computes the full gradient of a pointwise qfunction at a
// single quadrature point.
//
// active_input is the index of the argument to differentiate with respect
// to; active_output is the index of the (scalar) output argument whose
// derivative is taken.
//
// operator()(args...) takes the qfunction's arguments, except that the
// active output position receives the *gradient*, shaped like the active
// input (d(output)/d(input component)).
//
// Per input component d, one enzyme fwddiff call with the one-hot seed e_d
// in the input tangent yields gradient entry d, i.e. grad_components enzyme
// calls per point. The output tangent is not pre-zeroed, so the qfunction
// must fully write its output (tangent stores overwrite).
//
// operator() is MFEM_HOST_DEVICE, stateless and allocation-free, so it is
// callable inside a GPU kernel: seed, primal scratch and tangent all live
// on the stack.
template <typename Func, size_t active_input, size_t active_output>
struct FwdDiff
{
using traits = function_traits<decltype(&Func::operator())>;
using args_tuple = typename traits::args_tuple;
static constexpr size_t arity = traits::arity;
static_assert(std::is_void_v<typename traits::primal_return_type>,
"FwdDiff only supports primal functions with void return type");
static_assert(active_input < arity && active_output < arity,
"active argument indices must be within the function arity");
static_assert(active_input != active_output,
"active input and output must be different arguments");
using input_type =
std::decay_t<std::tuple_element_t<active_input, args_tuple>>;
using output_type =
std::decay_t<std::tuple_element_t<active_output, args_tuple>>;
using grad_type = typename qp_traits<input_type>::view_type;
using output_view = typename qp_traits<output_type>::view_type;
static constexpr int grad_components = qp_traits<input_type>::components;
static_assert(qp_traits<output_type>::components == 1,
"gradient output requires a scalar output");
// Signature of the differentiated qfunction: the primal arguments, with
// the Active output slot receiving the (writable) gradient instead.
// Exposed through create_function_signature below so that
// DifferentiableOperator can deduce the parameter types, which it cannot
// do from the variadic operator().
template <size_t I>
using qf_arg_t = std::conditional_t<I == active_output, grad_type &,
std::tuple_element_t<I, args_tuple>>;
template <size_t... Is>
static FunctionSignature<void(qf_arg_t<Is>...)>
signature_impl(std::index_sequence<Is...>);
using signature =
decltype(signature_impl(std::make_index_sequence<arity> {}));
// d-th scalar of a per-point argument in flat row-major order, regardless
// of rank, built on the native operator[] (tensor has no flat-index
// accessor; flatten() returns a copy, so it cannot be written through).
MFEM_HOST_DEVICE static double &component(double &t, int) { return t; }
template <typename T, int n0, int... n>
MFEM_HOST_DEVICE static T &component(tensor<T, n0, n...> &t, int d)
{
if constexpr (sizeof...(n) == 0)
{
return t[d];
}
else
{
constexpr int stride = (n * ... * 1);
return component(t[d / stride], d % stride);
}
}
// Plain function with the qfunction's exact (reference) signature, so it
// can be handed to Enzyme as a function pointer; references are pointers
// to Enzyme, so primal arguments and shadows are passed by address below.
template <size_t... Is>
MFEM_HOST_DEVICE static void
static_call(std::tuple_element_t<Is, args_tuple>... args)
{
Func{}(args...);
}
template <size_t... Is>
static constexpr auto fn_ptr(std::index_sequence<Is...>)
{
return &static_call<Is...>;
}
static constexpr auto fn = fn_ptr(std::make_index_sequence<arity> {});
// Writable, zero-initialized scratch with the shape of argument I, used
// as its enzyme shadow.
template <size_t I>
using shadow_t = typename qp_traits<
std::decay_t<std::tuple_element_t<I, args_tuple>>>::view_type;
template <size_t... Is>
MFEM_HOST_DEVICE static auto make_shadows(std::index_sequence<Is...>)
{
return mfem::future::make_tuple(shadow_t<Is> {}...);
}
template <typename Shadows, size_t... Is>
MFEM_HOST_DEVICE static auto make_shadow_ptrs(Shadows &shadows,
std::index_sequence<Is...>)
{
return mfem::future::make_tuple(&mfem::future::get<int(Is)>(shadows)...);
}
// The caller's argument pointers, except the active output slot, which
// points to scalar scratch: the caller's slot holds the gradient, while
// the primal function writes its scalar output there.
template <size_t I, typename Ptrs>
MFEM_HOST_DEVICE static auto primal_ptr(Ptrs &ptrs, output_view &primal)
{
if constexpr (I == active_output) { return &primal; }
else { return mfem::future::get<int(I)>(ptrs); }
}
template <typename Ptrs, size_t... Is>
MFEM_HOST_DEVICE static auto make_primal_ptrs(Ptrs &ptrs,
output_view &primal,
std::index_sequence<Is...>)
{
return mfem::future::make_tuple(primal_ptr<Is>(ptrs, primal)...);
}
// Single flat enzyme call. The activity markers must appear directly in
// the __enzyme_fwddiff argument list — Enzyme cannot trace markers that
// were forwarded through function parameters (e.g. at -O0, where nothing
// is inlined). Every argument is therefore enzyme_dup'd in one sticky
// group; Const arguments simply carry a zero tangent, which is equivalent
// to marking them enzyme_const.
//
// always_inline is load-bearing: when FwdDiff is itself differentiated
// (second derivatives, forward-over-forward), Enzyme only recognizes this
// nested __enzyme_fwddiff call if it sits at most one call level below
// the function handed to the outer __enzyme_fwddiff. Without inlining
// (-O0) it sits two levels down (wrapper -> operator() -> call_enzyme)
// and the outer pass treats it as a regular call: the activity marker
// ints then receive undef shadows, which misaligns the argument pairing
// (observed as "cannot compute with global variable that doesn't have
// marked shadow global" at compile time or null-shadow segfaults at
// runtime). The always-inliner runs even at -O0, hoisting this call into
// operator() where the nested handling applies.
template <typename PrimalPtrs, typename ShadowPtrs, size_t... Is>
__attribute__((always_inline))
MFEM_HOST_DEVICE static void call_enzyme(PrimalPtrs &primal_ptrs,
ShadowPtrs &shadow_ptrs,
std::index_sequence<Is...>)
{
__enzyme_fwddiff<void>(fn, enzyme_dup,
mfem::future::get<int(Is)>(primal_ptrs)...,
enzyme_interleave,
mfem::future::get<int(Is)>(shadow_ptrs)...,
enzyme_runtime_activity);
}
template <typename... Args>
MFEM_HOST_DEVICE void operator()(Args &&...args) const
{
static_assert(sizeof...(Args) == arity, "Wrong number of arguments");
auto ptrs = mfem::future::make_tuple(&args...);
auto &grad = *mfem::future::get<int(active_output)>(ptrs);
static_assert(std::is_same_v<std::decay_t<decltype(grad)>, grad_type>,
"gradient argument must be shaped like the Active input "
"(with writable scalars)");
constexpr auto seq = std::make_index_sequence<arity> {};
output_view primal{};
auto primal_ptrs = make_primal_ptrs(ptrs, primal, seq);
auto shadows = make_shadows(seq);
auto shadow_ptrs = make_shadow_ptrs(shadows, seq);
auto &seed = mfem::future::get<int(active_input)>(shadows);
auto &tangent = mfem::future::get<int(active_output)>(shadows);
// One enzyme call per input component d: seed e_d in the input tangent
// and read gradient entry d off the output tangent.
for (int d = 0; d < grad_components; d++)
{
component(seed, d) = 1.0;
call_enzyme(primal_ptrs, shadow_ptrs, seq);
component(grad, d) = component(tangent, 0);
component(seed, d) = 0.0;
}
}
static void print() { print_impl(std::make_index_sequence<arity> {}); }
template <size_t... Is> static void print_impl(std::index_sequence<Is...>)
{
mfem::out << "for d in [0, " << grad_components
<< "): __enzyme_fwddiff<void>(fptr, enzyme_dup";
((mfem::out << ", "
<< get_type_name<std::tuple_element_t<Is, args_tuple>>()),
...);
mfem::out << ", enzyme_interleave";
(([&]
{
if constexpr (Is == active_input) { mfem::out << ", e_d seed"; }
else if constexpr (Is == active_output) { mfem::out << ", tangent out"; }
else { mfem::out << ", zero tangent"; }
}()),
...);
mfem::out << ")\n";
}
};
template <typename Func, size_t active_input, size_t active_output>
struct create_function_signature<FwdDiff<Func, active_input, active_output>>
{
using type =
typename FwdDiff<Func, active_input, active_output>::signature;
};
} // namespace mfem::future
#endif // MFEM_USE_ENZYME
+83
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@@ -0,0 +1,83 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
// Explicit instantiation of the local Q-function backend device code
#include "../../../../config/config.hpp"
#ifdef MFEM_USE_MPI
#include "kernels.hpp"
namespace mfem::future
{
// ────────────────────────────────────────────────────────────────────────────
// Low-order backends instantiations for (DIM, Q1D)
// ────────────────────────────────────────────────────────────────────────────
template struct lo_ker_backend<2, 2>;
template struct lo_ker_backend<2, 3>;
template struct lo_ker_backend<2, 4>;
template struct lo_ker_backend<2, 5>;
template struct lo_ker_backend<2, 6>;
template struct lo_ker_backend<2, 7>;
template struct lo_ker_backend<2, 8>;
template struct lo_ker_backend<3, 2>;
template struct lo_ker_backend<3, 3>;
template struct lo_ker_backend<3, 4>;
template struct lo_ker_backend<3, 5>;
template struct lo_ker_backend<3, 6>;
template struct lo_ker_backend<3, 7>;
template struct lo_ker_backend<3, 8>;
template struct LocalQFLOBackend<2, 2>;
template struct LocalQFLOBackend<2, 3>;
template struct LocalQFLOBackend<2, 4>;
template struct LocalQFLOBackend<2, 5>;
template struct LocalQFLOBackend<2, 6>;
template struct LocalQFLOBackend<2, 7>;
template struct LocalQFLOBackend<2, 8>;
template struct LocalQFLOBackend<3, 2>;
template struct LocalQFLOBackend<3, 3>;
template struct LocalQFLOBackend<3, 4>;
template struct LocalQFLOBackend<3, 5>;
template struct LocalQFLOBackend<3, 6>;
template struct LocalQFLOBackend<3, 7>;
template struct LocalQFLOBackend<3, 8>;
// ────────────────────────────────────────────────────────────────────────────
// High-order backends instantiations for (DIM, Q1D)
// ────────────────────────────────────────────────────────────────────────────
template struct ho_ker_backend<2, 8>;
template struct ho_ker_backend<2, 10>;
template struct ho_ker_backend<2, 12>;
template struct ho_ker_backend<2, 16>;
template struct ho_ker_backend<3, 8>;
template struct ho_ker_backend<3, 10>;
template struct ho_ker_backend<3, 12>;
template struct ho_ker_backend<3, 16>;
template struct LocalQFHOBackend<2, 8>;
template struct LocalQFHOBackend<2, 10>;
template struct LocalQFHOBackend<2, 12>;
template struct LocalQFHOBackend<2, 16>;
template struct LocalQFHOBackend<3, 8>;
template struct LocalQFHOBackend<3, 10>;
template struct LocalQFHOBackend<3, 12>;
template struct LocalQFHOBackend<3, 16>;
} // namespace mfem::future
#endif // MFEM_USE_MPI
+77
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// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "kernels_lo.hpp" // IWYU pragma: export
#include "kernels_ho.hpp" // IWYU pragma: export
namespace mfem::future
{
// ────────────────────────────────────────────────────────────────────────────
// Low-order backends instantiations for (DIM, Q1D)
// ────────────────────────────────────────────────────────────────────────────
extern template struct lo_ker_backend<2, 2>;
extern template struct lo_ker_backend<2, 3>;
extern template struct lo_ker_backend<2, 4>;
extern template struct lo_ker_backend<2, 5>;
extern template struct lo_ker_backend<2, 6>;
extern template struct lo_ker_backend<2, 7>;
extern template struct lo_ker_backend<2, 8>;
extern template struct lo_ker_backend<3, 2>;
extern template struct lo_ker_backend<3, 3>;
extern template struct lo_ker_backend<3, 4>;
extern template struct lo_ker_backend<3, 5>;
extern template struct lo_ker_backend<3, 6>;
extern template struct lo_ker_backend<3, 7>;
extern template struct lo_ker_backend<3, 8>;
extern template struct LocalQFLOBackend<2, 2>;
extern template struct LocalQFLOBackend<2, 3>;
extern template struct LocalQFLOBackend<2, 4>;
extern template struct LocalQFLOBackend<2, 5>;
extern template struct LocalQFLOBackend<2, 6>;
extern template struct LocalQFLOBackend<2, 7>;
extern template struct LocalQFLOBackend<2, 8>;
extern template struct LocalQFLOBackend<3, 2>;
extern template struct LocalQFLOBackend<3, 3>;
extern template struct LocalQFLOBackend<3, 4>;
extern template struct LocalQFLOBackend<3, 5>;
extern template struct LocalQFLOBackend<3, 6>;
extern template struct LocalQFLOBackend<3, 7>;
extern template struct LocalQFLOBackend<3, 8>;
// ────────────────────────────────────────────────────────────────────────────
// High-order backends instantiations for (DIM, Q1D)
// ────────────────────────────────────────────────────────────────────────────
extern template struct ho_ker_backend<2, 8>;
extern template struct ho_ker_backend<2, 10>;
extern template struct ho_ker_backend<2, 12>;
extern template struct ho_ker_backend<2, 16>;
extern template struct ho_ker_backend<3, 8>;
extern template struct ho_ker_backend<3, 10>;
extern template struct ho_ker_backend<3, 12>;
extern template struct ho_ker_backend<3, 16>;
extern template struct LocalQFHOBackend<2, 8>;
extern template struct LocalQFHOBackend<2, 10>;
extern template struct LocalQFHOBackend<2, 12>;
extern template struct LocalQFHOBackend<2, 16>;
extern template struct LocalQFHOBackend<3, 8>;
extern template struct LocalQFHOBackend<3, 10>;
extern template struct LocalQFHOBackend<3, 12>;
extern template struct LocalQFHOBackend<3, 16>;
} // namespace mfem::future
+803
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@@ -0,0 +1,803 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../../../kernels.hpp"
namespace ker = mfem::kernels::internal;
#include "../../util.hpp" // for ThreadBlocks
#include "util.hpp"
namespace mfem::future
{
// ────────────────────────────────────────────────────────────────────────────
inline constexpr int LocalQFHOBackendMQ1() { return 16; }
// ────────────────────────────────────────────────────────────────────────────
/// Register type for one HO q-function parameter
template<typename KerOps, typename T, int rank = qf_param_shape<T>::rank>
struct ho_qreg;
template<typename KerOps, typename T>
struct ho_qreg<KerOps, T, 0>
{
using type = typename KerOps::template val_reg_t<1>;
};
template<typename KerOps, typename T>
struct ho_qreg<KerOps, T, 1>
{
static constexpr int e0 = qf_param_shape<T>::extents[0];
using type = typename KerOps::template val_reg_t<e0>;
};
template<typename KerOps, typename T>
struct ho_qreg<KerOps, T, 2>
{
static constexpr int VDIM = qf_param_shape<T>::extents[0];
static constexpr int SDIM = qf_param_shape<T>::extents[1];
using type = typename KerOps::template del_reg_t<VDIM, SDIM>;
};
template<typename KerOps, typename T>
using ho_qreg_t = typename ho_qreg<KerOps, T>::type;
// ────────────────────────────────────────────────────────────────────────────
namespace hok
{
/// Load one quadrature-point value
template<int DIM, typename T, typename Reg>
MFEM_HOST_DEVICE inline auto load_at(Reg &reg, int qx, int qy, int qz)
{
static_assert(DIM == 2 || DIM == 3);
constexpr int RNK = qf_param_shape<T>::rank;
if constexpr (DIM == 2)
{
MFEM_CONTRACT_VAR(qz);
if constexpr (RNK == 0) { return T{ reg(0, qy, qx) }; }
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<T>::extents[0];
T t{};
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd) { t(dd) = reg(dd, qy, qx); }
return t;
}
else
{
constexpr int e0 = qf_param_shape<T>::extents[0];
constexpr int e1 = qf_param_shape<T>::extents[1];
T t;
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j) { t(i, j) = reg(i, j, qy, qx); }
}
return t;
}
}
else
{
if constexpr (RNK == 0) { return T{ reg(0, qz, qy, qx) }; }
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<T>::extents[0];
T t{};
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd) { t(dd) = reg(dd, qz, qy, qx); }
return t;
}
else
{
constexpr int e0 = qf_param_shape<T>::extents[0];
constexpr int e1 = qf_param_shape<T>::extents[1];
T t;
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j) { t(i, j) = reg(i, j, qz, qy, qx); }
}
return t;
}
}
}
template<bool tangent, typename U>
MFEM_HOST_DEVICE inline auto qp_store(const U &v)
{
if constexpr (tangent) { return qf_store_gradient(v); }
else
{
return qf_store_value(v);
}
}
// Store primal value or dual tangent at one quadrature point
template<int DIM, typename T, typename Reg, bool tangent>
MFEM_HOST_DEVICE inline void
store_at(Reg &reg, int qx, int qy, int qz, const T &out)
{
static_assert(DIM == 2 || DIM == 3);
constexpr int RNK = qf_param_shape<T>::rank;
if constexpr (DIM == 2)
{
MFEM_CONTRACT_VAR(qz);
if constexpr (RNK == 0) { reg(0, qy, qx) = qp_store<tangent>(out); }
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<T>::extents[0];
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd)
{
reg(dd, qy, qx) = qp_store<tangent>(out(dd));
}
}
else
{
constexpr int e0 = qf_param_shape<T>::extents[0];
constexpr int e1 = qf_param_shape<T>::extents[1];
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j)
{
reg(i, j, qy, qx) = qp_store<tangent>(out(i, j));
}
}
}
}
else
{
if constexpr (RNK == 0) { reg(0, qz, qy, qx) = qp_store<tangent>(out); }
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<T>::extents[0];
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd)
{
reg(dd, qz, qy, qx) = qp_store<tangent>(out(dd));
}
}
else
{
constexpr int e0 = qf_param_shape<T>::extents[0];
constexpr int e1 = qf_param_shape<T>::extents[1];
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j)
{
reg(i, j, qz, qy, qx) = qp_store<tangent>(out(i, j));
}
}
}
}
}
// Pull primal/tangent pair into a dual q-function argument
template<int DIM, typename T, typename Reg>
MFEM_HOST_DEVICE inline auto
pull_directional(Reg &preg, Reg &sreg, int qx, int qy, int qz, bool dependent)
{
if constexpr (!qf_param_uses_dual_v<T>)
{
return load_at<DIM, T>(preg, qx, qy, qz);
}
else
{
if (!dependent) { return load_at<DIM, T>(preg, qx, qy, qz); }
constexpr int RNK = qf_param_shape<T>::rank;
if constexpr (DIM == 2)
{
MFEM_CONTRACT_VAR(qz);
if constexpr (RNK == 0)
{
return T{ preg(0, qy, qx), sreg(0, qy, qx) };
}
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<T>::extents[0];
T t{};
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd)
{
t(dd) = { preg(dd, qy, qx), sreg(dd, qy, qx) };
}
return t;
}
else
{
constexpr int e0 = qf_param_shape<T>::extents[0];
constexpr int e1 = qf_param_shape<T>::extents[1];
T t;
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j)
{
t(i, j) = { preg(i, j, qy, qx), sreg(i, j, qy, qx) };
}
}
return t;
}
}
else
{
if constexpr (RNK == 0)
{
return T{ preg(0, qz, qy, qx), sreg(0, qz, qy, qx) };
}
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<T>::extents[0];
T t{};
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd)
{
t(dd) = { preg(dd, qz, qy, qx), sreg(dd, qz, qy, qx) };
}
return t;
}
else
{
constexpr int e0 = qf_param_shape<T>::extents[0];
constexpr int e1 = qf_param_shape<T>::extents[1];
T t;
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j)
{
t(i, j) = { preg(i, j, qz, qy, qx), sreg(i, j, qz, qy, qx) };
}
}
return t;
}
}
}
}
} // namespace hok
// ────────────────────────────────────────────────────────────────────────────
/// HO tensor-product kernels
template<int T_DIM, int MQ1>
struct ho_ker_backend
{
static constexpr int DIM = T_DIM;
static_assert(DIM == 2 || DIM == 3);
template<int VDIM>
using val_reg_t = std::conditional_t<(DIM == 2),
ker::v_regs2d_t<VDIM, MQ1>,
ker::v_regs3d_t<VDIM, MQ1>>;
template<int VDIM, int SDIM>
using del_reg_t = std::conditional_t<(DIM == 2),
ker::vd_regs2d_t<VDIM, SDIM, MQ1>,
ker::vd_regs3d_t<VDIM, SDIM, MQ1>>;
struct Shared
{
real_t M[MQ1][MQ1], B[MQ1][MQ1], G[MQ1][MQ1];
};
template<typename XE_t, typename Dofs>
static MFEM_HOST_DEVICE void
load_dofs(const int e, const int d, const XE_t &XE, Dofs &dofs)
{
if constexpr (DIM == 2) { ker::LoadDofs2d(e, d, XE, dofs); }
else
{
ker::LoadDofs3d(e, d, XE, dofs);
}
}
template<int VDIM, int SDIM, typename XE_t, typename Dofs>
static MFEM_HOST_DEVICE void
load_grad_dofs(const int e, const int d, const XE_t &XE, Dofs &dofs)
{
static_assert(SDIM == DIM, "gradient spatial dim must match kernel DIM");
load_dofs(e, d, XE, dofs);
}
template<typename Smem, typename Dofs, typename ArgReg>
static MFEM_HOST_DEVICE void
eval_value(const int d, const int q, Smem &s, Dofs &dofs, ArgReg &rarg)
{
if constexpr (DIM == 2) { ker::Eval2d(d, q, s.M, s.B, dofs, rarg); }
else
{
ker::Eval3d(d, q, s.M, s.B, dofs, rarg);
}
}
template<int VDIM, int SDIM, typename Smem, typename Dofs, typename ArgReg>
static MFEM_HOST_DEVICE void
grad(const int d, const int q, Smem &s, Dofs &dofs, ArgReg &rarg)
{
static_assert(SDIM == DIM, "gradient spatial dim must match kernel DIM");
if constexpr (DIM == 2) { ker::Grad2d(d, q, s.M, s.B, s.G, dofs, rarg); }
else
{
ker::Grad3d(d, q, s.M, s.B, s.G, dofs, rarg);
}
}
template<typename Smem, typename Dofs, typename ArgReg, typename YE_t>
static MFEM_HOST_DEVICE void write_value(const int d,
const int q,
const int e,
Smem &s,
ArgReg &rarg,
Dofs &dofs,
YE_t &YE)
{
if constexpr (DIM == 2)
{
ker::EvalTranspose2d(d, q, s.M, s.B, rarg, dofs);
ker::WriteDofs2d(e, d, dofs, YE);
}
else
{
ker::EvalTranspose3d(d, q, s.M, s.B, rarg, dofs);
ker::WriteDofs3d(e, d, dofs, YE);
}
}
template<typename Smem, typename Dofs, typename ArgReg, typename YE_t>
static MFEM_HOST_DEVICE void write_gradient_2d(const int d,
const int q,
const int e,
Smem &s,
ArgReg &rarg,
Dofs &dofs,
YE_t &YE)
{
ker::GradTranspose2d(d, q, s.M, s.B, s.G, rarg, dofs);
ker::WriteDofs2d(e, d, dofs, YE);
}
template<typename Smem, typename Dofs, typename ArgReg, typename YE_t>
static MFEM_HOST_DEVICE void write_gradient_3d(const int d,
const int q,
const int e,
Smem &s,
ArgReg &rarg,
Dofs &dofs,
YE_t &YE)
{
ker::GradTranspose3d(d, q, s.M, s.B, s.G, rarg, dofs);
ker::WriteDofs3d(e, d, dofs, YE);
}
template<int VDIM,
int SDIM,
typename Smem,
typename Dofs,
typename ArgReg,
typename YE_t>
static MFEM_HOST_DEVICE void write_gradient(const int d,
const int q,
const int e,
Smem &s,
ArgReg &rarg,
Dofs &dofs,
YE_t &YE)
{
static_assert(SDIM == DIM, "gradient spatial dim must match kernel DIM");
if constexpr (DIM == 2) { write_gradient_2d(d, q, e, s, rarg, dofs, YE); }
else
{
write_gradient_3d(d, q, e, s, rarg, dofs, YE);
}
}
};
// ────────────────────────────────────────────────────────────────────────────
template<int T_DIM, int T_Q1D = LocalQFHOBackendMQ1()>
struct LocalQFHOBackend
{
// ─────────────────────────────────────────────────────
static constexpr int DIM = T_DIM, MQ1 = T_Q1D, Q1D = T_Q1D;
static_assert(DIM == 2 || DIM == 3);
// ─────────────────────────────────────────────────────
static inline ThreadBlocks thread_blocks(const int q1d)
{
MFEM_ASSERT(q1d <= Q1D, "q1d must be <= " << Q1D);
return { q1d, q1d, 1 };
}
// ─────────────────────────────────────────────────────
static inline constexpr int MAX_THREADS_PER_BLOCK() { return Q1D * Q1D; }
// ─────────────────────────────────────────────────────
using backend_t = ho_ker_backend<DIM, Q1D>;
// ─────────────────────────────────────────────────────
using Shared = typename backend_t::Shared;
// ─────────────────────────────────────────────────────
template<typename WT, typename WI, typename Cache, typename AddY>
static MFEM_HOST_DEVICE inline void DiagContract(Shared &s,
const int num_dof_1d,
const int q1d,
const int nz_dof,
WT wt,
WI wi,
Cache cache,
AddY add_y)
{
MFEM_CONTRACT_VAR(nz_dof);
const int nqz = (DIM == 3) ? q1d : 1;
const int ndz = (DIM == 3) ? num_dof_1d : 1;
ker::s_regs3d_t<MQ1> rz, ry;
auto &smem = s.M;
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
for (int dz = 0; dz < ndz; dz++)
{
real_t u = 0.0;
for (int qz = 0; qz < nqz; qz++)
{
const int q = qx + (qy + qz * q1d) * q1d;
const real_t wz =
(DIM == 3) ? (wt(2, qz, dz) * wi(2, qz, dz)) : real_t(1);
u += wz * cache(q);
}
rz[dz][qy][qx] = u;
}
}
}
MFEM_SYNC_THREAD;
for (int dz = 0; dz < ndz; dz++)
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{ smem[qy][qx] = rz[dz][qy][qx]; }
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD_DIRECT(dy, y, num_dof_1d)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
real_t u = 0.0;
for (int qy = 0; qy < q1d; qy++)
{
u += wt(1, qy, dy) * wi(1, qy, dy) * smem[qy][qx];
}
ry[dz][dy][qx] = u;
}
}
MFEM_SYNC_THREAD;
}
for (int dz = 0; dz < ndz; dz++)
{
MFEM_FOREACH_THREAD_DIRECT(dy, y, num_dof_1d)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{ smem[dy][qx] = ry[dz][dy][qx]; }
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD_DIRECT(dy, y, num_dof_1d)
{
MFEM_FOREACH_THREAD_DIRECT(dx, x, num_dof_1d)
{
real_t u = 0.0;
for (int qx = 0; qx < q1d; qx++)
{
u += wt(0, qx, dx) * wi(0, qx, dx) * smem[dy][qx];
}
add_y(dx, dy, dz, u);
}
}
MFEM_SYNC_THREAD;
}
}
// ─────────────────────────────────────────────────────
template<typename T>
using QReg = ho_qreg_t<backend_t, T>;
// ─────────────────────────────────────────────────────
template<typename ArgRegT, typename XE_T>
static inline MFEM_HOST_DEVICE void LoadValue(Shared &s,
const int e,
const int d,
const int q,
const int,
const real_t *B,
const XE_T &XE,
ArgRegT &rarg)
{
ker::LoadMatrix(d, q, B, s.B);
std::remove_reference_t<ArgRegT> dofs;
backend_t::load_dofs(e, d, XE, dofs);
backend_t::eval_value(d, q, s, dofs, rarg);
}
// ─────────────────────────────────────────────────────
template<int RNK,
typename ArgRegT,
typename XE_T,
typename FieldParamT = ArgRegT>
static inline MFEM_HOST_DEVICE void LoadGradient(Shared &s,
const int e,
const int d,
const int q,
const int,
const real_t *B,
const real_t *G,
const XE_T &XE,
ArgRegT &rarg)
{
ker::LoadMatrix(d, q, B, s.B);
ker::LoadMatrix(d, q, G, s.G);
static_assert(RNK == 1 || RNK == 2);
static constexpr int VDIM =
(RNK == 1) ? 1 : qf_param_shape<FieldParamT>::extents[0];
static constexpr int SDIM = (RNK == 1)
? qf_param_shape<FieldParamT>::extents[0]
: qf_param_shape<FieldParamT>::extents[1];
if constexpr (SDIM == DIM)
{
typename backend_t::template del_reg_t<VDIM, SDIM> dofs;
if constexpr (RNK == 1) { backend_t::load_dofs(e, d, XE, dofs); }
else
{
backend_t::template load_grad_dofs<VDIM, SDIM>(e, d, XE, dofs);
}
backend_t::template grad<VDIM, SDIM>(d, q, s, dofs, rarg);
}
}
// ─────────────────────────────────────────────────────
template<typename T>
static MFEM_HOST_DEVICE inline auto
qp_pull(QReg<T> &reg, int qx, int qy, int qz)
{ return hok::load_at<DIM, T>(reg, qx, qy, qz); }
// ─────────────────────────────────────────────────────
template<typename T>
static MFEM_HOST_DEVICE inline auto qp_pull_directional(
QReg<T> &preg, QReg<T> &sreg, int qx, int qy, int qz, bool dependent)
{ return hok::pull_directional<DIM, T>(preg, sreg, qx, qy, qz, dependent); }
// ─────────────────────────────────────────────────────
template<typename DT, typename XE_T>
static MFEM_HOST_DEVICE inline DT identity_qp_pull_dual(bool dependent,
const XE_T &XP,
const XE_T &XD,
int qx,
int qy,
int qz,
int e)
{
constexpr int RNK = qf_param_shape<DT>::rank;
if constexpr (RNK == 0)
{
DT t{};
t.value = XP(0, qx, qy, qz, e);
t.gradient = dependent ? XD(0, qx, qy, qz, e) : 0.0;
return t;
}
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<DT>::extents[0];
DT t{};
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd)
{
t(dd).value = XP(dd, qx, qy, qz, e);
t(dd).gradient = dependent ? XD(dd, qx, qy, qz, e) : 0.0;
}
return t;
}
else if constexpr (RNK == 2)
{
constexpr int e0 = qf_param_shape<DT>::extents[0];
constexpr int e1 = qf_param_shape<DT>::extents[1];
DT t{};
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j)
{
t(i, j).value = XP(i + e0 * j, qx, qy, qz, e);
t(i, j).gradient =
dependent ? XD(i + e0 * j, qx, qy, qz, e) : 0.0;
}
}
return t;
}
else
{
static_assert(false, "Unsupported");
}
}
// ─────────────────────────────────────────────────────
template<typename T>
static MFEM_HOST_DEVICE inline void
qp_push(QReg<T> &reg, int qx, int qy, int qz, const T &out)
{ hok::store_at<DIM, T, decltype(reg), false>(reg, qx, qy, qz, out); }
// ─────────────────────────────────────────────────────
template<typename T>
static MFEM_HOST_DEVICE inline void
qp_push_tangent(QReg<T> &reg, int qx, int qy, int qz, const T &out)
{
hok::store_at<DIM, T, decltype(reg), qf_param_uses_dual_v<T>>(
reg, qx, qy, qz, out);
}
// ─────────────────────────────────────────────────────
template<typename DT, typename YE_T>
static MFEM_HOST_DEVICE inline void identity_qp_write_value(
YE_T &YE, int qx, int qy, int qz, int e, const DT &qout)
{
constexpr int RNK = qf_param_shape<DT>::rank;
if constexpr (qf_param_uses_dual_v<DT>)
{
if constexpr (RNK == 0)
{
YE(0, qx, qy, qz, e) = qf_store_value(qout);
}
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<DT>::extents[0];
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd)
{
YE(dd, qx, qy, qz, e) = qf_store_value(qout(dd));
}
}
else if constexpr (RNK == 2)
{
constexpr int e0 = qf_param_shape<DT>::extents[0];
constexpr int e1 = qf_param_shape<DT>::extents[1];
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j)
{
YE(i + e0 * j, qx, qy, qz, e) = qf_store_value(qout(i, j));
}
}
}
else
{
static_assert(false, "Unsupported");
}
}
}
// ─────────────────────────────────────────────────────
template<typename DT, typename YE_T>
static MFEM_HOST_DEVICE inline void identity_qp_write_tangent(
YE_T &YE, int qx, int qy, int qz, int e, const DT &qout)
{
constexpr int RNK = qf_param_shape<DT>::rank;
if constexpr (qf_param_uses_dual_v<DT>)
{
if constexpr (RNK == 0)
{
YE(0, qx, qy, qz, e) = qf_store_gradient(qout);
}
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<DT>::extents[0];
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd)
{
YE(dd, qx, qy, qz, e) = qf_store_gradient(qout(dd));
}
}
else if constexpr (RNK == 2)
{
constexpr int e0 = qf_param_shape<DT>::extents[0];
constexpr int e1 = qf_param_shape<DT>::extents[1];
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j)
{
YE(i + e0 * j, qx, qy, qz, e) = qf_store_gradient(qout(i, j));
}
}
}
else
{
static_assert(false, "Unsupported");
}
}
}
// ─────────────────────────────────────────────────────
template<typename ArgRegT, typename YE_T>
static inline MFEM_HOST_DEVICE void WriteValue(Shared &s,
const int e,
const int d,
const int q,
const int,
const real_t *B,
YE_T &YE,
ArgRegT &rarg)
{
ker::LoadMatrix(d, q, B, s.B);
std::remove_reference_t<ArgRegT> dofs;
backend_t::write_value(d, q, e, s, rarg, dofs, YE);
}
// ─────────────────────────────────────────────────────
template<int RNK,
typename ArgRegT,
typename YE_T,
typename FieldParamT = ArgRegT>
static inline MFEM_HOST_DEVICE void WriteGradient(Shared &s,
const int e,
const int d,
const int q,
const int,
const real_t *B,
const real_t *G,
YE_T &YE,
ArgRegT &rarg)
{
ker::LoadMatrix(d, q, B, s.B);
ker::LoadMatrix(d, q, G, s.G);
static_assert(RNK == 1 || RNK == 2);
static constexpr int VDIM =
(RNK == 1) ? 1 : qf_param_shape<FieldParamT>::extents[0];
static constexpr int SDIM = (RNK == 1)
? qf_param_shape<FieldParamT>::extents[0]
: qf_param_shape<FieldParamT>::extents[1];
if constexpr (SDIM == DIM)
{
typename backend_t::template del_reg_t<VDIM, SDIM> dofs;
backend_t::template write_gradient<VDIM, SDIM>(
d, q, e, s, rarg, dofs, YE);
}
}
};
/// @brief Dispatch to a compile-time HO kernel with MQ1 >= runtime @a q1d.
template <typename HOKernelTable, int DIM, int MQ1 = LocalQFHOBackendMQ1()>
inline typename HOKernelTable::KernelSignature
DispatchHOKernelByQ1D(int q1d)
{
MFEM_VERIFY(q1d >= 2 && q1d <= MQ1,
"Unsupported HO quadrature order: " << q1d);
return HOKernelTable::template Kernel<DIM, MQ1>();
}
} // namespace mfem::future
+813
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@@ -0,0 +1,813 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../../../kernels.hpp"
namespace ker = mfem::kernels::internal;
#include "../../util.hpp" // for ThreadBlocks
#include "../util.hpp" // for as_tensor
#include "util.hpp"
namespace mfem::future
{
// ────────────────────────────────────────────────────────────────────────────
inline constexpr int LocalQFLOBackendMQ1() { return 8; }
// ────────────────────────────────────────────────────────────────────────────
/// Register type for one LO q-function parameter
template<typename KerOps, typename T, int rank = qf_param_shape<T>::rank>
struct lo_qreg;
template<typename KerOps, typename T>
struct lo_qreg<KerOps, T, 0>
{
using type = typename KerOps::template qreg_t<1>;
};
template<typename KerOps, typename T>
struct lo_qreg<KerOps, T, 1>
{
static constexpr int e0 = qf_param_shape<T>::extents[0];
using type = typename KerOps::template qreg_t<e0>;
};
template<typename KerOps, typename T>
struct lo_qreg<KerOps, T, 2>
{
static constexpr int e0 = qf_param_shape<T>::extents[0];
static constexpr int e1 = qf_param_shape<T>::extents[1];
using type = typename KerOps::template qreg_vd_t<e0, e1>;
};
template<typename KerOps, typename T>
using lo_qreg_t = typename lo_qreg<KerOps, T>::type;
// ────────────────────────────────────────────────────────────────────────────
namespace lok
{
template<int DIM, typename Reg>
MFEM_HOST_DEVICE inline auto &at(Reg &reg, int qx, int qy, int qz)
{
if constexpr (DIM == 2)
{
MFEM_CONTRACT_VAR(qz);
return reg[qy][qx];
}
else
{
return reg[qz][qy][qx];
}
}
template<int DIM, typename T, typename Reg>
MFEM_HOST_DEVICE inline auto load_at(Reg &reg, int qx, int qy, int qz)
{
constexpr int RNK = qf_param_shape<T>::rank;
auto &qp = at<DIM>(reg, qx, qy, qz);
if constexpr (RNK == 0) { return T{ qp[0] }; }
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<T>::extents[0];
T t{};
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd) { t(dd) = qp[dd]; }
return t;
}
else
{
constexpr int e0 = qf_param_shape<T>::extents[0];
constexpr int e1 = qf_param_shape<T>::extents[1];
T t;
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j) { t(i, j) = qp[i][j]; }
}
return t;
}
}
template<bool tangent, typename U>
MFEM_HOST_DEVICE inline auto qp_store(const U &v)
{
if constexpr (tangent) { return qf_store_gradient(v); }
else
{
return qf_store_value(v);
}
}
// Store primal value or dual tangent at one quadrature point
template<int DIM, typename T, typename Reg, bool tangent>
MFEM_HOST_DEVICE inline void
store_at(Reg &reg, int qx, int qy, int qz, const T &out)
{
constexpr int RNK = qf_param_shape<T>::rank;
auto &qp = at<DIM>(reg, qx, qy, qz);
if constexpr (RNK == 0) { qp[0] = qp_store<tangent>(out); }
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<T>::extents[0];
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd) { qp[dd] = qp_store<tangent>(out(dd)); }
}
else
{
constexpr int e0 = qf_param_shape<T>::extents[0];
constexpr int e1 = qf_param_shape<T>::extents[1];
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j)
{
qp[i][j] = qp_store<tangent>(out(i, j));
}
}
}
}
// Pull primal/tangent pair into a dual q-function argument
template<int DIM, typename T, typename Reg>
MFEM_HOST_DEVICE inline auto
pull_directional(Reg &preg, Reg &sreg, int qx, int qy, int qz, bool dependent)
{
if constexpr (!qf_param_uses_dual_v<T>)
{
return load_at<DIM, T>(preg, qx, qy, qz);
}
else
{
if (!dependent) { return load_at<DIM, T>(preg, qx, qy, qz); }
constexpr int RNK = qf_param_shape<T>::rank;
auto &pqp = at<DIM>(preg, qx, qy, qz);
auto &sqp = at<DIM>(sreg, qx, qy, qz);
if constexpr (RNK == 0) { return T{ pqp[0], sqp[0] }; }
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<T>::extents[0];
T t{};
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd) { t(dd) = { pqp[dd], sqp[dd] }; }
return t;
}
else
{
constexpr int e0 = qf_param_shape<T>::extents[0];
constexpr int e1 = qf_param_shape<T>::extents[1];
T t;
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j) { t(i, j) = { pqp[i][j], sqp[i][j] }; }
}
return t;
}
}
}
} // namespace lok
// ────────────────────────────────────────────────────────────────────────────
/// LO tensor-product kernels
template<int T_DIM, int MQ1>
struct lo_ker_backend
{
static constexpr int DIM = T_DIM;
static_assert(DIM == 2 || DIM == 3);
template<int VDIM>
using qreg_t = std::conditional_t<(DIM == 2),
ker::regs2d_t<VDIM, MQ1>,
ker::regs3d_t<VDIM, MQ1>>;
template<int VDIM, int SDIM>
using qreg_vd_t = std::conditional_t<(DIM == 2),
ker::regs2d_vd_t<VDIM, SDIM, MQ1>,
ker::regs3d_vd_t<VDIM, SDIM, MQ1>>;
struct Shared2d
{
real_t M[2][MQ1][MQ1][DIM];
real_t B[MQ1][MQ1], G[MQ1][MQ1];
};
struct Shared3d
{
real_t M[2][MQ1][MQ1][MQ1][DIM];
real_t B[MQ1][MQ1], G[MQ1][MQ1];
};
using Shared = std::conditional_t<(DIM == 2), Shared2d, Shared3d>;
template<typename FieldParamT, typename ArgRegT, typename XE_T>
static MFEM_HOST_DEVICE void load_value(Shared &s,
const int e,
const int d,
const int q,
const real_t *B,
const XE_T &XE,
ArgRegT &rarg)
{
ker::LoadMatrix(d, q, B, s.B);
using field_t = std::remove_cv_t<std::remove_reference_t<FieldParamT>>;
constexpr int RNK = qf_param_shape<field_t>::rank;
constexpr int VDIM = []()
{
if constexpr (RNK == 0) { return 1; }
else { return qf_param_shape<field_t>::extents[RNK - 1]; }
}();
if constexpr (DIM == 2)
{
ker::LoadDofs2d<VDIM, DIM, MQ1>(e, d, XE, s.M[0]);
ker::Eval2d(d, q, s.B, s.M[0], s.M[1], rarg);
}
else
{
ker::LoadDofs3d<VDIM, DIM, MQ1>(e, d, XE, s.M[0]);
ker::Eval3d(d, q, s.B, s.M[0], s.M[1], rarg);
}
}
template<int RNK,
typename ArgRegT,
typename XE_T,
typename FieldParamT = ArgRegT>
static MFEM_HOST_DEVICE void load_gradient(Shared &s,
const int e,
const int d,
const int q,
const real_t *B,
const real_t *G,
const XE_T &XE,
ArgRegT &rarg)
{
ker::LoadMatrix(d, q, B, s.B);
ker::LoadMatrix(d, q, G, s.G);
static_assert(RNK == 1 || RNK == 2);
if constexpr (RNK == 1)
{
static constexpr int SDIM = qf_param_shape<FieldParamT>::extents[0];
if constexpr (SDIM == DIM)
{
if constexpr (DIM == 2)
{
ker::LoadDofs2d(e, d, 0, XE, s.M[0]);
ker::Grad2d(d, q, s.B, s.G, s.M[0], s.M[1], rarg);
}
else
{
ker::LoadDofs3d(e, d, 0, XE, s.M[0]);
ker::Grad3d(d, q, s.B, s.G, s.M[0], s.M[1], rarg);
}
}
}
if constexpr (RNK == 2)
{
static constexpr int VDIM = qf_param_shape<FieldParamT>::extents[0];
static constexpr int SDIM = qf_param_shape<FieldParamT>::extents[1];
if constexpr (SDIM == DIM)
{
for (int c = 0; c < VDIM; ++c)
{
if constexpr (DIM == 2)
{
ker::LoadDofs2d(e, d, c, XE, s.M[0]);
ker::VectorGrad2d(d, q, c, s.B, s.G, s.M[0], s.M[1], rarg);
}
else
{
ker::LoadDofs3d(e, d, c, XE, s.M[0]);
ker::VectorGrad3d(d, q, c, s.B, s.G, s.M[0], s.M[1], rarg);
}
}
}
}
}
template<typename ArgRegT, typename YE_T>
static MFEM_HOST_DEVICE void write_value(Shared &s,
const int e,
const int d,
const int q,
const real_t *B,
const YE_T &YE,
ArgRegT &rarg)
{
ker::LoadMatrix(d, q, B, s.B);
if constexpr (DIM == 2)
{
ker::EvalTranspose2d(d, q, s.B, rarg, s.M[1], s.M[0]);
ker::WriteEvalDofs2d(d, 0, e, rarg, YE);
}
else
{
ker::EvalTranspose3d(d, q, s.B, rarg, s.M[1], s.M[0]);
ker::WriteEvalDofs3d(d, 0, e, rarg, YE);
}
}
template<int RNK,
typename ArgRegT,
typename YE_T,
typename FieldParamT = ArgRegT>
static MFEM_HOST_DEVICE void write_gradient(Shared &s,
const int e,
const int d,
const int q,
const real_t *B,
const real_t *G,
YE_T &YE,
ArgRegT &rarg)
{
ker::LoadMatrix(d, q, B, s.B);
ker::LoadMatrix(d, q, G, s.G);
static_assert(RNK == 1 || RNK == 2);
if constexpr (RNK == 1)
{
static constexpr int SDIM = qf_param_shape<FieldParamT>::extents[0];
if constexpr (SDIM == DIM)
{
if constexpr (DIM == 2)
{
ker::GradTranspose2d(d, q, s.B, s.G, rarg, s.M[1], s.M[0]);
ker::WriteGradDofs2d(d, 0, e, rarg, YE);
}
else
{
ker::GradTranspose3d(d, q, s.B, s.G, rarg, s.M[1], s.M[0]);
ker::WriteGradDofs3d(d, 0, e, rarg, YE);
}
}
}
else if constexpr (RNK == 2)
{
static constexpr int VDIM = qf_param_shape<FieldParamT>::extents[0];
static constexpr int SDIM = qf_param_shape<FieldParamT>::extents[1];
if constexpr (SDIM == DIM)
{
for (int c = 0; c < VDIM; ++c)
{
if constexpr (DIM == 2)
{
ker::VectorGradTranspose2d(
d, q, c, s.B, s.G, s.M[0], s.M[1], rarg);
ker::WriteGradDofs2d(d, c, e, rarg, YE);
}
else
{
ker::VectorGradTranspose3d(
d, q, c, s.B, s.G, s.M[0], s.M[1], rarg);
ker::WriteGradDofs3d(d, c, e, rarg, YE);
}
}
}
}
else
{
static_assert(false, "Unsupported");
}
}
};
// ────────────────────────────────────────────────────────────────────────────
template<int T_DIM, int T_Q1D = LocalQFLOBackendMQ1()>
struct LocalQFLOBackend
{
// ─────────────────────────────────────────────────────
static constexpr int DIM = T_DIM, MQ1 = T_Q1D, Q1D = T_Q1D;
static_assert(DIM == 2 || DIM == 3);
// ─────────────────────────────────────────────────────
static inline ThreadBlocks thread_blocks(const int q1d)
{
MFEM_ASSERT(q1d <= Q1D, "q1d must be <= " << Q1D);
return { q1d, q1d, (DIM == 2) ? 1 : q1d };
}
// ─────────────────────────────────────────────────────
static inline constexpr int MAX_THREADS_PER_BLOCK()
{ return Q1D * Q1D * ((DIM == 2) ? 1 : Q1D); }
// ─────────────────────────────────────────────────────
using backend_t = lo_ker_backend<DIM, Q1D>;
// ─────────────────────────────────────────────────────
using Shared = typename backend_t::Shared;
// ─────────────────────────────────────────────────────
template<typename WT, typename WI, typename Cache, typename AddY>
static MFEM_HOST_DEVICE inline void DiagContract(Shared &s,
const int num_dof_1d,
const int q1d,
const int nz_dof,
WT wt,
WI wi,
Cache cache,
AddY add_y)
{
MFEM_CONTRACT_VAR(nz_dof);
real_t *base = reinterpret_cast<real_t *>(&s.M[0]);
auto s0 = reinterpret_cast<real_t(*)[Q1D][Q1D]>(base);
if constexpr (DIM == 3)
{
auto s1 =
reinterpret_cast<real_t(*)[Q1D][Q1D]>(base + Q1D * Q1D * Q1D);
// reduce qz → dz : s0[dz][qy][qx]
MFEM_FOREACH_THREAD(dz, z, num_dof_1d)
MFEM_FOREACH_THREAD(qy, y, q1d)
MFEM_FOREACH_THREAD(qx, x, q1d)
{
real_t u = 0.0;
for (int qz = 0; qz < q1d; qz++)
{
const int q = qx + (qy + qz * q1d) * q1d;
u += wt(2, qz, dz) * wi(2, qz, dz) * cache(q);
}
s0[dz][qy][qx] = u;
}
MFEM_SYNC_THREAD;
// reduce qy → dy : s1[dz][dy][qx]
MFEM_FOREACH_THREAD(dz, z, num_dof_1d)
MFEM_FOREACH_THREAD(dy, y, num_dof_1d)
MFEM_FOREACH_THREAD(qx, x, q1d)
{
real_t u = 0.0;
for (int qy = 0; qy < q1d; qy++)
{
u += wt(1, qy, dy) * wi(1, qy, dy) * s0[dz][qy][qx];
}
s1[dz][dy][qx] = u;
}
MFEM_SYNC_THREAD;
// reduce qx → dx : Y(dx,dy,dz)
MFEM_FOREACH_THREAD(dz, z, num_dof_1d)
MFEM_FOREACH_THREAD(dy, y, num_dof_1d)
MFEM_FOREACH_THREAD(dx, x, num_dof_1d)
{
real_t u = 0.0;
for (int qx = 0; qx < q1d; qx++)
{
u += wt(0, qx, dx) * wi(0, qx, dx) * s1[dz][dy][qx];
}
add_y(dx, dy, dz, u);
}
MFEM_SYNC_THREAD;
}
else
{
// reduce qy → dy : s0[0][dy][qx]
MFEM_FOREACH_THREAD(dy, y, num_dof_1d)
MFEM_FOREACH_THREAD(qx, x, q1d)
{
real_t u = 0.0;
for (int qy = 0; qy < q1d; qy++)
{
const int q = qx + qy * q1d;
u += wt(1, qy, dy) * wi(1, qy, dy) * cache(q);
}
s0[0][dy][qx] = u;
}
MFEM_SYNC_THREAD;
// reduce qx → dx : Y(dx,dy,0)
MFEM_FOREACH_THREAD(dy, y, num_dof_1d)
MFEM_FOREACH_THREAD(dx, x, num_dof_1d)
{
real_t u = 0.0;
for (int qx = 0; qx < q1d; qx++)
{
u += wt(0, qx, dx) * wi(0, qx, dx) * s0[0][dy][qx];
}
add_y(dx, dy, 0, u);
}
MFEM_SYNC_THREAD;
}
}
// ─────────────────────────────────────────────────────
template<typename T>
using QReg = lo_qreg_t<backend_t, T>;
// ─────────────────────────────────────────────────────
template<typename ArgRegT, typename XE_T>
static inline MFEM_HOST_DEVICE void LoadValue(Shared &s,
const int e,
const int d,
const int q,
const int,
const real_t *B,
const XE_T &XE,
ArgRegT &rarg)
{
backend_t::template load_value<ArgRegT>(s, e, d, q, B, XE, rarg);
}
// ─────────────────────────────────────────────────────
template<int RNK,
typename ArgRegT,
typename XE_T,
typename FieldParamT = ArgRegT>
static inline MFEM_HOST_DEVICE void LoadGradient(Shared &s,
const int e,
const int d,
const int q,
const int,
const real_t *B,
const real_t *G,
const XE_T &XE,
ArgRegT &rarg)
{
backend_t::template load_gradient<RNK, ArgRegT, XE_T, FieldParamT>(
s, e, d, q, B, G, XE, rarg);
}
// ─────────────────────────────────────────────────────
template<typename T>
static MFEM_HOST_DEVICE inline auto
qp_pull(QReg<T> &reg, int qx, int qy, int qz)
{
if constexpr (qf_param_uses_dual_v<T>)
{
return lok::load_at<DIM, T>(reg, qx, qy, qz);
}
else
{
constexpr int RNK = qf_param_shape<T>::rank;
if constexpr (RNK == 0)
{
return as_tensor<real_t>(&lok::at<DIM>(reg, qx, qy, qz)[0]);
}
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<T>::extents[0];
return as_tensor<real_t, e0>(&lok::at<DIM>(reg, qx, qy, qz)[0]);
}
else if constexpr (RNK == 2)
{
constexpr int e0 = qf_param_shape<T>::extents[0];
constexpr int e1 = qf_param_shape<T>::extents[1];
return as_tensor<real_t, e0, e1>(
&lok::at<DIM>(reg, qx, qy, qz)[0][0]);
}
else
{
static_assert(false, "Unsupported");
}
}
}
// ─────────────────────────────────────────────────────
template<typename T>
static MFEM_HOST_DEVICE inline auto qp_pull_directional(
QReg<T> &preg, QReg<T> &sreg, int qx, int qy, int qz, bool dependent)
{ return lok::pull_directional<DIM, T>(preg, sreg, qx, qy, qz, dependent); }
// ─────────────────────────────────────────────────────
template<typename DT, typename XE_T>
static MFEM_HOST_DEVICE inline DT identity_qp_pull_dual(bool dependent,
const XE_T &XP,
const XE_T &XD,
int qx,
int qy,
int qz,
int e)
{
constexpr int RNK = qf_param_shape<DT>::rank;
if constexpr (RNK == 0)
{
DT t{};
t.value = XP(0, qx, qy, qz, e);
t.gradient = dependent ? XD(0, qx, qy, qz, e) : 0.0;
return t;
}
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<DT>::extents[0];
DT t{};
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd)
{
t(dd).value = XP(dd, qx, qy, qz, e);
t(dd).gradient = dependent ? XD(dd, qx, qy, qz, e) : 0.0;
}
return t;
}
else if constexpr (RNK == 2)
{
constexpr int e0 = qf_param_shape<DT>::extents[0];
constexpr int e1 = qf_param_shape<DT>::extents[1];
DT t{};
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j)
{
t(i, j).value = XP(i + e0 * j, qx, qy, qz, e);
t(i, j).gradient =
dependent ? XD(i + e0 * j, qx, qy, qz, e) : 0.0;
}
}
return t;
}
else
{
static_assert(false, "Unsupported");
}
}
// ─────────────────────────────────────────────────────
template<typename T>
static MFEM_HOST_DEVICE inline void
qp_push(QReg<T> &reg, int qx, int qy, int qz, const T &out)
{
if constexpr (qf_param_uses_dual_v<T>)
{
lok::store_at<DIM, T, decltype(reg), false>(reg, qx, qy, qz, out);
}
else
{
constexpr int RNK = qf_param_shape<T>::rank;
if constexpr (RNK == 0)
{
as_tensor<real_t>(&lok::at<DIM>(reg, qx, qy, qz)[0]) = out;
}
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<T>::extents[0];
as_tensor<real_t, e0>(&lok::at<DIM>(reg, qx, qy, qz)[0]) = out;
}
else if constexpr (RNK == 2)
{
constexpr int e0 = qf_param_shape<T>::extents[0];
constexpr int e1 = qf_param_shape<T>::extents[1];
as_tensor<real_t, e0, e1>(&lok::at<DIM>(reg, qx, qy, qz)[0][0]) =
out;
}
else
{
static_assert(false, "Unsupported");
}
}
}
// ─────────────────────────────────────────────────────
template<typename T>
static MFEM_HOST_DEVICE inline void
qp_push_tangent(QReg<T> &reg, int qx, int qy, int qz, const T &out)
{
if constexpr (!qf_param_uses_dual_v<T>)
{
qp_push<T>(reg, qx, qy, qz, out);
}
else
{
lok::store_at<DIM, T, decltype(reg), true>(reg, qx, qy, qz, out);
}
}
// ─────────────────────────────────────────────────────
template<typename DT, typename YE_T>
static MFEM_HOST_DEVICE inline void identity_qp_write_value(
YE_T &YE, int qx, int qy, int qz, int e, const DT &qout)
{
constexpr int RNK = qf_param_shape<DT>::rank;
if constexpr (qf_param_uses_dual_v<DT>)
{
if constexpr (RNK == 0)
{
YE(0, qx, qy, qz, e) = qf_store_value(qout);
}
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<DT>::extents[0];
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd)
{
YE(dd, qx, qy, qz, e) = qf_store_value(qout(dd));
}
}
else if constexpr (RNK == 2)
{
constexpr int e0 = qf_param_shape<DT>::extents[0];
constexpr int e1 = qf_param_shape<DT>::extents[1];
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j)
{
YE(i + e0 * j, qx, qy, qz, e) = qf_store_value(qout(i, j));
}
}
}
else
{
static_assert(false, "Unsupported");
}
}
}
// ─────────────────────────────────────────────────────
template<typename DT, typename YE_T>
static MFEM_HOST_DEVICE inline void identity_qp_write_tangent(
YE_T &YE, int qx, int qy, int qz, int e, const DT &qout)
{
constexpr int RNK = qf_param_shape<DT>::rank;
if constexpr (qf_param_uses_dual_v<DT>)
{
if constexpr (RNK == 0)
{
YE(0, qx, qy, qz, e) = qf_store_gradient(qout);
}
else if constexpr (RNK == 1)
{
constexpr int e0 = qf_param_shape<DT>::extents[0];
MFEM_UNROLL(e0)
for (int dd = 0; dd < e0; ++dd)
{
YE(dd, qx, qy, qz, e) = qf_store_gradient(qout(dd));
}
}
else if constexpr (RNK == 2)
{
constexpr int e0 = qf_param_shape<DT>::extents[0];
constexpr int e1 = qf_param_shape<DT>::extents[1];
MFEM_UNROLL(e0)
for (int i = 0; i < e0; ++i)
{
MFEM_UNROLL(e1)
for (int j = 0; j < e1; ++j)
{
YE(i + e0 * j, qx, qy, qz, e) = qf_store_gradient(qout(i, j));
}
}
}
else
{
static_assert(false, "Unsupported");
}
}
}
// ─────────────────────────────────────────────────────
template<typename ArgRegT, typename YE_T>
static inline MFEM_HOST_DEVICE void WriteValue(Shared &s,
const int e,
const int d,
const int q,
const int,
const real_t *B,
const YE_T &YE,
ArgRegT &rarg)
{ backend_t::write_value(s, e, d, q, B, YE, rarg); }
// ─────────────────────────────────────────────────────
template<int RNK,
typename ArgRegT,
typename YE_T,
typename FieldParamT = ArgRegT>
static inline MFEM_HOST_DEVICE void WriteGradient(Shared &s,
const int e,
const int d,
const int q,
const int,
const real_t *B,
const real_t *G,
YE_T &YE,
ArgRegT &rarg)
{
backend_t::template write_gradient<RNK, ArgRegT, YE_T, FieldParamT>(
s, e, d, q, B, G, YE, rarg);
}
};
/// @brief Dispatch to a compile-time LO kernel matching runtime @a q1d.
template <typename LOKernelTable, int DIM, int MQ1 = LocalQFLOBackendMQ1()>
inline typename LOKernelTable::KernelSignature
DispatchLOKernelByQ1D(int q1d)
{
MFEM_VERIFY(q1d >= 2 && q1d <= MQ1,
"Unsupported LO quadrature order: " << q1d);
return LOKernelTable::template Kernel<DIM, MQ1>();
}
} // namespace mfem::future
+242
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@@ -0,0 +1,242 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../../integrator_ctx.hpp"
#include "action.hpp"
#include "derivative_action.hpp"
#include "derivative_setup.hpp"
#include "derivative_apply.hpp"
#include "derivative_assemble.hpp"
#include "derivative_assemble_diagonal.hpp"
#include "derivative_apply_transpose.hpp"
namespace mfem::future
{
struct LocalQFBackend
{
/**
* @brief Make an action for a local Q-function backend.
*
* @param ctx The integrator context.
* @param args The arguments to the action.
* @return The action.
*/
template<typename qfunc_t, typename inputs_t, typename outputs_t>
static auto MakeAction(
const IntegratorContext &ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs)
{
return LocalQFImpl::Action<qfunc_t, inputs_t, outputs_t>(
ctx, qfunc, inputs, outputs);
}
/**
* @brief Make a derivative action for a local Q-function backend.
*
* @tparam derivative_id The id of the derivative.
* @param ctx The integrator context.
* @param args The arguments to the derivative action.
* @return The derivative action.
*/
template<int id, typename qfunc_t, typename inputs_t, typename outputs_t>
static auto MakeDerivativeAction(
const IntegratorContext &ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs)
{
return LocalQFImpl::DerivativeAction<id, qfunc_t, inputs_t, outputs_t>(
ctx, qfunc, inputs, outputs);
}
template<
int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
static auto MakeDerivativeSetup(
const IntegratorContext &ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs,
Vector &qp_cache)
{
return LocalQFImpl::DerivativeSetup<
derivative_id, qfunc_t, inputs_t, outputs_t>(ctx, qfunc, inputs,
outputs, qp_cache);
}
template<
int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
static auto MakeDerivativeApply(
const IntegratorContext &ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs,
const Vector &qp_cache)
{
return LocalQFImpl::DerivativeApply<
derivative_id, qfunc_t, inputs_t, outputs_t>(ctx, qfunc, inputs,
outputs, qp_cache);
}
template<
int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
static auto MakeDerivativeApplyTranspose(
const IntegratorContext &ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs,
const Vector &qp_cache)
{
return LocalQFImpl::DerivativeApplyTranspose<
derivative_id, qfunc_t, inputs_t, outputs_t>(ctx, qfunc, inputs,
outputs, qp_cache);
}
template<
int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
static auto MakeDerivativeAssemble(
const IntegratorContext &ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs,
const Vector &qp_cache)
{
return LocalQFImpl::DerivativeAssemble<
derivative_id, qfunc_t, inputs_t, outputs_t>(ctx, qfunc, inputs,
outputs, qp_cache);
}
template<
int derivative_id,
typename qfunc_t,
typename inputs_t,
typename outputs_t>
static auto MakeDerivativeAssembleDiagonal(
const IntegratorContext &ctx,
const qfunc_t &qfunc,
inputs_t inputs,
outputs_t outputs,
const Vector &qp_cache)
{
return LocalQFImpl::DerivativeAssembleDiagonal<
derivative_id, qfunc_t, inputs_t, outputs_t>(ctx, qfunc, inputs,
outputs, qp_cache);
}
};
// ────────────────────────────────────────────────────────────────────────────
template<int DIM, int Q1D, typename QT, typename IT, typename OT>
inline void AddAction()
{
using ker = LocalQFImpl::Action<QT, IT, OT>;
if constexpr (Q1D <= 8)
{
ker::ActionLO::template Specialization<DIM, Q1D>::Add();
}
else
{
ker::ActionHO::template Specialization<DIM, Q1D>::Add();
}
}
// ────────────────────────────────────────────────────────────────────────────
template<int DIM, int Q1D, int DID, typename QT, typename IT, typename OT>
inline void AddDerivativeAction()
{
using ker = LocalQFImpl::DerivativeAction<DID, QT, IT, OT>;
if constexpr (Q1D <= 8)
{
ker::DerivativeActionLO::template Specialization<DIM, Q1D>::Add();
}
else
{
ker::DerivativeActionHO::template Specialization<DIM, Q1D>::Add();
}
}
// ────────────────────────────────────────────────────────────────────────────
template<int DIM, int Q1D, int DID, typename QT, typename IT, typename OT>
inline void AddDerivativeSetup()
{
using ker = LocalQFImpl::DerivativeSetup<DID, QT, IT, OT>;
if constexpr (Q1D <= 8)
{
ker::DerivativeSetupLO::template Specialization<DIM, Q1D>::Add();
}
else
{
ker::DerivativeSetupHO::template Specialization<DIM, Q1D>::Add();
}
}
// ────────────────────────────────────────────────────────────────────────────
template<int DIM, int Q1D, int DID, typename QT, typename IT, typename OT>
inline void AddDerivativeApply()
{
using ker = LocalQFImpl::DerivativeApply<DID, QT, IT, OT>;
if constexpr (Q1D <= 8)
{
ker::DerivativeApplyLO::template Specialization<DIM, Q1D>::Add();
}
else
{
ker::DerivativeApplyHO::template Specialization<DIM, Q1D>::Add();
}
}
// ────────────────────────────────────────────────────────────────────────────
template<int DIM, int Q1D, int DID, typename QT, typename IT, typename OT>
inline void AddDerivativeApplyTranspose()
{
using ker = LocalQFImpl::DerivativeApplyTranspose<DID, QT, IT, OT>;
if constexpr (Q1D <= 8)
{
ker::DerivativeApplyTransposeLO::template Specialization<DIM, Q1D>::Add();
}
else
{
ker::DerivativeApplyTransposeHO::template Specialization<DIM, Q1D>::Add();
}
}
// ────────────────────────────────────────────────────────────────────────────
template<int DIM, int Q1D, typename QT, typename IT, typename OT,
typename derivative_ids_t = std::index_sequence<>>
inline void AddLocalSpecializations()
{
AddAction<DIM, Q1D, QT, IT, OT>();
for_constexpr([&](auto i)
{
using derivative_id = decltype(i);
AddDerivativeAction<DIM, Q1D, derivative_id::value, QT, IT, OT>();
AddDerivativeSetup<DIM, Q1D, derivative_id::value, QT, IT, OT>();
AddDerivativeApply<DIM, Q1D, derivative_id::value, QT, IT, OT>();
AddDerivativeApplyTranspose<DIM, Q1D, derivative_id::value, QT, IT, OT>();
}, derivative_ids_t{});
}
}
@@ -0,0 +1,274 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../../util.hpp"
#ifdef MFEM_USE_ENZYME
namespace mfem::future
{
template <typename T> struct function_traits;
template <typename R, typename C, typename... Args>
struct function_traits<R (C::*)(Args...) const>
{
using primal_return_type = R;
using args_tuple = tuple<Args...>;
static constexpr size_t arity = sizeof...(Args);
};
// Component count and writable counterpart of a per-point argument, which
// is either a tensor or a plain scalar.
template <typename Arg> struct qp_traits
{
static_assert(std::is_arithmetic_v<Arg>,
"per-point arguments must be tensors or scalars");
using view_type = Arg;
static constexpr int components = 1;
};
template <typename T, int... Sizes> struct qp_traits<tensor<T, Sizes...>>
{
using view_type = tensor<std::remove_const_t<T>, Sizes...>;
static constexpr int components = (Sizes * ... * 1);
};
template <typename... T1s, typename... T2s>
constexpr tuple<T1s..., T2s...> concat_tuples(tuple<T1s...>, tuple<T2s...>);
// RevDiff: computes the full gradient of a pointwise qfunction at a single
// quadrature point using one Enzyme reverse-mode (autodiff) call.
//
// operator()(args...) takes all qfunction input primals followed by one
// writable gradient output per Active input (same shape as that input).
// The qfunction's own output is not passed; Enzyme writes it to stack
// scratch (enzyme_dupnoneed).
//
// A single __enzyme_autodiff call with the output adjoint seeded to 1
// yields all gradient blocks simultaneously — O(1) calls per point
// regardless of input size, vs O(ncomp) for forward mode.
//
// operator() is MFEM_HOST_DEVICE, stateless and allocation-free.
template <typename Func, typename InputActivityTuple,
typename OutputActivityTuple>
struct RevDiff
{
using traits = function_traits<decltype(&Func::operator())>;
using args_tuple = typename traits::args_tuple;
using activity =
decltype(concat_tuples(InputActivityTuple{}, OutputActivityTuple{}));
static constexpr size_t arity = traits::arity;
static constexpr size_t num_inputs = tuple_size<InputActivityTuple>::value;
static_assert(std::is_void_v<typename traits::primal_return_type>,
"RevDiff only supports primal functions with void return type");
static_assert(tuple_size<activity>::value == arity,
"Number of input and output activity tags must match function "
"arity");
template <size_t I>
static constexpr bool is_active =
std::is_same_v<tuple_element_t<I, activity>, Active>;
// Index of the single Active tag in [Lo, Hi), or arity if not exactly one.
template <size_t Lo, size_t Hi, size_t... Is>
static constexpr size_t find_single_active(std::index_sequence<Is...>)
{
size_t idx = arity, count = 0;
(((Is >= Lo && Is < Hi && is_active<Is>) ? (idx = Is, ++count) : size_t{0}),
...);
return count == 1 ? idx : arity;
}
// Number of Active inputs and their argument indices, in ascending order.
// A qfunction may have several Active inputs at once: e.g. a field's value
// u and its gradient dudx both feed the output and both must be
// differentiated (the chain-rule contraction with the value/gradient shape
// functions then happens at the FE-operator level). We produce one gradient
// block, d(output)/d(input), per Active input — each computed with the other
// Active inputs frozen, so they come out as isolated partials.
template <size_t... Is>
static constexpr size_t count_active_inputs(std::index_sequence<Is...>)
{
return ((Is < num_inputs && is_active<Is> ? size_t{1} : size_t{0}) + ...);
}
static constexpr size_t num_active_inputs =
count_active_inputs(std::make_index_sequence<arity> {});
template <size_t... Is>
static constexpr std::array<size_t, num_active_inputs>
collect_active_inputs(std::index_sequence<Is...>)
{
std::array<size_t, num_active_inputs> idx{};
size_t j = 0;
(((Is < num_inputs && is_active<Is>) ? (idx[j++] = Is) : size_t{0}), ...);
return idx;
}
static constexpr auto active_inputs =
collect_active_inputs(std::make_index_sequence<arity> {});
// Slot index of argument I in the active_inputs array (compile-time).
template <size_t I>
static constexpr size_t slot_of = []() constexpr -> size_t
{
for (size_t s = 0; s < num_active_inputs; s++)
if (active_inputs[s] == I) { return s; }
return num_active_inputs;
}();
static constexpr size_t active_output =
find_single_active<num_inputs, arity>(std::make_index_sequence<arity> {});
static_assert(active_output < arity,
"gradient mode requires exactly one Active output");
static_assert(num_active_inputs >= 1,
"gradient mode requires at least one Active input");
static_assert(tuple_size<OutputActivityTuple>::value == 1,
"gradient mode requires exactly one (scalar) output");
using output_type =
std::decay_t<tuple_element_t<active_output, args_tuple>>;
using output_view = typename qp_traits<output_type>::view_type;
static_assert(qp_traits<output_type>::components == 1,
"gradient output requires a scalar output");
template <size_t I>
using primal_arg_t = tuple_element_t<I, args_tuple>;
template <size_t S>
using grad_arg_t =
typename qp_traits<std::decay_t<tuple_element_t<active_inputs[S], args_tuple>>>::view_type
&;
template <size_t... Is, size_t... Ss>
static FunctionSignature<void(primal_arg_t<Is>..., grad_arg_t<Ss>...)>
signature_impl(std::index_sequence<Is...>, std::index_sequence<Ss...>);
using signature = decltype(signature_impl(std::make_index_sequence<num_inputs> {},
std::make_index_sequence<num_active_inputs> {}));
// Plain function with the qfunction's exact (reference) signature so it can
// be handed to Enzyme as a function pointer.
template <size_t... Is>
MFEM_HOST_DEVICE static __attribute__((always_inline)) void
static_call(tuple_element_t<Is, args_tuple>... args)
{
Func{}(args...);
}
template <size_t... Is>
static constexpr auto fn_ptr(std::index_sequence<Is...>)
{
return &static_call<Is...>;
}
static constexpr auto fn = fn_ptr(std::make_index_sequence<arity> {});
// Recursive builder of the per-argument reverse-mode enzyme call.
template <size_t I = 0, typename AllPtrs, typename... Built>
MFEM_HOST_DEVICE static __attribute__((always_inline)) void
call_enzyme_rev(AllPtrs &ptrs, output_view &scratch, output_view &adjoint,
Built... built)
{
if constexpr (I == arity)
{
__enzyme_autodiff<void>(fn, built...);
}
else if constexpr (I == active_output)
{
// Output: primal written to scratch (unused), adjoint seeded to 1.
call_enzyme_rev<I + 1>(ptrs, scratch, adjoint, built...,
enzyme_dupnoneed, &scratch, &adjoint);
}
else if constexpr (is_active<I>)
{
// Active input: gradient accumulates into its grad-output slot.
call_enzyme_rev<I + 1>(
ptrs, scratch, adjoint, built..., enzyme_dup,
mfem::future::get<int(I)>(ptrs),
mfem::future::get<int(num_inputs + slot_of<I>)>(ptrs));
}
else
{
// Const input: primal only, no shadow.
call_enzyme_rev<I + 1>(ptrs, scratch, adjoint, built...,
enzyme_const, mfem::future::get<int(I)>(ptrs));
}
}
// Zero all gradient outputs before the enzyme call (Enzyme accumulates).
template <typename AllPtrs, size_t... Ss>
MFEM_HOST_DEVICE static
__attribute__((always_inline)) void zero_grads(
AllPtrs &ptrs,
std::index_sequence<Ss...>)
{
((*mfem::future::get<int(num_inputs + Ss)>(ptrs) =
std::decay_t<decltype(*mfem::future::get<int(num_inputs + Ss)>(ptrs))> {}),
...);
}
// Called once per quadrature point. Arguments are, in order:
// * the primal value of every qfunction input (active and const), then
// * one gradient output per Active input (ascending index order), each
// shaped like its Active input.
// The qfunction's own output slot is not passed; Enzyme writes it to stack
// scratch (enzyme_dupnoneed). A single __enzyme_autodiff call yields all
// gradient blocks simultaneously.
template <typename... Args>
MFEM_HOST_DEVICE __attribute__((always_inline)) void operator()(
Args &&...args) const
{
static_assert(sizeof...(Args) == num_inputs + num_active_inputs,
"expected one primal per input plus one gradient output per "
"Active input");
auto ptrs = mfem::future::make_tuple(&args...);
zero_grads(ptrs, std::make_index_sequence<num_active_inputs> {});
output_view out_scratch{};
output_view out_adjoint{1.0}; // seed: d(output)/d(output) = 1
call_enzyme_rev(ptrs, out_scratch, out_adjoint);
}
static __attribute__((always_inline)) void print() { print_impl(std::make_index_sequence<arity> {}); }
template <size_t... Is> static __attribute__((always_inline)) void print_impl(
std::index_sequence<Is...>)
{
mfem::out << "__enzyme_autodiff<void>(fptr";
(([&]
{
auto name = get_type_name<tuple_element_t<Is, args_tuple>>();
if constexpr (Is == active_output)
mfem::out << ", enzyme_dupnoneed, " << name << ", adjoint=1";
else if constexpr (is_active<Is>)
mfem::out << ", enzyme_dup, " << name << ", grad out";
else
{
mfem::out << ", enzyme_const, " << name;
}
}()),
...);
mfem::out << ")\n";
}
};
template <typename Func, typename InputActivityTuple, typename OutputActivityTuple>
struct create_function_signature<RevDiff<Func, InputActivityTuple, OutputActivityTuple>>
{
using type = typename
RevDiff<Func, InputActivityTuple, OutputActivityTuple>::signature;
};
} // namespace mfem::future
#endif // MFEM_USE_ENZYME
+622
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@@ -0,0 +1,622 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
// Compile-time quadrature argument metadata for local q-functions
#include "../../../../linalg/tensor.hpp"
#include "../../integrator_ctx.hpp"
#include "../../util.hpp"
#include <algorithm>
#include <array>
#include <cstddef>
#include <type_traits>
namespace mfem::future
{
///////////////////////////////////////////////////////////////////////////////
template <typename T>
MFEM_HOST_DEVICE auto qf_store_value(const T &v)
{
if constexpr (is_dual_number<T>::value) { return v.value; }
else { return v; }
}
template <typename T>
MFEM_HOST_DEVICE auto qf_store_gradient(const T &v)
{
if constexpr (is_dual_number<T>::value) { return v.gradient; }
else { return v; }
}
///////////////////////////////////////////////////////////////////////////////
/// True when quadrature-point values of `T` carry dual-number derivatives
template <typename T>
struct qf_param_uses_dual : std::false_type {};
template <typename S, int... Is>
struct qf_param_uses_dual<tensor<S, Is...>> : is_dual_number<S> {};
template <typename V, typename G>
struct qf_param_uses_dual<dual<V, G>> : std::true_type {};
template <typename T>
constexpr bool qf_param_uses_dual_v = qf_param_uses_dual<T>::value;
///////////////////////////////////////////////////////////////////////////////
/// Static shape for one decayed q-function parameter type
template <typename T>
struct qf_param_shape
{
static constexpr int rank = 0;
static constexpr std::array<int, 0> extents {};
};
template <typename scalar_t, int... Is>
struct qf_param_shape<tensor<scalar_t, Is...>>
{
static constexpr int rank = sizeof...(Is);
static constexpr std::array<int, sizeof...(Is)> extents {{Is...}};
};
template <typename scalar_t>
struct qf_param_shape<tensor<scalar_t>>
{
static constexpr int rank = 0;
static constexpr std::array<int, 0> extents {};
};
template <>
struct qf_param_shape<real_t>
{
static constexpr int rank = 0;
static constexpr std::array<int, 0> extents {};
};
///////////////////////////////////////////////////////////////////////////////
/// Type used in quadrature registers for parameter
template <typename T>
struct qf_reg_t { using type = T; };
template <>
struct qf_reg_t<real_t> { using type = tensor<real_t>; };
///////////////////////////////////////////////////////////////////////////////
/// Per-parameter tensor info for slot `I` in the decayed q-function parameter tuple
template <typename qfunc_t, std::size_t I>
struct qf_param_slot
{
using qf_signature = typename get_function_signature<qfunc_t>::type;
using qf_param_ts = typename qf_signature::parameter_ts;
using qf_raw_param_t = typename tuple_element<I, qf_param_ts>::type;
using qf_decay_param_t =
std::remove_cv_t<std::remove_reference_t<qf_raw_param_t>>;
using qf_reg_param_t = typename qf_reg_t<qf_decay_param_t>::type;
static constexpr auto extents = qf_param_shape<qf_decay_param_t>::extents;
};
///////////////////////////////////////////////////////////////////////////////
/// Builds a register-bank tuple covering the q-function parameter slots
/// `[K0, N)`. `K` is the recursion cursor and starts at `K0`; the resulting
/// tuple is indexed from 0, so a bank starting at `K0 > 0` has its slot indices
/// rebased by `-K0` relative to the q-function parameter list.
template <
typename backend_t,
typename qfunc_t, typename inputs_t, typename outputs_t, int MQ1,
std::size_t K0, std::size_t K, std::size_t N, typename... Acc>
struct build_args_reg_tuple_impl;
template <
typename backend_t,
typename qfunc_t, typename inputs_t, typename outputs_t, int MQ1,
std::size_t K0, std::size_t N, typename... Acc>
struct build_args_reg_tuple_impl<backend_t, qfunc_t, inputs_t, outputs_t, MQ1, K0, N, N, Acc...>
{
using type = tuple<Acc...>;
static_assert(sizeof...(Acc) == N - K0);
static_assert(sizeof...(Acc) <= 9);
};
template <
typename backend_t,
typename qfunc_t, typename inputs_t, typename outputs_t, int MQ1,
std::size_t K0, std::size_t K, std::size_t N, typename... Acc>
struct build_args_reg_tuple_impl
{
using qf_reg_param_t = typename qf_param_slot<qfunc_t, K>::qf_reg_param_t;
using R = typename backend_t::template QReg<qf_reg_param_t>;
using type = typename build_args_reg_tuple_impl<backend_t, qfunc_t, inputs_t,
outputs_t, MQ1, K0, K + 1, N, Acc..., R>::type;
};
template <
typename backend_t,
typename qfunc_t, typename inputs_t, typename outputs_t, int MQ1>
using args_reg_t = typename build_args_reg_tuple_impl<backend_t, qfunc_t,
inputs_t, outputs_t, MQ1, 0, 0,
tuple_size<inputs_t>::value + tuple_size<outputs_t>::value>::type;
/// Register bank covering q-function inputs only (same types as first
/// `n_inputs` slots of args_reg_t). Used where shadow / tangent paths never
/// touch output parameter registers.
template <
typename backend_t,
typename qfunc_t, typename inputs_t, typename outputs_t, int MQ1>
using input_args_reg_t = typename build_args_reg_tuple_impl<backend_t, qfunc_t,
inputs_t, outputs_t, MQ1, 0, 0,
tuple_size<inputs_t>::value>::type;
/// Register bank covering q-function outputs only (same types as the slots
/// from `n_inputs` onward in args_reg_t). Used where the primal / trial inputs
/// live in a separate bank and only the test registers are integrated.
/// Slot `o` of this bank is q-function parameter `n_inputs + o`.
template <
typename backend_t,
typename qfunc_t, typename inputs_t, typename outputs_t, int MQ1>
using output_args_reg_t = typename build_args_reg_tuple_impl<backend_t, qfunc_t,
inputs_t, outputs_t, MQ1,
tuple_size<inputs_t>::value,
tuple_size<inputs_t>::value,
tuple_size<inputs_t>::value + tuple_size<outputs_t>::value>::type;
template <typename ARG>
MFEM_HOST_DEVICE inline void qf_set_flat_value(ARG &a, int c, real_t v)
{
if constexpr (std::is_same_v<ARG, real_t>) { MFEM_CONTRACT_VAR(c); a = v; }
else if constexpr (is_dual_number<ARG>::value)
{
MFEM_CONTRACT_VAR(c);
a.value = v;
}
else
{
constexpr int RNK = qf_param_shape<ARG>::rank;
constexpr bool D = qf_param_uses_dual_v<ARG>;
if constexpr (RNK == 0)
{
if constexpr (D) { a(0).value = v; }
else { a(0) = v; }
}
else if constexpr (RNK == 1)
{
if constexpr (D) { a(c).value = v; }
else { a(c) = v; }
}
else
{
constexpr int e0 = qf_param_shape<ARG>::extents[0];
if constexpr (D) { a(c % e0, c / e0).value = v; }
else { a(c % e0, c / e0) = v; }
}
}
}
template <typename ARG>
MFEM_HOST_DEVICE inline void qf_set_flat_gradient(ARG &a, int c, real_t v)
{
if constexpr (is_dual_number<ARG>::value)
{
MFEM_CONTRACT_VAR(c);
a.gradient = v;
}
else if constexpr (qf_param_uses_dual_v<ARG>)
{
constexpr int RNK = qf_param_shape<ARG>::rank;
if constexpr (RNK == 0) { a(0).gradient = v; }
else if constexpr (RNK == 1) { a(c).gradient = v; }
else
{
constexpr int e0 = qf_param_shape<ARG>::extents[0];
a(c % e0, c / e0).gradient = v;
}
}
else
{
// Non-dual argument (e.g. Weight): never an active trial direction.
MFEM_CONTRACT_VAR(a);
MFEM_CONTRACT_VAR(c);
MFEM_CONTRACT_VAR(v);
}
}
///////////////////////////////////////////////////////////////////////////////
/// Two-index component access for a q-function argument.
///
/// `i` indexes vdim, `k` indexes the operator dimension, matching the
/// column-major packing `c = i + extents[0]*k` of the flat accessors above.
/// Prefer these wherever the caller already has both indices: the flat form
/// would have to undo the packing with an integer division, which is expensive
/// on device and pointless when `(i, k)` are right there.
///
/// The runtime extents of the callers agree with the static extents of `ARG`:
/// for rank 2, `vdim == extents[0]` and `op_dim == extents[1]`; for rank 1 one
/// of the two is 1 and the corresponding index is always 0, so `a(i + k)`
/// selects the right component; for rank 0 both are 1.
template <typename ARG>
MFEM_HOST_DEVICE inline real_t qf_value_at(const ARG &a, int i, int k)
{
if constexpr (std::is_same_v<ARG, real_t> || is_dual_number<ARG>::value)
{
MFEM_CONTRACT_VAR(i);
MFEM_CONTRACT_VAR(k);
return qf_store_value(a);
}
else
{
constexpr int RNK = qf_param_shape<ARG>::rank;
if constexpr (RNK == 0)
{
MFEM_CONTRACT_VAR(i);
MFEM_CONTRACT_VAR(k);
return qf_store_value(a(0));
}
else if constexpr (RNK == 1) { return qf_store_value(a(i + k)); }
else { return qf_store_value(a(i, k)); }
}
}
template <typename ARG>
MFEM_HOST_DEVICE inline real_t qf_gradient_at(const ARG &a, int i, int k)
{
if constexpr (is_dual_number<ARG>::value)
{
MFEM_CONTRACT_VAR(i);
MFEM_CONTRACT_VAR(k);
return a.gradient;
}
else if constexpr (qf_param_uses_dual_v<ARG>)
{
constexpr int RNK = qf_param_shape<ARG>::rank;
if constexpr (RNK == 0)
{
MFEM_CONTRACT_VAR(i);
MFEM_CONTRACT_VAR(k);
return a(0).gradient;
}
else if constexpr (RNK == 1) { return a(i + k).gradient; }
else { return a(i, k).gradient; }
}
else
{
// Non-dual argument carries no tangent: its derivative contribution is 0.
MFEM_CONTRACT_VAR(a);
MFEM_CONTRACT_VAR(i);
MFEM_CONTRACT_VAR(k);
return real_t(0);
}
}
template <typename ARG>
MFEM_HOST_DEVICE inline void qf_set_value_at(ARG &a, int i, int k, real_t v)
{
if constexpr (std::is_same_v<ARG, real_t>)
{
MFEM_CONTRACT_VAR(i);
MFEM_CONTRACT_VAR(k);
a = v;
}
else if constexpr (is_dual_number<ARG>::value)
{
MFEM_CONTRACT_VAR(i);
MFEM_CONTRACT_VAR(k);
a.value = v;
}
else
{
constexpr int RNK = qf_param_shape<ARG>::rank;
constexpr bool D = qf_param_uses_dual_v<ARG>;
if constexpr (RNK == 0)
{
MFEM_CONTRACT_VAR(i);
MFEM_CONTRACT_VAR(k);
if constexpr (D) { a(0).value = v; }
else { a(0) = v; }
}
else if constexpr (RNK == 1)
{
if constexpr (D) { a(i + k).value = v; }
else { a(i + k) = v; }
}
else
{
if constexpr (D) { a(i, k).value = v; }
else { a(i, k) = v; }
}
}
}
template <typename ARG>
MFEM_HOST_DEVICE inline void qf_set_gradient_at(ARG &a, int i, int k, real_t v)
{
if constexpr (is_dual_number<ARG>::value)
{
MFEM_CONTRACT_VAR(i);
MFEM_CONTRACT_VAR(k);
a.gradient = v;
}
else if constexpr (qf_param_uses_dual_v<ARG>)
{
constexpr int RNK = qf_param_shape<ARG>::rank;
if constexpr (RNK == 0)
{
MFEM_CONTRACT_VAR(i);
MFEM_CONTRACT_VAR(k);
a(0).gradient = v;
}
else if constexpr (RNK == 1) { a(i + k).gradient = v; }
else { a(i, k).gradient = v; }
}
else
{
// Non-dual argument (e.g. Weight): never an active trial direction.
MFEM_CONTRACT_VAR(a);
MFEM_CONTRACT_VAR(i);
MFEM_CONTRACT_VAR(k);
MFEM_CONTRACT_VAR(v);
}
}
///////////////////////////////////////////////////////////////////////////////
/// Maps each FOP slot to unionfds indices — used with dtqs / create_dtq_maps
template<typename C, typename T>
const auto create_union_field_map_for_dtq(C& ctx, T& io)
{
using FE = Entity::Element;
return create_descriptors_to_fields_map<FE>(ctx.unionfds, io);
}
/// **`xe[i]`** slot per input FOP — indices into **`ctx.infds`** (`SIZE_MAX` for Weight).
template<typename C, typename T>
const auto create_input_vector_map(C& ctx, T& io)
{
using FE = Entity::Element;
return create_descriptors_to_fields_map<FE>(ctx.infds, io);
}
/// **`ye[i]`** slot per output FOP — indices into **`ctx.outfds`**.
template<typename C, typename T>
const auto create_output_vector_map(C& ctx, T& io)
{
using FE = Entity::Element;
return create_descriptors_to_fields_map<FE>(ctx.outfds, io);
}
template<typename C>
const auto make_dtqs(C& ctx)
{
std::vector<const DofToQuad*> dtq_vec;
dtq_vec.reserve(ctx.unionfds.size());
constexpr auto dtq_mode = DofToQuad::Mode::TENSOR;
for (const auto &field: ctx.unionfds)
{
auto dtq = GetDofToQuad<Entity::Element>(field, ctx.ir, dtq_mode);
dtq_vec.emplace_back(dtq);
}
return dtq_vec;
}
///////////////////////////////////////////////////////////////////////////////
template<typename Tuple>
constexpr auto get_vdim(const Tuple& fields)
{
return future::apply([](const auto&... f)
{
return std::array<int, sizeof...(f)> {f.vdim...};
}, fields);
}
template<typename Tuple>
constexpr auto get_B(const Tuple& fields)
{
return future::apply([](const auto&... f)
{
return std::array<const real_t*, sizeof...(f)> {f.B...};
}, fields);
}
template<typename Tuple>
constexpr auto get_G(const Tuple& fields)
{
return future::apply([](const auto&... f)
{
return std::array<const real_t*, sizeof...(f)> {f.G...};
}, fields);
}
template<typename Tuple>
constexpr auto get_D1D(const Tuple& fields)
{
return future::apply([](const auto&... f)
{
return std::array<int, sizeof...(f)> {f.B.GetShape()[2]...};
}, fields);
}
template<typename Tuple>
constexpr auto get_Q1D(const Tuple& fields)
{
return future::apply([](const auto&... f)
{
return std::array<int, sizeof...(f)> {f.B.GetShape()[0]...};
}, fields);
}
///////////////////////////////////////////////////////////////////////////////
/// Per-output FOP layout metadata (shared by derivative setup / apply kernels).
template<typename outputs_t>
constexpr auto compute_out_qp_size(const outputs_t &outs)
{
constexpr std::size_t n_outputs = tuple_size<outputs_t>::value;
std::array<int, n_outputs> sizes{};
for_constexpr<n_outputs>([&](auto o) { sizes[o] = get<o>(outs).size_on_qp; });
return sizes;
}
template<typename outputs_t>
constexpr auto compute_out_op_dim(const outputs_t &outs)
{
constexpr std::size_t n_outputs = tuple_size<outputs_t>::value;
std::array<int, n_outputs> op{};
for_constexpr<n_outputs>([&](auto o)
{
op[o] = get<o>(outs).size_on_qp / get<o>(outs).vdim;
});
return op;
}
template<std::size_t N>
constexpr std::array<int, N> compute_out_offsets(
const std::array<int, N> &vdim,
const std::array<int, N> &op_dim)
{
std::array<int, N> offsets{};
offsets[0] = 0;
for (std::size_t o = 1; o < N; o++)
{
offsets[o] = offsets[o - 1] + vdim[o - 1] * op_dim[o - 1];
}
return offsets;
}
template<std::size_t N>
constexpr std::array<int, N> compute_out_flat_offsets(
const std::array<int, N> &vdim,
const std::array<int, N> &op_dim,
const int num_qp)
{
std::array<int, N> offsets{};
offsets[0] = 0;
for (std::size_t o = 1; o < N; o++)
{
offsets[o] = offsets[o - 1] + vdim[o - 1] * op_dim[o - 1] * num_qp;
}
return offsets;
}
template<typename inputs_t>
const auto compute_input_is_dependent(const inputs_t &ins, int deriv_id)
{
auto dependency_map = make_dependency_map(ins);
auto it = dependency_map.find(deriv_id);
MFEM_ASSERT(it != dependency_map.end(),
"Derivative ID not found in dependency map");
return it->second;
}
template<typename inputs_t>
constexpr int compute_trial_vdim(const inputs_t &ins, int deriv_id)
{
constexpr std::size_t n_inputs = tuple_size<inputs_t>::value;
int v = 1;
for_constexpr<n_inputs>([&](auto i)
{
if (get<i>(ins).GetFieldId() == deriv_id) { v = get<i>(ins).vdim; }
});
return v;
}
template<typename inputs_t>
constexpr int compute_total_trial_op_dim(
const inputs_t &ins,
const std::array<bool, tuple_size<inputs_t>::value> &dep,
const std::array<int, tuple_size<inputs_t>::value> &size_on_qp)
{
constexpr std::size_t n_inputs = tuple_size<inputs_t>::value;
int total = 0;
for_constexpr<n_inputs>([&](auto i)
{
if (dep[i]) { total += size_on_qp[i] / get<i>(ins).vdim; }
});
return total;
}
inline size_t find_union_field_index(const IntegratorContext &ctx, int field_id)
{
for (size_t uf = 0; uf < ctx.unionfds.size(); uf++)
{
if (static_cast<int>(ctx.unionfds[uf].id) == field_id) { return uf; }
}
return SIZE_MAX;
}
inline size_t find_infd_index(const IntegratorContext &ctx, int field_id)
{
for (size_t i = 0; i < ctx.infds.size(); i++)
{
if (static_cast<int>(ctx.infds[i].id) == field_id) { return i; }
}
return SIZE_MAX;
}
template<typename entity_t = Entity::Element>
inline int compute_element_dof_sz(
const FieldDescriptor &fd,
int num_entities,
ElementDofOrdering ordering)
{
auto R = get_restriction<entity_t>(fd, ordering);
MFEM_ASSERT(R != nullptr, "LocalQF: missing element restriction");
return num_entities ? (R->Height() / num_entities) : 0;
}
// ────────────────────────────────────────────────────────────────────────────
// Number of threads per 1D direction to launch the kernel with
template <typename inputs_t, typename outputs_t,
std::size_t N_in, std::size_t N_out>
inline int compute_kernel_thread_1d(
const int q1d,
const std::array<int, N_in> &in_d1d,
const std::array<int, N_out> &out_d1d)
{
int t1d = q1d;
for_constexpr<N_in>([&](auto ic)
{
using FOP = tuple_element_t<ic.value, inputs_t>;
if constexpr (is_value_fop_v<FOP> || is_gradient_fop_v<FOP>)
{
t1d = std::max(t1d, in_d1d[ic.value]);
}
});
for_constexpr<N_out>([&](auto ic)
{
using FOP = tuple_element_t<ic.value, outputs_t>;
if constexpr (is_value_fop_v<FOP> || is_gradient_fop_v<FOP>)
{
t1d = std::max(t1d, out_d1d[ic.value]);
}
});
return t1d;
}
// Inputs-only variant: used by kernels whose outputs are written at qp
template <typename inputs_t, std::size_t N_in>
inline int compute_kernel_thread_1d(
const int q1d,
const std::array<int, N_in> &in_d1d)
{
int t1d = q1d;
for_constexpr<N_in>([&](auto ic)
{
using FOP = tuple_element_t<ic.value, inputs_t>;
if constexpr (is_value_fop_v<FOP> || is_gradient_fop_v<FOP>)
{
t1d = std::max(t1d, in_d1d[ic.value]);
}
});
return t1d;
}
} // namespace mfem::future
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// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "mfem.hpp"
#include "../tuple.hpp"
#include <memory>
#include <type_traits>
#include <vector>
namespace mfem::future
{
// Scratch storage and q-function shadow helpers for dFEM backends. The bank
// supports two scratch kinds:
// - quadrature-point scratch: real_t buffers sized as NQ * components_per_qp,
// - global scratch: one tuple of qfunction-local temporaries, independent of
// NQ, used for values such as flags, scalars, or small Vector workspaces.
template <typename... GlobalScratchTypes>
struct ScratchBank
{
//=================================
///<--- Global scratch utilities.
//=================================
using GlobalScratchTuple = tuple<GlobalScratchTypes...>;
template <typename T>
static T MakeGlobalScratchShadow(const T &)
{
return T {};
}
static Vector MakeGlobalScratchShadow(const Vector &primal)
{
Vector shadow(primal.Size());
shadow.UseDevice(true);
shadow = 0.0;
return shadow;
}
template <typename Tuple, size_t... Is>
static auto MakeGlobalScratchShadowTuple(const Tuple &primal,
std::index_sequence<Is...>)
{
return make_tuple(MakeGlobalScratchShadow(get<Is>(primal))...);
}
template <typename Tuple>
static auto MakeGlobalScratchShadowTuple(const Tuple &primal)
{
return MakeGlobalScratchShadowTuple(
primal, std::make_index_sequence<tuple_size<Tuple>::value> {});
}
//===========================
///<--- Scratch objects
//===========================
mutable GlobalScratchTuple global;
int nq = 0;
std::vector<int> components;
std::vector<int> sizes;
std::vector<std::shared_ptr<Vector>> owned;
std::vector<real_t *> ptrs;
//===========================
///<--- Setter methods
//===========================
void SetScratch(const int nq_,
std::initializer_list<int> components_per_qp = {1})
{
SetScratch(nq_, std::vector<int>(components_per_qp));
}
void SetScratch(const int nq_, const std::vector<int> &components_per_qp)
{
nq = nq_;
components.clear();
sizes.clear();
owned.clear();
ptrs.clear();
for (int component_count : components_per_qp)
{
AddScratch(component_count);
}
}
void AddScratch(const int components_per_qp = 1)
{
MFEM_VERIFY(nq > 0, "SetScratch must be called before AddScratch");
MFEM_VERIFY(components_per_qp > 0,
"scratch components per quadrature point must be positive");
owned.push_back(std::make_shared<Vector>());
Vector &scratch = *owned.back();
const int size = components_per_qp * nq;
scratch.SetSize(size);
scratch.UseDevice(true);
scratch = 0.0;
components.push_back(components_per_qp);
sizes.push_back(scratch.Size());
ptrs.push_back(scratch.ReadWrite());
}
void SetGlobalScratch(const GlobalScratchTuple &global_)
{
global = global_;
}
//===========================
///<--- Getter methods
//===========================
real_t *GetScratchPointer(const int i) const { return ptrs[i]; }
real_t *operator[](const int i) const { return ptrs[i]; }
Vector &GetScratchVector(const int i) const { return *owned[i]; }
template <int I>
auto &GetGlobalScratch() const
{
return get<I>(global);
}
//===========================
///<--- Utils methods
//===========================
void CloneScratchLayoutTo(ScratchBank &shadow) const
{
shadow.SetScratch(nq, components);
shadow.SetGlobalScratch(MakeGlobalScratchShadowTuple(global));
}
int Size() const { return static_cast<int>(ptrs.size()); }
};
// Shared base for Q-functions that use ScratchBank and need a matching scratch
// shadow for forward differentiation.
template <typename... GlobalScratchTypes>
struct QFWithScratch
{
using GlobalScratchTuple = tuple<GlobalScratchTypes...>;
int nq = 0;
ScratchBank<GlobalScratchTypes...> scratch;
void SetScratch(const int nq_,
std::initializer_list<int> components_per_qp = {1})
{
nq = nq_;
scratch.SetScratch(nq, components_per_qp);
}
void SetScratch(const int nq_, const std::vector<int> &components_per_qp)
{
nq = nq_;
scratch.SetScratch(nq, components_per_qp);
}
void SetScratch(const int nq_, const int num_scratch_elem,
const int components_per_qp = 1)
{
nq = nq_;
scratch.SetScratch(nq,
std::vector<int>(num_scratch_elem, components_per_qp));
}
void SetGlobalScratch(const GlobalScratchTuple &global_scratch_)
{
scratch.SetGlobalScratch(global_scratch_);
}
Vector &GetScratchVector(const int i) const
{
return scratch.GetScratchVector(i);
}
real_t *GetScratchPointer(const int i) const
{
return scratch.GetScratchPointer(i);
}
template <int I>
auto &GetGlobalScratch() const
{
return scratch.template GetGlobalScratch<I>();
}
void CloneScratchLayoutTo(QFWithScratch &shadow) const
{
shadow.nq = nq;
scratch.CloneScratchLayoutTo(shadow.scratch);
}
QFWithScratch CreateShadow() const
{
QFWithScratch shadow;
CloneScratchLayoutTo(shadow);
return shadow;
}
};
using QFWithScratchType = QFWithScratch<>;
using QFWithGlobalScratchType = QFWithScratch<bool, real_t, Vector>;
namespace detail
{
template <typename T>
struct qfunc_uses_scratch
{
private:
template <typename... GlobalScratchTypes>
static std::true_type Test(const QFWithScratch<GlobalScratchTypes...> *);
static std::false_type Test(...);
public:
static constexpr bool value = decltype(Test(
static_cast<std::remove_cv_t<std::remove_reference_t<T>> *>(nullptr)))::value;
};
template <typename T>
inline constexpr bool qfunc_uses_scratch_v =
qfunc_uses_scratch<T>::value;
struct unused_qfunc_shadow { };
template <typename qfunc_t, bool uses_scratch>
struct qfunc_shadow_type
{
using type = unused_qfunc_shadow;
};
template <typename qfunc_t>
struct qfunc_shadow_type<qfunc_t, true>
{
using type = decltype(std::declval<const qfunc_t &>().CreateShadow());
};
template <typename qfunc_t>
using qfunc_shadow_t = typename qfunc_shadow_type<qfunc_t,
qfunc_uses_scratch_v<qfunc_t>>::type;
// Create a persistent q-function shadow if the q-function uses scratch, otherwise return an empty struct.
template <typename qfunc_t>
inline qfunc_shadow_t<qfunc_t> MakeQFunctionShadowStorage(
const qfunc_t &qfunc)
{
if constexpr (qfunc_uses_scratch_v<qfunc_t>)
{
return qfunc.CreateShadow();
}
else
{
MFEM_CONTRACT_VAR(qfunc);
return {};
}
}
} // namespace detail
}
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+362 -19
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@@ -11,44 +11,387 @@
#include "doperator.hpp"
#include <algorithm>
#ifdef MFEM_USE_MPI
using namespace mfem;
using namespace mfem::future;
void DifferentiableOperator::SetParameters(std::vector<Vector *> p) const
namespace
{
MFEM_ASSERT(parameters.size() == p.size(),
"number of parameters doesn't match descriptors");
for (size_t i = 0; i < parameters.size(); i++)
int GetTotalTrueVSize(const std::vector<FieldDescriptor> &fds)
{
int size = 0;
for (const auto &fd : fds)
{
p[i]->Read();
parameters_l[i] = *p[i];
size += mfem::future::GetTrueVSize(fd);
}
return size;
}
using DerivativeActionMap =
std::map<size_t, std::vector<derivative_action_t>>;
using DerivativeSetupMap =
std::map<size_t, std::vector<derivative_setup_t>>;
using DerivativeFieldMap =
std::map<size_t, std::vector<FieldDescriptor>>;
using SparseAssemblyMap =
std::map<size_t,
std::vector<assemble_derivative_sparsematrix_callback_t>>;
using HypreAssemblyMap =
std::map<size_t,
std::vector<assemble_derivative_hypreparmatrix_callback_t>>;
using DiagonalAssemblyMap =
std::map<size_t, std::vector<assemble_diagonal_callback_t>>;
using SecondDerivativeActionMap =
std::map<second_derivative_key_t, std::vector<derivative_action_t>>;
using SecondDerivativeSetupMap =
std::map<second_derivative_key_t, std::vector<derivative_setup_t>>;
using SecondDerivativeFieldMap =
std::map<second_derivative_key_t, std::vector<FieldDescriptor>>;
using SecondSparseAssemblyMap =
std::map<second_derivative_key_t,
std::vector<assemble_derivative_sparsematrix_callback_t>>;
using SecondHypreAssemblyMap =
std::map<second_derivative_key_t,
std::vector<assemble_derivative_hypreparmatrix_callback_t>>;
using SecondDiagonalAssemblyMap =
std::map<second_derivative_key_t, std::vector<assemble_diagonal_callback_t>>;
template <typename map_t>
const typename map_t::mapped_type &FindOrDefault(
const map_t &map, const typename map_t::key_type &id,
const typename map_t::mapped_type &fallback)
{
const auto it = map.find(id);
return it == map.end() ? fallback : it->second;
}
template <typename map_t>
typename map_t::mapped_type FindOrEmpty(
const map_t &map, const typename map_t::key_type &id)
{
const auto it = map.find(id);
return it == map.end() ? typename map_t::mapped_type{} : it->second;
}
const std::vector<derivative_action_t> &SelectActionCallbacks(
const std::vector<derivative_action_t> &direct_actions,
const DerivativeActionMap &cached_actions,
size_t derivative_id,
bool use_cached_setup)
{
if (use_cached_setup)
{
const auto it_apply = cached_actions.find(derivative_id);
if (it_apply != cached_actions.end() && !it_apply->second.empty())
{
return it_apply->second;
}
}
return direct_actions;
}
struct DerivativeCallbackSet
{
const DerivativeActionMap &actions;
const DerivativeActionMap &cached_actions;
const DerivativeActionMap &transpose_actions;
const DerivativeFieldMap &outfds;
const SparseAssemblyMap &assemble_sparse;
const HypreAssemblyMap &assemble_hypre;
const DiagonalAssemblyMap &assemble_diagonal;
const DerivativeSetupMap &setup;
const char *missing_action_message;
};
struct SecondDerivativeCallbackSet
{
const SecondDerivativeActionMap &actions;
const SecondDerivativeActionMap &cached_actions;
const SecondDerivativeActionMap &transpose_actions;
const SecondDerivativeFieldMap &outfds;
const SecondSparseAssemblyMap &assemble_sparse;
const SecondHypreAssemblyMap &assemble_hypre;
const SecondDiagonalAssemblyMap &assemble_diagonal;
const SecondDerivativeSetupMap &setup;
const char *missing_action_message;
};
template <typename vector_t>
std::shared_ptr<DerivativeOperator> MakeStatefulDerivativeOperator(
size_t derivative_id,
const vector_t &x,
const std::vector<FieldDescriptor> &infds,
const std::vector<FieldDescriptor> &default_outfds,
const DerivativeCallbackSet &callbacks,
bool use_cached_setup,
bool lvector_mode,
bool functional_gradient = false)
{
const auto it_action = callbacks.actions.find(derivative_id);
MFEM_ASSERT(it_action != callbacks.actions.end(),
callbacks.missing_action_message << derivative_id);
const size_t dfidx = FindIdx(derivative_id, infds);
const auto &doutfds =
FindOrDefault(callbacks.outfds, derivative_id, default_outfds);
const auto &mult_callbacks =
SelectActionCallbacks(it_action->second, callbacks.cached_actions,
derivative_id, use_cached_setup);
return std::make_shared<DerivativeOperator>(
GetTotalTrueVSize(doutfds),
GetTrueVSize(infds[dfidx]),
mult_callbacks,
FindOrEmpty(callbacks.transpose_actions, derivative_id),
infds[dfidx],
x,
infds,
doutfds,
FindOrEmpty(callbacks.assemble_sparse, derivative_id),
FindOrEmpty(callbacks.assemble_hypre, derivative_id),
FindOrEmpty(callbacks.assemble_diagonal, derivative_id),
FindOrEmpty(callbacks.setup, derivative_id),
lvector_mode,
functional_gradient);
}
const std::vector<derivative_action_t> &SelectSecondDerivativeActionCallbacks(
const std::vector<derivative_action_t> &direct_actions,
const SecondDerivativeActionMap &cached_actions,
second_derivative_key_t derivative_key,
bool use_cached_setup)
{
if (use_cached_setup)
{
const auto it_apply = cached_actions.find(derivative_key);
if (it_apply != cached_actions.end() && !it_apply->second.empty())
{
return it_apply->second;
}
}
return direct_actions;
}
template <typename vector_t>
std::shared_ptr<DerivativeOperator> MakeStatefulSecondDerivativeOperator(
size_t gradient_id,
size_t direction_id,
const vector_t &x,
const std::vector<FieldDescriptor> &infds,
const std::vector<FieldDescriptor> &default_outfds,
const SecondDerivativeCallbackSet &callbacks,
bool use_cached_setup,
bool lvector_mode)
{
const second_derivative_key_t derivative_key{gradient_id, direction_id};
const auto it_action = callbacks.actions.find(derivative_key);
MFEM_ASSERT(it_action != callbacks.actions.end(),
callbacks.missing_action_message << "(" << gradient_id << ", "
<< direction_id << ")");
const size_t dfidx = FindIdx(direction_id, infds);
const auto &doutfds =
FindOrDefault(callbacks.outfds, derivative_key, default_outfds);
const auto &mult_callbacks =
SelectSecondDerivativeActionCallbacks(
it_action->second, callbacks.cached_actions, derivative_key,
use_cached_setup);
return std::make_shared<DerivativeOperator>(
GetTotalTrueVSize(doutfds),
GetTrueVSize(infds[dfidx]),
mult_callbacks,
FindOrEmpty(callbacks.transpose_actions, derivative_key),
infds[dfidx],
x,
infds,
doutfds,
FindOrEmpty(callbacks.assemble_sparse, derivative_key),
FindOrEmpty(callbacks.assemble_hypre, derivative_key),
FindOrEmpty(callbacks.assemble_diagonal, derivative_key),
FindOrEmpty(callbacks.setup, derivative_key),
lvector_mode);
}
}
DifferentiableOperator::DifferentiableOperator(
const std::vector<FieldDescriptor> &solutions,
const std::vector<FieldDescriptor> &parameters,
const std::vector<FieldDescriptor> &infds,
const std::vector<FieldDescriptor> &outfds,
const ParMesh &mesh) :
Operator(),
mesh(mesh),
solutions(solutions),
parameters(parameters)
infds(infds),
outfds(outfds)
{
fields.resize(solutions.size() + parameters.size());
fields_e.resize(fields.size());
solutions_l.resize(solutions.size());
parameters_l.resize(parameters.size());
unionfds.clear();
unionfds.insert(unionfds.end(), infds.begin(), infds.end());
unionfds.insert(unionfds.end(), outfds.begin(), outfds.end());
std::sort(unionfds.begin(), unionfds.end());
auto last = std::unique(unionfds.begin(), unionfds.end());
unionfds.erase(last, unionfds.end());
for (size_t i = 0; i < solutions.size(); i++)
infields_l.resize(infds.size());
for (size_t i = 0; i < infds.size(); i++)
{
fields[i] = solutions[i];
infields_l[i] = new Vector(GetVSize(infds[i]));
}
for (size_t i = 0; i < parameters.size(); i++)
infields_e.resize(infds.size());
}
void DifferentiableOperator::SetMultLevel(MultLevel level)
{
mult_level = level;
}
void DifferentiableOperator::Mult(const Vector &x, Vector &y) const
{
MFEM_ASSERT(!action_callbacks.empty(),
"no integrators have been set");
MFEM_ASSERT(dynamic_cast<const BlockVector*>(&x),
"x needs to be a BlockVector");
MFEM_ASSERT(dynamic_cast<const BlockVector*>(&y),
"y needs to be a BlockVector");
const auto &bx = static_cast<const BlockVector &>(x);
auto &by = static_cast<BlockVector &>(y);
Mult(bx, by);
}
void DifferentiableOperator::DisableTensorProductStructure(bool disable)
{
use_tensor_product_structure = !disable;
}
std::shared_ptr<DerivativeOperator> DifferentiableOperator::GetDerivative(
size_t derivative_id, const Vector &x)
{
return MakeStatefulDerivativeOperator(
derivative_id, x, infds, outfds,
{
fields[i + solutions.size()] = parameters[i];
}
derivative_action_callbacks,
derivative_apply_callbacks,
daction_transpose_callbacks,
derivative_outfds,
assemble_derivative_sparsematrix_callbacks,
assemble_derivative_hypreparmatrix_callbacks,
assemble_diagonal_callbacks,
derivative_setup_callbacks,
"no derivative action has been found for ID "
},
true,
mult_level == MultLevel::LVECTOR,
IsFunctionalDerivative(derivative_id));
}
std::shared_ptr<DerivativeOperator> DifferentiableOperator::GetDerivative(
size_t derivative_id, const MultiVector &x, const bool use_cached_setup)
{
return MakeStatefulDerivativeOperator(
derivative_id, x, infds, outfds,
{
derivative_action_callbacks,
derivative_apply_callbacks,
daction_transpose_callbacks,
derivative_outfds,
assemble_derivative_sparsematrix_callbacks,
assemble_derivative_hypreparmatrix_callbacks,
assemble_diagonal_callbacks,
derivative_setup_callbacks,
"no derivative action has been found for ID "
},
use_cached_setup,
mult_level == MultLevel::LVECTOR,
IsFunctionalDerivative(derivative_id));
}
std::shared_ptr<DerivativeOperator> DifferentiableOperator::GetDerivative(
size_t derivative_id)
{
MFEM_ASSERT(has_functional_integrator,
"stateless GetDerivative is available only for functionals");
const auto it_action = derivative_action_callbacks.find(derivative_id);
MFEM_ASSERT(it_action != derivative_action_callbacks.end(),
"no derivative action has been found for ID " << derivative_id);
const size_t dfidx = FindIdx(derivative_id, infds);
const auto &doutfds =
FindOrDefault(derivative_outfds, derivative_id, outfds);
return std::make_shared<DerivativeOperator>(
GetTotalTrueVSize(doutfds),
GetTrueVSize(infds[dfidx]),
it_action->second,
infds,
doutfds);
}
std::shared_ptr<DerivativeOperator> DifferentiableOperator::GetSecondDerivative(
size_t derivative_id, const Vector &x)
{
return GetSecondDerivative(derivative_id, derivative_id, x);
}
std::shared_ptr<DerivativeOperator> DifferentiableOperator::GetSecondDerivative(
size_t gradient_id, size_t direction_id, const Vector &x)
{
MFEM_ASSERT(has_functional_integrator,
"second derivatives are available only for functionals");
return MakeStatefulSecondDerivativeOperator(
gradient_id, direction_id, x, infds, outfds,
{
second_derivative_action_callbacks,
second_derivative_apply_callbacks,
second_daction_transpose_callbacks,
second_derivative_outfds,
assemble_second_derivative_sparsematrix_callbacks,
assemble_second_derivative_hypreparmatrix_callbacks,
assemble_second_derivative_diagonal_callbacks,
second_derivative_setup_callbacks,
"no second derivative action has been found for ID "
},
false,
mult_level == MultLevel::LVECTOR);
}
std::shared_ptr<DerivativeOperator> DifferentiableOperator::GetSecondDerivative(
size_t derivative_id, const MultiVector &x, const bool use_cached_setup)
{
return GetSecondDerivative(derivative_id, derivative_id, x, use_cached_setup);
}
std::shared_ptr<DerivativeOperator> DifferentiableOperator::GetSecondDerivative(
size_t gradient_id, size_t direction_id, const MultiVector &x,
const bool use_cached_setup)
{
MFEM_ASSERT(has_functional_integrator,
"second derivatives are available only for functionals");
return MakeStatefulSecondDerivativeOperator(
gradient_id, direction_id, x, infds, outfds,
{
second_derivative_action_callbacks,
second_derivative_apply_callbacks,
second_daction_transpose_callbacks,
second_derivative_outfds,
assemble_second_derivative_sparsematrix_callbacks,
assemble_second_derivative_hypreparmatrix_callbacks,
assemble_second_derivative_diagonal_callbacks,
second_derivative_setup_callbacks,
"no second derivative action has been found for ID "
},
use_cached_setup,
mult_level == MultLevel::LVECTOR);
}
#endif // MFEM_USE_MPI
+1035 -957
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File diff suppressed because it is too large Load Diff
+64
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@@ -0,0 +1,64 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../fespace.hpp"
#include "../qspace.hpp"
#include "parameterspace.hpp"
namespace mfem::future
{
/// @brief FieldDescriptor struct
///
/// This struct is used to store information about a field.
struct FieldDescriptor
{
using data_variant_t =
std::variant<const FiniteElementSpace *,
const ParFiniteElementSpace *,
const VectorQuadratureSpace *,
const ParameterSpace *>;
/// Field ID
std::size_t id;
/// Field variant
data_variant_t data;
/// Default constructor
FieldDescriptor() :
id(SIZE_MAX), data(data_variant_t{}) {}
/// Constructor
template <typename T>
FieldDescriptor(std::size_t field_id, const T* v) :
id(field_id), data(v) {}
bool operator==(const FieldDescriptor& other) const
{
return id == other.id;
}
bool operator<(const FieldDescriptor& other) const
{
return id < other.id;
}
friend void swap(FieldDescriptor& a, FieldDescriptor& b)
{
using std::swap;
swap(a.id, b.id);
swap(a.data, b.data);
}
};
}
+73 -2
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@@ -10,6 +10,7 @@
// CONTRIBUTING.md for details.
#pragma once
#include <ostream>
#include <type_traits>
namespace mfem::future
@@ -74,6 +75,15 @@ struct is_identity_fop : std::false_type {};
template <int FIELD_ID>
struct is_identity_fop<Identity<FIELD_ID>> : std::true_type {};
template <typename T>
constexpr bool is_identity_fop_v = is_identity_fop<T>::value;
template <int FIELD_ID>
inline std::ostream& operator<<(std::ostream& out, Identity<FIELD_ID>)
{
return out << "Identity<" << FIELD_ID << ">";
}
/// @brief Weight FieldOperator.
///
/// This FieldOperator is used to signal that this field contains the quadrature
@@ -90,6 +100,14 @@ struct is_weight_fop : std::false_type {};
template <>
struct is_weight_fop<Weight> : std::true_type {};
template <typename T>
constexpr bool is_weight_fop_v = is_weight_fop<T>::value;
inline std::ostream& operator<<(std::ostream& out, Weight)
{
return out << "Weight";
}
/// @brief Value FieldOperator.
///
/// This FieldOperator is used to signal that the field contains the
@@ -101,11 +119,20 @@ public:
constexpr Value() : FieldOperator<FIELD_ID>() {};
};
template< typename T >
template <typename T>
struct is_value_fop : std::false_type {};
template <int T>
struct is_value_fop<Value<T>> : std::true_type {};
template <typename T>
constexpr bool is_value_fop_v = is_value_fop<T>::value;
template <int FIELD_ID>
struct is_value_fop<Value<FIELD_ID>> : std::true_type {};
inline std::ostream& operator<<(std::ostream& out, Value<FIELD_ID>)
{
return out << "Value<" << FIELD_ID << ">";
}
/// @brief Gradient FieldOperator.
///
@@ -124,6 +151,15 @@ struct is_gradient_fop : std::false_type {};
template <int FIELD_ID>
struct is_gradient_fop<Gradient<FIELD_ID>> : std::true_type {};
template <typename T>
constexpr bool is_gradient_fop_v = is_gradient_fop<T>::value;
template <int FIELD_ID>
inline std::ostream& operator<<(std::ostream& out, Gradient<FIELD_ID>)
{
return out << "Gradient<" << FIELD_ID << ">";
}
/// @brief Sum FieldOperator.
///
/// This FieldOperator is commonly used to signal that an output of a quadrature
@@ -141,4 +177,39 @@ struct is_sum_fop : std::false_type {};
template <int FIELD_ID>
struct is_sum_fop<Sum<FIELD_ID>> : std::true_type {};
template <typename T>
constexpr bool is_sum_fop_v = is_sum_fop<T>::value;
template <int FIELD_ID>
inline std::ostream& operator<<(std::ostream& out, Sum<FIELD_ID>)
{
return out << "Sum<" << FIELD_ID << ">";
}
/// @brief FunctionalValue FieldOperator.
///
/// This FieldOperator is commonly used to signal that an output of a quadrature
/// function should be summed.
template <int FIELD_ID = -1>
class FunctionalValue : public FieldOperator<FIELD_ID>
{
public:
constexpr FunctionalValue() : FieldOperator<FIELD_ID>() {};
};
template< typename T >
struct is_functionalvalue_fop : std::false_type {};
template <int FIELD_ID>
struct is_functionalvalue_fop<FunctionalValue<FIELD_ID>> : std::true_type {};
template <typename T>
constexpr bool is_functionalvalue_fop_v = is_functionalvalue_fop<T>::value;
template <int FIELD_ID>
inline std::ostream& operator<<(std::ostream& out, FunctionalValue<FIELD_ID>)
{
return out << "FunctionalValue<" << FIELD_ID << ">";
}
} // namespace mfem::future
-536
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@@ -1,536 +0,0 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "util.hpp"
namespace mfem::future
{
template <typename output_t>
MFEM_HOST_DEVICE
void map_quadrature_data_to_fields_impl(
DeviceTensor<2, real_t> &y,
const DeviceTensor<3, real_t> &f,
const output_t &output,
const DofToQuadMap &dtq)
{
[[maybe_unused]] auto B = dtq.B;
[[maybe_unused]] auto G = dtq.G;
// assuming the quadrature point residual has to "play nice with
// the test function"
if constexpr (is_value_fop<std::decay_t<output_t>>::value)
{
const auto [num_qp, cdim, num_dof] = B.GetShape();
const int vdim = output.vdim > 0 ? output.vdim : cdim ;
for (int dof = 0; dof < num_dof; dof++)
{
for (int vd = 0; vd < vdim; vd++)
{
real_t acc = 0.0;
for (int qp = 0; qp < num_qp; qp++)
{
acc += B(qp, 0, dof) * f(vd, 0, qp);
}
y(dof, vd) += acc;
}
}
}
else if constexpr (
is_gradient_fop<std::decay_t<output_t>>::value)
{
const auto [num_qp, dim, num_dof] = G.GetShape();
const int vdim = output.vdim;
for (int dof = 0; dof < num_dof; dof++)
{
for (int vd = 0; vd < vdim; vd++)
{
real_t acc = 0.0;
for (int d = 0; d < dim; d++)
{
for (int qp = 0; qp < num_qp; qp++)
{
acc += G(qp, d, dof) * f(vd, d, qp);
}
}
y(dof, vd) += acc;
}
}
}
else if constexpr (is_sum_fop<std::decay_t<output_t>>::value)
{
// This is the "integral over all quadrature points type" applying
// B = 1 s.t. B^T * C \in R^1.
const auto [num_qp, unused, unused1] = B.GetShape();
auto cc = Reshape(&f(0, 0, 0), num_qp);
for (int i = 0; i < num_qp; i++)
{
y(0, 0) += cc(i);
}
}
else if constexpr (is_identity_fop<std::decay_t<output_t>>::value)
{
const auto [num_qp, unused, num_dof] = B.GetShape();
const auto vdim = output.vdim;
auto cc = Reshape(&f(0, 0, 0), num_qp * vdim);
auto yy = Reshape(&y(0, 0), num_qp * vdim);
for (int i = 0; i < num_qp * vdim; i++)
{
yy(i) = cc(i);
}
}
else
{
MFEM_ABORT_KERNEL("quadrature data mapping to field is not implemented"
" for this field descriptor");
}
}
template <typename output_t>
MFEM_HOST_DEVICE
void map_quadrature_data_to_fields_tensor_impl_1d(
DeviceTensor<2, real_t> &y,
const DeviceTensor<3, real_t> &f,
const output_t &output,
const DofToQuadMap &dtq,
std::array<DeviceTensor<1>, 6> &scratch_mem)
{
[[maybe_unused]] auto B = dtq.B;
[[maybe_unused]] auto G = dtq.G;
if constexpr (is_value_fop<std::decay_t<output_t>>::value)
{
const auto [q1d, unused, d1d] = B.GetShape();
const int vdim = output.vdim;
const int test_dim = output.size_on_qp / vdim;
auto fqp = Reshape(&f(0, 0, 0), vdim, test_dim, q1d);
auto yd = Reshape(&y(0, 0), d1d, vdim);
for (int vd = 0; vd < vdim; vd++)
{
MFEM_FOREACH_THREAD(dx, x, d1d)
{
real_t acc = 0.0;
for (int qx = 0; qx < q1d; qx++)
{
acc += fqp(vd, 0, qx) * B(qx, 0, dx);
}
yd(dx, vd) = acc;
}
}
MFEM_SYNC_THREAD;
}
else if constexpr (is_gradient_fop<std::decay_t<output_t>>::value)
{
const auto [q1d, unused, d1d] = G.GetShape();
const int vdim = output.vdim;
const int test_dim = output.size_on_qp / vdim;
auto fqp = Reshape(&f(0, 0, 0), vdim, test_dim, q1d);
auto yd = Reshape(&y(0, 0), d1d, vdim);
for (int vd = 0; vd < vdim; vd++)
{
MFEM_FOREACH_THREAD(dx, x, d1d)
{
real_t acc = 0.0;
for (int qx = 0; qx < q1d; qx++)
{
acc += fqp(vd, 0, qx) * G(qx, 0, dx);
}
yd(dx, vd) = acc;
}
}
MFEM_SYNC_THREAD;
}
else if constexpr (is_identity_fop<std::decay_t<output_t>>::value)
{
const auto [q1d, unused, d1d] = B.GetShape();
auto fqp = Reshape(&f(0, 0, 0), output.size_on_qp, q1d);
auto yqp = Reshape(&y(0, 0), output.size_on_qp, q1d);
for (int sq = 0; sq < output.size_on_qp; sq++)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
yqp(sq, qx) = fqp(sq, qx);
}
MFEM_SYNC_THREAD;
}
}
else
{
MFEM_ABORT_KERNEL("quadrature data mapping to field is not implemented"
"for this field descriptor with sum factorization on"
" tensor product elements");
}
}
template <typename output_t>
MFEM_HOST_DEVICE
void map_quadrature_data_to_fields_tensor_impl_2d(
DeviceTensor<2, real_t> &y,
const DeviceTensor<3, real_t> &f,
const output_t &output,
const DofToQuadMap &dtq,
std::array<DeviceTensor<1>, 6> &scratch_mem)
{
[[maybe_unused]] auto B = dtq.B;
[[maybe_unused]] auto G = dtq.G;
if constexpr (is_value_fop<std::decay_t<output_t>>::value)
{
const auto [q1d, unused, d1d] = B.GetShape();
const int vdim = output.vdim;
const int test_dim = output.size_on_qp / vdim;
auto fqp = Reshape(&f(0, 0, 0), vdim, test_dim, q1d, q1d);
auto yd = Reshape(&y(0, 0), d1d, d1d, vdim);
auto s0 = Reshape(&scratch_mem[0](0), q1d, d1d);
for (int vd = 0; vd < vdim; vd++)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(dx, x, d1d)
{
real_t acc = 0.0;
for (int qx = 0; qx < q1d; qx++)
{
acc += fqp(vd, 0, qx, qy) * B(qx, 0, dx);
}
s0(qy, dx) = acc;
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD(dy, y, d1d)
{
MFEM_FOREACH_THREAD(dx, x, d1d)
{
real_t acc = 0.0;
for (int qy = 0; qy < q1d; qy++)
{
acc += s0(qy, dx) * B(qy, 0, dy);
}
yd(dx, dy, vd) += acc;
}
}
MFEM_SYNC_THREAD;
}
}
else if constexpr (is_gradient_fop<std::decay_t<output_t>>::value)
{
const auto [q1d, unused, d1d] = G.GetShape();
const int vdim = output.vdim;
const int test_dim = output.size_on_qp / vdim;
auto fqp = Reshape(&f(0, 0, 0), vdim, test_dim, q1d, q1d);
auto yd = Reshape(&y(0, 0), d1d, d1d, vdim);
auto s0 = Reshape(&scratch_mem[0](0), q1d, d1d);
auto s1 = Reshape(&scratch_mem[1](0), q1d, d1d);
for (int vd = 0; vd < vdim; vd++)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(dx, x, d1d)
{
real_t uv[2] = {0.0, 0.0};
for (int qx = 0; qx < q1d; qx++)
{
uv[0] += fqp(vd, 0, qx, qy) * G(qx, 0, dx);
uv[1] += fqp(vd, 1, qx, qy) * B(qx, 0, dx);
}
s0(qy, dx) = uv[0];
s1(qy, dx) = uv[1];
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD(dy, y, d1d)
{
MFEM_FOREACH_THREAD(dx, x, d1d)
{
real_t uv[2] = {0.0, 0.0};
for (int qy = 0; qy < q1d; qy++)
{
uv[0] += s0(qy, dx) * B(qy, 0, dy);
uv[1] += s1(qy, dx) * G(qy, 0, dy);
}
yd(dx, dy, vd) += uv[0] + uv[1];
}
}
MFEM_SYNC_THREAD;
}
}
else if constexpr (is_identity_fop<std::decay_t<output_t>>::value)
{
const auto [q1d, unused, d1d] = B.GetShape();
// // TODO: Check if this is the right fix for all cases
// auto fqp = Reshape(&f(0, 0, 0), output.size_on_qp, q1d);
// auto yqp = Reshape(&y(0, 0), output.size_on_qp, q1d);
// for (int sq = 0; sq < output.size_on_qp; sq++)
// {
// MFEM_FOREACH_THREAD(qx, x, q1d)
// {
// yqp(sq, qx) = fqp(sq, qx);
// }
// MFEM_SYNC_THREAD;
// }
auto fqp = Reshape(&f(0, 0, 0), output.size_on_qp, q1d, q1d);
auto yqp = Reshape(&y(0, 0), output.size_on_qp, q1d, q1d);
for (int sq = 0; sq < output.size_on_qp; sq++)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
yqp(sq, qx, qy) = fqp(sq, qx, qy);
}
}
MFEM_SYNC_THREAD;
}
}
else
{
MFEM_ABORT_KERNEL("quadrature data mapping to field is not implemented"
" for this field descriptor with sum factorization on"
" tensor product elements");
}
}
template <typename output_t>
MFEM_HOST_DEVICE
void map_quadrature_data_to_fields_tensor_impl_3d(
DeviceTensor<2, real_t> &y,
const DeviceTensor<3, real_t> &f,
const output_t &output,
const DofToQuadMap &dtq,
std::array<DeviceTensor<1>, 6> &scratch_mem)
{
[[maybe_unused]] auto B = dtq.B;
[[maybe_unused]] auto G = dtq.G;
if constexpr (is_value_fop<std::decay_t<output_t>>::value)
{
const auto [q1d, unused, d1d] = B.GetShape();
const int vdim = output.vdim;
const int test_dim = output.size_on_qp / vdim;
auto fqp = Reshape(&f(0, 0, 0), vdim, test_dim, q1d, q1d, q1d);
auto yd = Reshape(&y(0, 0), d1d, d1d, d1d, vdim);
auto s0 = Reshape(&scratch_mem[0](0), q1d, q1d, d1d);
auto s1 = Reshape(&scratch_mem[1](0), q1d, d1d, d1d);
for (int vd = 0; vd < vdim; vd++)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(dx, x, d1d)
{
MFEM_FOREACH_THREAD(qz, z, q1d)
{
real_t acc = 0.0;
for (int qx = 0; qx < q1d; qx++)
{
acc += fqp(vd, 0, qx, qy, qz) * B(qx, 0, dx);
}
s0(qz, qy, dx) = acc;
}
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD(dy, y, d1d)
{
MFEM_FOREACH_THREAD(dx, x, d1d)
{
MFEM_FOREACH_THREAD(qz, z, q1d)
{
real_t acc = 0.0;
for (int qy = 0; qy < q1d; qy++)
{
acc += s0(qz, qy, dx) * B(qy, 0, dy);
}
s1(qz, dy, dx) = acc;
}
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD(dy, y, d1d)
{
MFEM_FOREACH_THREAD(dx, x, d1d)
{
MFEM_FOREACH_THREAD(dz, z, d1d)
{
real_t acc = 0.0;
for (int qz = 0; qz < q1d; qz++)
{
acc += s1(qz, dy, dx) * B(qz, 0, dz);
}
yd(dx, dy, dz, vd) += acc;
}
}
}
MFEM_SYNC_THREAD;
}
}
else if constexpr (is_gradient_fop<std::decay_t<output_t>>::value)
{
const auto [q1d, unused, d1d] = G.GetShape();
const int vdim = output.vdim;
const int test_dim = output.size_on_qp / vdim;
auto fqp = Reshape(&f(0, 0, 0), vdim, test_dim, q1d, q1d, q1d);
auto yd = Reshape(&y(0, 0), d1d, d1d, d1d, vdim);
auto s0 = Reshape(&scratch_mem[0](0), q1d, q1d, d1d);
auto s1 = Reshape(&scratch_mem[1](0), q1d, q1d, d1d);
auto s2 = Reshape(&scratch_mem[2](0), q1d, q1d, d1d);
auto s3 = Reshape(&scratch_mem[3](0), q1d, d1d, d1d);
auto s4 = Reshape(&scratch_mem[4](0), q1d, d1d, d1d);
auto s5 = Reshape(&scratch_mem[5](0), q1d, d1d, d1d);
for (int vd = 0; vd < vdim; vd++)
{
MFEM_FOREACH_THREAD(qz, z, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(dx, x, d1d)
{
real_t uvw[3] = {0.0, 0.0, 0.0};
for (int qx = 0; qx < q1d; qx++)
{
uvw[0] += fqp(vd, 0, qx, qy, qz) * G(qx, 0, dx);
uvw[1] += fqp(vd, 1, qx, qy, qz) * B(qx, 0, dx);
uvw[2] += fqp(vd, 2, qx, qy, qz) * B(qx, 0, dx);
}
s0(qz, qy, dx) = uvw[0];
s1(qz, qy, dx) = uvw[1];
s2(qz, qy, dx) = uvw[2];
}
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD(qz, z, q1d)
{
MFEM_FOREACH_THREAD(dy, y, d1d)
{
MFEM_FOREACH_THREAD(dx, x, d1d)
{
real_t uvw[3] = {0.0, 0.0, 0.0};
for (int qy = 0; qy < q1d; qy++)
{
uvw[0] += s0(qz, qy, dx) * B(qy, 0, dy);
uvw[1] += s1(qz, qy, dx) * G(qy, 0, dy);
uvw[2] += s2(qz, qy, dx) * B(qy, 0, dy);
}
s3(qz, dy, dx) = uvw[0];
s4(qz, dy, dx) = uvw[1];
s5(qz, dy, dx) = uvw[2];
}
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD(dz, z, d1d)
{
MFEM_FOREACH_THREAD(dy, y, d1d)
{
MFEM_FOREACH_THREAD(dx, x, d1d)
{
real_t uvw[3] = {0.0, 0.0, 0.0};
for (int qz = 0; qz < q1d; qz++)
{
uvw[0] += s3(qz, dy, dx) * B(qz, 0, dz);
uvw[1] += s4(qz, dy, dx) * B(qz, 0, dz);
uvw[2] += s5(qz, dy, dx) * G(qz, 0, dz);
}
yd(dx, dy, dz, vd) += uvw[0] + uvw[1] + uvw[2];
}
}
}
MFEM_SYNC_THREAD;
}
}
else if constexpr (is_identity_fop<std::decay_t<output_t>>::value)
{
const auto [q1d, unused, d1d] = B.GetShape();
auto fqp = Reshape(&f(0, 0, 0), output.size_on_qp, q1d, q1d, q1d);
auto yqp = Reshape(&y(0, 0), output.size_on_qp, q1d, q1d, q1d);
for (int sq = 0; sq < output.size_on_qp; sq++)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(qz, z, q1d)
{
yqp(sq, qx, qy, qz) = fqp(sq, qx, qy, qz);
}
}
}
MFEM_SYNC_THREAD;
}
}
else
{
MFEM_ABORT_KERNEL("quadrature data mapping to field is not implemented"
" for this field descriptor with sum factorization on"
" tensor product elements");
}
}
template <typename output_t>
MFEM_HOST_DEVICE
void map_quadrature_data_to_fields(
DeviceTensor<2, real_t> &y,
const DeviceTensor<3, real_t> &f,
const output_t &output,
const DofToQuadMap &dtq,
std::array<DeviceTensor<1>, 6> &scratch_mem,
const int &dimension,
const bool &use_sum_factorization)
{
if (use_sum_factorization)
{
if (dimension == 1)
{
map_quadrature_data_to_fields_tensor_impl_1d(y, f, output, dtq, scratch_mem);
}
else if (dimension == 2)
{
map_quadrature_data_to_fields_tensor_impl_2d(y, f, output, dtq, scratch_mem);
}
else if (dimension == 3)
{
map_quadrature_data_to_fields_tensor_impl_3d(y, f, output, dtq, scratch_mem);
}
else { MFEM_ABORT_KERNEL("dimension not supported"); }
}
else
{
map_quadrature_data_to_fields_impl(y, f, output, dtq);
}
}
} // namespace mfem::future
+37
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@@ -0,0 +1,37 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include <typeindex>
#include <unordered_map>
#include <vector>
#include "../../general/array.hpp"
#include "fielddescriptor.hpp"
namespace mfem::future
{
struct IntegratorContext
{
const ParMesh &mesh;
const Array<int> *elem_attr;
Array<int> attr;
const int nentities;
const std::vector<FieldDescriptor> &infds;
const std::vector<FieldDescriptor> &outfds;
const std::vector<FieldDescriptor> &unionfds;
const IntegrationRule &ir;
std::unordered_map<std::type_index, std::vector<int>> &in_qlayouts;
std::unordered_map<std::type_index, std::vector<int>> &out_qlayouts;
};
}
-678
View File
@@ -1,678 +0,0 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "util.hpp"
namespace mfem::future
{
template <typename field_operator_t>
MFEM_HOST_DEVICE inline
void map_field_to_quadrature_data_tensor_product_3d(
DeviceTensor<2> &field_qp,
const DofToQuadMap &dtq,
const DeviceTensor<1> &field_e,
const field_operator_t &input,
const DeviceTensor<1, const real_t> &integration_weights,
const std::array<DeviceTensor<1>, 6> &scratch_mem)
{
[[maybe_unused]] auto B = dtq.B;
[[maybe_unused]] auto G = dtq.G;
if constexpr (is_value_fop<std::decay_t<field_operator_t>>::value)
{
auto [q1d, unused, d1d] = B.GetShape();
const int vdim = input.vdim;
const auto field = Reshape(&field_e[0], d1d, d1d, d1d, vdim);
auto fqp = Reshape(&field_qp[0], vdim, q1d, q1d, q1d);
auto s0 = Reshape(&scratch_mem[0](0), d1d, d1d, q1d);
auto s1 = Reshape(&scratch_mem[1](0), d1d, q1d, q1d);
for (int vd = 0; vd < vdim; vd++)
{
MFEM_FOREACH_THREAD(dz, z, d1d)
{
MFEM_FOREACH_THREAD(dy, y, d1d)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
real_t acc = 0.0;
for (int dx = 0; dx < d1d; dx++)
{
acc += B(qx, 0, dx) * field(dx, dy, dz, vd);
}
s0(dz, dy, qx) = acc;
}
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD(dz, z, d1d)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
real_t acc = 0.0;
for (int dy = 0; dy < d1d; dy++)
{
acc += s0(dz, dy, qx) * B(qy, 0, dy);
}
s1(dz, qy, qx) = acc;
}
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD(qz, z, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
real_t acc = 0.0;
for (int dz = 0; dz < d1d; dz++)
{
acc += s1(dz, qy, qx) * B(qz, 0, dz);
}
fqp(vd, qx, qy, qz) = acc;
}
}
}
MFEM_SYNC_THREAD;
}
}
else if constexpr (
is_gradient_fop<std::decay_t<field_operator_t>>::value)
{
const auto [q1d, unused, d1d] = B.GetShape();
const int vdim = input.vdim;
const int dim = input.dim;
const auto field = Reshape(&field_e[0], d1d, d1d, d1d, vdim);
auto fqp = Reshape(&field_qp[0], vdim, dim, q1d, q1d, q1d);
auto s0 = Reshape(&scratch_mem[0](0), d1d, d1d, q1d);
auto s1 = Reshape(&scratch_mem[1](0), d1d, d1d, q1d);
auto s2 = Reshape(&scratch_mem[2](0), d1d, q1d, q1d);
auto s3 = Reshape(&scratch_mem[3](0), d1d, q1d, q1d);
auto s4 = Reshape(&scratch_mem[4](0), d1d, q1d, q1d);
for (int vd = 0; vd < vdim; vd++)
{
MFEM_FOREACH_THREAD(dz, z, d1d)
{
MFEM_FOREACH_THREAD(dy, y, d1d)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
real_t uv[2] = {0.0, 0.0};
for (int dx = 0; dx < d1d; dx++)
{
const real_t f = field(dx, dy, dz, vd);
uv[0] += f * B(qx, 0, dx);
uv[1] += f * G(qx, 0, dx);
}
s0(dz, dy, qx) = uv[0];
s1(dz, dy, qx) = uv[1];
}
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD(dz, z, d1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
real_t uvw[3] = {0.0, 0.0, 0.0};
for (int dy = 0; dy < d1d; dy++)
{
const real_t s0i = s0(dz, dy, qx);
uvw[0] += s1(dz, dy, qx) * B(qy, 0, dy);
uvw[1] += s0i * G(qy, 0, dy);
uvw[2] += s0i * B(qy, 0, dy);
}
s2(dz, qy, qx) = uvw[0];
s3(dz, qy, qx) = uvw[1];
s4(dz, qy, qx) = uvw[2];
}
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD(qz, z, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
real_t uvw[3] = {0.0, 0.0, 0.0};
for (int dz = 0; dz < d1d; dz++)
{
uvw[0] += s2(dz, qy, qx) * B(qz, 0, dz);
uvw[1] += s3(dz, qy, qx) * B(qz, 0, dz);
uvw[2] += s4(dz, qy, qx) * G(qz, 0, dz);
}
fqp(vd, 0, qx, qy, qz) = uvw[0];
fqp(vd, 1, qx, qy, qz) = uvw[1];
fqp(vd, 2, qx, qy, qz) = uvw[2];
}
}
}
MFEM_SYNC_THREAD;
}
}
// TODO: Create separate function for clarity
else if constexpr (
std::is_same_v<std::decay_t<field_operator_t>, Weight>)
{
const int num_qp = integration_weights.GetShape()[0];
// TODO: eeek
const int q1d = (int)floor(std::pow(num_qp, 1.0/input.dim) + 0.5);
auto w = Reshape(&integration_weights[0], q1d, q1d, q1d);
auto f = Reshape(&field_qp[0], q1d, q1d, q1d);
MFEM_FOREACH_THREAD(qx, x, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(qz, z, q1d)
{
f(qx, qy, qz) = w(qx, qy, qz);
}
}
}
MFEM_SYNC_THREAD;
}
else if constexpr (is_identity_fop<std::decay_t<field_operator_t>>::value)
{
const int q1d = B.GetShape()[0];
auto field = Reshape(&field_e[0], input.size_on_qp, q1d * q1d * q1d);
field_qp = field;
}
else
{
static_assert(dfem::always_false<std::decay_t<field_operator_t>>,
"can't map field to quadrature data");
}
}
template <typename field_operator_t>
MFEM_HOST_DEVICE inline
void map_field_to_quadrature_data_tensor_product_2d(
DeviceTensor<2> &field_qp,
const DofToQuadMap &dtq,
const DeviceTensor<1> &field_e,
const field_operator_t &input,
const DeviceTensor<1, const real_t> &integration_weights,
const std::array<DeviceTensor<1>, 6> &scratch_mem)
{
[[maybe_unused]] auto B = dtq.B;
[[maybe_unused]] auto G = dtq.G;
if constexpr (is_value_fop<std::decay_t<field_operator_t>>::value)
{
auto [q1d, unused, d1d] = B.GetShape();
const int vdim = input.vdim;
const auto field = Reshape(&field_e[0], d1d, d1d, vdim);
auto fqp = Reshape(&field_qp[0], vdim, q1d, q1d);
auto s0 = Reshape(&scratch_mem[0](0), d1d, q1d);
for (int vd = 0; vd < vdim; vd++)
{
MFEM_FOREACH_THREAD(dy, y, d1d)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
real_t acc = 0.0;
for (int dx = 0; dx < d1d; dx++)
{
acc += B(qx, 0, dx) * field(dx, dy, vd);
}
s0(dy, qx) = acc;
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD(qx, x, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
real_t acc = 0.0;
for (int dy = 0; dy < d1d; dy++)
{
acc += s0(dy, qx) * B(qy, 0, dy);
}
fqp(vd, qx, qy) = acc;
}
}
MFEM_SYNC_THREAD;
}
}
else if constexpr (
is_gradient_fop<std::decay_t<field_operator_t>>::value)
{
const auto [q1d, unused, d1d] = B.GetShape();
const int vdim = input.vdim;
const int dim = input.dim;
const auto field = Reshape(&field_e[0], d1d, d1d, vdim);
auto fqp = Reshape(&field_qp[0], vdim, dim, q1d, q1d);
auto s0 = Reshape(&scratch_mem[0](0), d1d, q1d);
auto s1 = Reshape(&scratch_mem[1](0), d1d, q1d);
for (int vd = 0; vd < vdim; vd++)
{
MFEM_FOREACH_THREAD(dy, y, d1d)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
real_t uv[2] = {0.0, 0.0};
for (int dx = 0; dx < d1d; dx++)
{
const real_t f = field(dx, dy, vd);
uv[0] += f * B(qx, 0, dx);
uv[1] += f * G(qx, 0, dx);
}
s0(dy, qx) = uv[0];
s1(dy, qx) = uv[1];
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
real_t uv[2] = {0.0, 0.0};
for (int dy = 0; dy < d1d; dy++)
{
const real_t s0i = s0(dy, qx);
uv[0] += s1(dy, qx) * B(qy, 0, dy);
uv[1] += s0i * G(qy, 0, dy);
}
fqp(vd, 0, qx, qy) = uv[0];
fqp(vd, 1, qx, qy) = uv[1];
}
}
MFEM_SYNC_THREAD;
}
}
// TODO: Create separate function for clarity
else if constexpr (
std::is_same_v<std::decay_t<field_operator_t>, Weight>)
{
const int num_qp = integration_weights.GetShape()[0];
// TODO: eeek
const int q1d = (int)floor(std::pow(num_qp, 1.0/input.dim) + 0.5);
auto w = Reshape(&integration_weights[0], q1d, q1d);
auto f = Reshape(&field_qp[0], q1d, q1d);
MFEM_FOREACH_THREAD(qx, x, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
f(qx, qy) = w(qx, qy);
}
}
MFEM_SYNC_THREAD;
}
else if constexpr (is_identity_fop<std::decay_t<field_operator_t>>::value)
{
const int q1d = B.GetShape()[0];
auto field = Reshape(&field_e[0], input.size_on_qp, q1d * q1d);
field_qp = field;
}
else
{
static_assert(dfem::always_false<std::decay_t<field_operator_t>>,
"can't map field to quadrature data");
}
}
template <typename field_operator_t>
MFEM_HOST_DEVICE inline
void map_field_to_quadrature_data_tensor_product_1d(
DeviceTensor<2> &field_qp,
const DofToQuadMap &dtq,
const DeviceTensor<1> &field_e,
const field_operator_t &input,
const DeviceTensor<1, const real_t> &integration_weights,
const std::array<DeviceTensor<1>, 6> &scratch_mem)
{
[[maybe_unused]] auto B = dtq.B;
[[maybe_unused]] auto G = dtq.G;
if constexpr (is_value_fop<std::decay_t<field_operator_t>>::value)
{
auto [q1d, unused, d1d] = B.GetShape();
const int vdim = input.vdim;
const auto field = Reshape(&field_e[0], d1d, vdim);
auto fqp = Reshape(&field_qp[0], vdim, q1d);
for (int vd = 0; vd < vdim; vd++)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
real_t acc = 0.0;
for (int dx = 0; dx < d1d; dx++)
{
acc += B(qx, 0, dx) * field(dx, vd);
}
fqp(vd, qx) = acc;
}
}
MFEM_SYNC_THREAD;
}
else if constexpr (
is_gradient_fop<std::decay_t<field_operator_t>>::value)
{
const auto [q1d, unused, d1d] = B.GetShape();
const int vdim = input.vdim;
const int dim = input.dim;
const auto field = Reshape(&field_e[0], d1d, vdim);
auto fqp = Reshape(&field_qp[0], vdim, dim, q1d);
for (int vd = 0; vd < vdim; vd++)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
real_t acc = 0.0;
for (int dx = 0; dx < d1d; dx++)
{
acc += G(qx, 0, dx) * field(dx, vd);
}
fqp(vd, 0, qx) = acc;
}
MFEM_SYNC_THREAD;
}
}
// TODO: Create separate function for clarity
else if constexpr (
std::is_same_v<std::decay_t<field_operator_t>, Weight>)
{
const int num_qp = integration_weights.GetShape()[0];
// TODO: eeek
const int q1d = (int)floor(std::pow(num_qp, 1.0/input.dim) + 0.5);
auto w = Reshape(&integration_weights[0], q1d);
auto f = Reshape(&field_qp[0], q1d);
MFEM_FOREACH_THREAD(qx, x, q1d)
{
f(qx) = w(qx);
}
MFEM_SYNC_THREAD;
}
else if constexpr (is_identity_fop<std::decay_t<field_operator_t>>::value)
{
const int q1d = B.GetShape()[0];
auto field = Reshape(&field_e[0], input.size_on_qp, q1d);
field_qp = field;
}
else
{
static_assert(dfem::always_false<std::decay_t<field_operator_t>>,
"can't map field to quadrature data");
}
}
template <typename field_operator_t>
MFEM_HOST_DEVICE
void map_field_to_quadrature_data(
DeviceTensor<2> field_qp,
const DofToQuadMap &dtq,
const DeviceTensor<1> &field_e,
const field_operator_t &input,
const DeviceTensor<1, const real_t> &integration_weights)
{
[[maybe_unused]] auto B = dtq.B;
[[maybe_unused]] auto G = dtq.G;
if constexpr (is_value_fop<field_operator_t>::value)
{
auto [num_qp, dim, num_dof] = B.GetShape();
const int vdim = input.vdim;
const auto field = Reshape(&field_e(0), num_dof, vdim);
for (int vd = 0; vd < vdim; vd++)
{
for (int qp = 0; qp < num_qp; qp++)
{
real_t acc = 0.0;
for (int dof = 0; dof < num_dof; dof++)
{
acc += B(qp, 0, dof) * field(dof, vd);
}
field_qp(vd, qp) = acc;
}
}
}
else if constexpr (is_gradient_fop<field_operator_t>::value)
{
const auto [num_qp, dim, num_dof] = G.GetShape();
const int vdim = input.vdim;
const auto field = Reshape(&field_e(0), num_dof, vdim);
auto f = Reshape(&field_qp[0], vdim, dim, num_qp);
for (int vd = 0; vd < vdim; vd++)
{
for (int qp = 0; qp < num_qp; qp++)
{
for (int d = 0; d < dim; d++)
{
real_t acc = 0.0;
for (int dof = 0; dof < num_dof; dof++)
{
acc += G(qp, d, dof) * field(dof, vd);
}
f(vd, d, qp) = acc;
}
}
}
}
else if constexpr (std::is_same_v<field_operator_t, Weight>)
{
const int num_qp = integration_weights.GetShape()[0];
auto f = Reshape(&field_qp[0], num_qp);
for (int qp = 0; qp < num_qp; qp++)
{
f(qp) = integration_weights(qp);
}
}
else if constexpr (is_identity_fop<field_operator_t>::value)
{
auto [num_qp, unused, num_dof] = B.GetShape();
const int size_on_qp = input.size_on_qp;
const auto field = Reshape(&field_e[0], size_on_qp * num_qp);
auto f = Reshape(&field_qp[0], size_on_qp * num_qp);
for (int i = 0; i < size_on_qp * num_qp; i++)
{
f(i) = field(i);
}
}
else
{
static_assert(dfem::always_false<field_operator_t>,
"can't map field to quadrature data");
}
}
template <typename field_operator_ts, size_t num_inputs, size_t num_fields>
MFEM_HOST_DEVICE inline
void map_fields_to_quadrature_data(
std::array<DeviceTensor<2>, num_inputs> &fields_qp,
const std::array<DeviceTensor<1>, num_fields> &fields_e,
const std::array<DofToQuadMap, num_inputs> &dtqmaps,
const std::array<size_t, num_inputs> &input_to_field,
const field_operator_ts &fops,
const DeviceTensor<1, const real_t> &integration_weights,
const std::array<DeviceTensor<1>, 6> &scratch_mem,
const int &dimension,
const bool &use_sum_factorization = false)
{
// When the input_to_field map returns -1, this means the requested input
// is the integration weight. Weights don't have a user defined field
// attached to them and we create a dummy field which is not accessed
// inside the functions it is passed to.
const auto dummy_field_weight = DeviceTensor<1>(nullptr, 0);
for_constexpr<num_inputs>([&](auto i)
{
const DeviceTensor<1> &field_e =
(input_to_field[i] == SIZE_MAX) ? dummy_field_weight :
fields_e[input_to_field[i]];
if (use_sum_factorization)
{
if (dimension == 1)
{
map_field_to_quadrature_data_tensor_product_1d(
fields_qp[i], dtqmaps[i], field_e, get<i>(fops),
integration_weights, scratch_mem);
}
else if (dimension == 2)
{
map_field_to_quadrature_data_tensor_product_2d(
fields_qp[i], dtqmaps[i], field_e, get<i>(fops),
integration_weights, scratch_mem);
}
else if (dimension == 3)
{
map_field_to_quadrature_data_tensor_product_3d(
fields_qp[i], dtqmaps[i], field_e, get<i>(fops),
integration_weights, scratch_mem);
}
else
{
#if !(defined(MFEM_USE_CUDA) || defined(MFEM_USE_HIP))
MFEM_ABORT("unsupported dimension");
#endif
}
}
else
{
map_field_to_quadrature_data(
fields_qp[i], dtqmaps[i], field_e, get<i>(fops),
integration_weights);
}
});
}
template <typename field_operator_t>
MFEM_HOST_DEVICE
void map_field_to_quadrature_data_conditional(
DeviceTensor<2> &field_qp,
const DeviceTensor<1> &field_e,
const DofToQuadMap &dtqmap,
field_operator_t &fop,
const DeviceTensor<1, const real_t> &integration_weights,
const std::array<DeviceTensor<1>, 6> &scratch_mem,
const bool &condition,
const int &dimension,
const bool &use_sum_factorization = false)
{
if (condition)
{
if (use_sum_factorization)
{
if (dimension == 1)
{
map_field_to_quadrature_data_tensor_product_1d(
field_qp, dtqmap, field_e, fop, integration_weights, scratch_mem);
}
else if (dimension == 2)
{
map_field_to_quadrature_data_tensor_product_2d(
field_qp, dtqmap, field_e, fop, integration_weights, scratch_mem);
}
else if (dimension == 3)
{
map_field_to_quadrature_data_tensor_product_3d(
field_qp, dtqmap, field_e, fop, integration_weights, scratch_mem);
}
}
else
{
map_field_to_quadrature_data(
field_qp, dtqmap, field_e, fop, integration_weights);
}
}
}
template <size_t num_fields, size_t num_inputs, typename field_operator_ts>
MFEM_HOST_DEVICE
void map_fields_to_quadrature_data_conditional(
std::array<DeviceTensor<2>, num_inputs> &fields_qp,
const std::array<DeviceTensor<1, const real_t>, num_fields> &fields_e,
const std::array<DofToQuadMap, num_inputs> &dtqmaps,
field_operator_ts fops,
const DeviceTensor<1, const real_t> &integration_weights,
const std::array<DeviceTensor<1>, 6> &scratch_mem,
const std::array<bool, num_inputs> &conditions,
const bool &use_sum_factorization = false)
{
for_constexpr<num_inputs>([&](auto i)
{
map_field_to_quadrature_data_conditional(
fields_qp[i], fields_e[i], dtqmaps[i], get<i>(fops), integration_weights,
scratch_mem, conditions[i], use_sum_factorization);
});
}
template <size_t num_inputs, typename field_operator_ts>
MFEM_HOST_DEVICE
void map_direction_to_quadrature_data_conditional(
std::array<DeviceTensor<2>, num_inputs> &directions_qp,
const DeviceTensor<1> &direction_e,
const std::array<DofToQuadMap, num_inputs> &dtqmaps,
field_operator_ts fops,
const DeviceTensor<1, const real_t> &integration_weights,
const std::array<DeviceTensor<1>, 6> &scratch_mem,
const std::array<bool, num_inputs> &conditions,
const int &dimension,
const bool &use_sum_factorization)
{
for_constexpr<num_inputs>([&](auto i)
{
if (conditions[i])
{
if (use_sum_factorization)
{
if (dimension == 1)
{
map_field_to_quadrature_data_tensor_product_1d(
directions_qp[i], dtqmaps[i], direction_e, get<i>(fops),
integration_weights, scratch_mem);
}
else if (dimension == 2)
{
map_field_to_quadrature_data_tensor_product_2d(
directions_qp[i], dtqmaps[i], direction_e, get<i>(fops),
integration_weights, scratch_mem);
}
else if (dimension == 3)
{
map_field_to_quadrature_data_tensor_product_3d(
directions_qp[i], dtqmaps[i], direction_e, get<i>(fops),
integration_weights, scratch_mem);
}
}
else
{
map_field_to_quadrature_data(
directions_qp[i], dtqmaps[i], direction_e, get<i>(fops),
integration_weights);
}
}
});
}
}
+8 -5
View File
@@ -20,7 +20,7 @@ namespace mfem::future
class ParameterSpace
{
public:
ParameterSpace(int vdim = 1) : vdim(vdim) {}
ParameterSpace(int vdim = 1) : vdim(vdim) { dtq.FE = nullptr; dtq.IntRule = nullptr; }
/// @brief Get vector dimension at each point
///
@@ -43,7 +43,7 @@ public:
/// Get spatial dimension
///
/// returns always 1.
int Dimension() const
constexpr int Dimension() const
{
return 1;
}
@@ -65,7 +65,7 @@ public:
/// It should not be used by a user.
///
/// returns identity by default that is lazy evaluated.
virtual const Operator* GetElementRestriction(ElementDofOrdering o) const
virtual const Operator* GetElementRestriction(ElementDofOrdering) const
{
if (!elem_restr)
{
@@ -74,11 +74,14 @@ public:
return elem_restr.get();
}
virtual const Operator* GetB() const = 0;
virtual const Operator* GetBt() const = 0;
protected:
int vdim;
DofToQuad dtq;
mutable std::unique_ptr<Operator> prolongation;
mutable std::unique_ptr<Operator> elem_restr;
mutable std::unique_ptr<Operator> prolongation, elem_restr, B, Bt;
};
/// @brief Uniform parameter space
-619
View File
@@ -1,619 +0,0 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "util.hpp"
#include "qfunction_transform.hpp"
namespace mfem::future
{
/// @brief Call a qfunction with the given parameters.
///
/// @param qfunc the qfunction to call.
/// @param input_shmem the input shared memory.
/// @param residual_shmem the residual shared memory.
/// @param rs_qp the size of the residual.
/// @param num_qp the number of quadrature points.
/// @param q1d the number of quadrature points in 1D.
/// @param dimension the spatial dimension.
/// @param use_sum_factorization whether to use sum factorization.
/// @tparam qf_param_ts the tuple type of the qfunction parameters.
template <
typename qf_param_ts,
typename qfunc_t,
std::size_t num_fields>
MFEM_HOST_DEVICE inline
void call_qfunction(
qfunc_t &qfunc,
const std::array<DeviceTensor<2>, num_fields> &input_shmem,
DeviceTensor<2> &residual_shmem,
const int &rs_qp,
const int &num_qp,
const int &q1d,
const int &dimension,
const bool &use_sum_factorization)
{
if (use_sum_factorization)
{
if (dimension == 1)
{
MFEM_FOREACH_THREAD_DIRECT(q, x, q1d)
{
auto qf_args = decay_tuple<qf_param_ts> {};
auto r = Reshape(&residual_shmem(0, q), rs_qp);
apply_kernel(r, qfunc, qf_args, input_shmem, q);
}
}
else if (dimension == 2)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
const int q = qx + q1d * qy;
auto qf_args = decay_tuple<qf_param_ts> {};
auto r = Reshape(&residual_shmem(0, q), rs_qp);
apply_kernel(r, qfunc, qf_args, input_shmem, q);
}
}
}
else if (dimension == 3)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qz, z, q1d)
{
const int q = qx + q1d * (qy + q1d * qz);
auto qf_args = decay_tuple<qf_param_ts> {};
auto r = Reshape(&residual_shmem(0, q), rs_qp);
apply_kernel(r, qfunc, qf_args, input_shmem, q);
}
}
}
}
else
{
#if !(defined(MFEM_USE_CUDA) || defined(MFEM_USE_HIP))
MFEM_ABORT("unsupported dimension for sum factorization");
#endif
}
MFEM_SYNC_THREAD;
}
else
{
MFEM_FOREACH_THREAD_DIRECT(q, x, num_qp)
{
auto qf_args = decay_tuple<qf_param_ts> {};
auto r = Reshape(&residual_shmem(0, q), rs_qp);
apply_kernel(r, qfunc, qf_args, input_shmem, q);
}
}
}
/// @brief Call a qfunction with the given parameters and
/// compute it's derivative action.
///
/// @param qfunc the qfunction to call.
/// @param input_shmem the input shared memory.
/// @param shadow_shmem the shadow shared memory.
/// @param residual_shmem the residual shared memory.
/// @param das_qp the size of the derivative action.
/// @param num_qp the number of quadrature points.
/// @param q1d the number of quadrature points in 1D.
/// @param dimension the spatial dimension.
/// @param use_sum_factorization whether to use sum factorization.
/// @tparam qf_param_ts the tuple type of the qfunction parameters.
template <
typename qf_param_ts,
typename qfunc_t,
std::size_t num_fields>
MFEM_HOST_DEVICE inline
void call_qfunction_derivative_action(
qfunc_t &qfunc,
const std::array<DeviceTensor<2>, num_fields> &input_shmem,
const std::array<DeviceTensor<2>, num_fields> &shadow_shmem,
DeviceTensor<2> &residual_shmem,
const int &das_qp,
const int &num_qp,
const int &q1d,
const int &dimension,
const bool &use_sum_factorization)
{
if (use_sum_factorization)
{
if (dimension == 1)
{
MFEM_FOREACH_THREAD_DIRECT(q, x, q1d)
{
auto r = Reshape(&residual_shmem(0, q), das_qp);
auto qf_args = decay_tuple<qf_param_ts> {};
#ifdef MFEM_USE_ENZYME
auto qf_shadow_args = decay_tuple<qf_param_ts> {};
apply_kernel_fwddiff_enzyme(r, qfunc, qf_args, qf_shadow_args, input_shmem,
shadow_shmem, q);
#else
apply_kernel_native_dual(r, qfunc, qf_args, input_shmem, shadow_shmem, q);
#endif
}
}
else if (dimension == 2)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
const int q = qx + q1d * qy;
auto r = Reshape(&residual_shmem(0, q), das_qp);
auto qf_args = decay_tuple<qf_param_ts> {};
#ifdef MFEM_USE_ENZYME
auto qf_shadow_args = decay_tuple<qf_param_ts> {};
apply_kernel_fwddiff_enzyme(r, qfunc, qf_args, qf_shadow_args, input_shmem,
shadow_shmem, q);
#else
apply_kernel_native_dual(r, qfunc, qf_args, input_shmem, shadow_shmem, q);
#endif
}
}
}
else if (dimension == 3)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qz, z, q1d)
{
const int q = qx + q1d * (qy + q1d * qz);
auto r = Reshape(&residual_shmem(0, q), das_qp);
auto qf_args = decay_tuple<qf_param_ts> {};
#ifdef MFEM_USE_ENZYME
auto qf_shadow_args = decay_tuple<qf_param_ts> {};
apply_kernel_fwddiff_enzyme(r, qfunc, qf_args, qf_shadow_args, input_shmem,
shadow_shmem, q);
#else
apply_kernel_native_dual(r, qfunc, qf_args, input_shmem, shadow_shmem, q);
#endif
}
}
}
}
else
{
MFEM_ABORT_KERNEL("unsupported dimension");
}
}
else
{
MFEM_FOREACH_THREAD_DIRECT(q, x, num_qp)
{
auto r = Reshape(&residual_shmem(0, q), das_qp);
auto qf_args = decay_tuple<qf_param_ts> {};
#ifdef MFEM_USE_ENZYME
auto qf_shadow_args = decay_tuple<qf_param_ts> {};
apply_kernel_fwddiff_enzyme(r, qfunc, qf_args, qf_shadow_args, input_shmem,
shadow_shmem, q);
#else
apply_kernel_native_dual(r, qfunc, qf_args, input_shmem, shadow_shmem, q);
#endif
}
}
MFEM_SYNC_THREAD;
}
namespace detail
{
template <
typename qf_param_ts,
typename qfunc_t,
std::size_t num_fields>
MFEM_HOST_DEVICE inline
void call_qfunction_derivative(
qfunc_t &qfunc,
const std::array<DeviceTensor<2>, num_fields> &input_shmem,
const std::array<DeviceTensor<2>, num_fields> &shadow_shmem,
DeviceTensor<2> &residual_shmem,
DeviceTensor<5> &qpdc,
const DeviceTensor<1, const real_t> &itod,
const int &das_qp,
const int &q)
{
const int test_vdim = qpdc.GetShape()[0];
const int test_op_dim = qpdc.GetShape()[1];
const int trial_vdim = qpdc.GetShape()[2];
const int num_qp = qpdc.GetShape()[4];
const size_t num_inputs = itod.GetShape()[0];
for (int j = 0; j < trial_vdim; j++)
{
int m_offset = 0;
for (size_t s = 0; s < num_inputs; s++)
{
const int trial_op_dim = static_cast<int>(itod(s));
if (trial_op_dim == 0)
{
continue;
}
auto d_qp = Reshape(&(shadow_shmem[s])[0], trial_vdim, trial_op_dim, num_qp);
for (int m = 0; m < trial_op_dim; m++)
{
d_qp(j, m, q) = 1.0;
auto r = Reshape(&residual_shmem(0, q), das_qp);
auto qf_args = decay_tuple<qf_param_ts> {};
#ifdef MFEM_USE_ENZYME
auto qf_shadow_args = decay_tuple<qf_param_ts> {};
apply_kernel_fwddiff_enzyme(r, qfunc, qf_args, qf_shadow_args, input_shmem,
shadow_shmem, q);
#else
apply_kernel_native_dual(r, qfunc, qf_args, input_shmem, shadow_shmem, q);
#endif
d_qp(j, m, q) = 0.0;
auto f = Reshape(&r(0), test_vdim, test_op_dim);
for (int i = 0; i < test_vdim; i++)
{
for (int k = 0; k < test_op_dim; k++)
{
qpdc(i, k, j, m + m_offset, q) = f(i, k);
}
}
}
m_offset += trial_op_dim;
}
}
}
}
/// @brief Call a qfunction with the given parameters and
/// compute it's derivative represented by the Jacobian on
/// each quadrature point.
///
/// @param qfunc the qfunction to call.
/// @param input_shmem the input shared memory.
/// @param shadow_shmem the shadow shared memory.
/// @param residual_shmem the residual shared memory.
/// @param qpdc the quadrature point data cache holding the resulting
/// Jacobians on each quadrature point.
/// @param itod inputs trial operator dimension.
/// If input is dependent the value corresponds to the spatial dimension, otherwise
/// a zero indicates non-dependence on the variable.
/// @param das_qp the size of the derivative action.
/// @param q1d the number of quadrature points in 1D.
/// @param dimension the spatial dimension.
/// @param use_sum_factorization whether to use sum factorization.
/// @tparam qf_param_ts the tuple type of the qfunction parameters.
template <
typename qf_param_ts,
typename qfunc_t,
std::size_t num_fields>
MFEM_HOST_DEVICE inline
void call_qfunction_derivative(
qfunc_t &qfunc,
const std::array<DeviceTensor<2>, num_fields> &input_shmem,
const std::array<DeviceTensor<2>, num_fields> &shadow_shmem,
DeviceTensor<2> &residual_shmem,
DeviceTensor<5> &qpdc,
const DeviceTensor<1, const real_t> &itod,
const int &das_qp,
const int &q1d,
const int &dimension,
const bool &use_sum_factorization)
{
if (use_sum_factorization)
{
if (dimension == 1)
{
MFEM_FOREACH_THREAD_DIRECT(q, x, q1d)
{
detail::call_qfunction_derivative<qf_param_ts>(
qfunc, input_shmem, shadow_shmem, residual_shmem, qpdc, itod, das_qp, q);
}
}
else if (dimension == 2)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
const int q = qx + q1d * qy;
detail::call_qfunction_derivative<qf_param_ts>(
qfunc, input_shmem, shadow_shmem, residual_shmem, qpdc, itod, das_qp, q);
}
}
}
else if (dimension == 3)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qz, z, q1d)
{
const int q = qx + q1d * (qy + q1d * qz);
detail::call_qfunction_derivative<qf_param_ts>(
qfunc, input_shmem, shadow_shmem, residual_shmem, qpdc, itod, das_qp, q);
}
}
}
}
else
{
MFEM_ABORT_KERNEL("unsupported dimension");
}
}
else
{
const int num_qp = qpdc.GetShape()[4];
MFEM_FOREACH_THREAD_DIRECT(q, x, num_qp)
{
detail::call_qfunction_derivative<qf_param_ts>(
qfunc, input_shmem, shadow_shmem, residual_shmem, qpdc, itod, das_qp, q);
}
}
MFEM_SYNC_THREAD;
}
namespace detail
{
/// @brief Apply the quadrature point data cache (qpdc) to a vector
/// (usually a direction) on quadrature point q.
///
/// The qpdc consists of compatible data to be used for integration with a test
/// operator, e.g. Jacobians of a linearization from a FE operation with a trial
/// function including integration weights and necessesary transformations.
///
/// @param fhat the qpdc applied to a vector in shadow_memory.
/// @param shadow_shmem the shadow shared memory.
/// @param qpdc the quadrature point data cache holding the resulting
/// Jacobians on each quadrature point.
/// @param itod inputs trial operator dimension.
/// If input is dependent the value corresponds to the spatial dimension, otherwise
/// a zero indicates non-dependence on the variable.
/// @param q the current quadrature point index.
template <size_t num_fields>
MFEM_HOST_DEVICE inline
void apply_qpdc(
DeviceTensor<3> &fhat,
const std::array<DeviceTensor<2>, num_fields> &shadow_shmem,
const DeviceTensor<5, const real_t> &qpdc,
const DeviceTensor<1, const real_t> &itod,
const int &q)
{
const int test_vdim = qpdc.GetShape()[0];
const int test_op_dim = qpdc.GetShape()[1];
const int trial_vdim = qpdc.GetShape()[2];
const int num_qp = qpdc.GetShape()[4];
const size_t num_inputs = itod.GetShape()[0];
for (int i = 0; i < test_vdim; i++)
{
for (int k = 0; k < test_op_dim; k++)
{
real_t sum = 0.0;
int m_offset = 0;
for (size_t s = 0; s < num_inputs; s++)
{
const int trial_op_dim = static_cast<int>(itod(s));
if (trial_op_dim == 0)
{
continue;
}
const auto d_qp =
Reshape(&(shadow_shmem[s])[0], trial_vdim, trial_op_dim, num_qp);
for (int j = 0; j < trial_vdim; j++)
{
for (int m = 0; m < trial_op_dim; m++)
{
sum += qpdc(i, k, j, m + m_offset, q) * d_qp(j, m, q);
}
}
m_offset += trial_op_dim;
}
fhat(i, k, q) = sum;
}
}
}
}
/// @brief Apply the quadrature point data cache (qpdc) to a vector
/// (usually a direction).
///
/// The qpdc consists of compatible data to be used for integration with a test
/// operator, e.g. Jacobians of a linearization from a FE operation with a trial
/// function including integration weights and necessesary transformations.
///
/// @param fhat the qpdc applied to a vector in shadow_memory.
/// @param shadow_shmem the shadow shared memory.
/// @param qpdc the quadrature point data cache holding the resulting
/// Jacobians on each quadrature point.
/// @param itod inputs trial operator dimension.
/// If input is dependent the value corresponds to the spatial dimension, otherwise
/// a zero indicates non-dependence on the variable.
/// @param q1d number of quadrature points in 1D.
/// @param dimension spatial dimension.
/// @param use_sum_factorization whether to use sum factorization.
template <size_t num_fields>
MFEM_HOST_DEVICE inline
void apply_qpdc(
DeviceTensor<3> &fhat,
const std::array<DeviceTensor<2>, num_fields> &shadow_shmem,
const DeviceTensor<5, const real_t> &qpdc,
const DeviceTensor<1, const real_t> &itod,
const int &q1d,
const int &dimension,
const bool &use_sum_factorization)
{
if (use_sum_factorization)
{
if (dimension == 1)
{
MFEM_FOREACH_THREAD_DIRECT(q, x, q1d)
{
detail::apply_qpdc(fhat, shadow_shmem, qpdc, itod, q);
}
}
else if (dimension == 2)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
const int q = qx + q1d * qy;
detail::apply_qpdc(fhat, shadow_shmem, qpdc, itod, q);
}
}
}
else if (dimension == 3)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, q1d)
{
MFEM_FOREACH_THREAD_DIRECT(qz, z, q1d)
{
const int q = qx + q1d * (qy + q1d * qz);
detail::apply_qpdc(fhat, shadow_shmem, qpdc, itod, q);
}
}
}
}
else
{
MFEM_ABORT_KERNEL("unsupported dimension");
}
}
else
{
const int num_qp = qpdc.GetShape()[4];
MFEM_FOREACH_THREAD_DIRECT(q, x, num_qp)
{
detail::apply_qpdc(fhat, shadow_shmem, qpdc, itod, q);
}
}
}
template <typename qfunc_t, typename args_ts, size_t num_args>
MFEM_HOST_DEVICE inline
void apply_kernel(
DeviceTensor<1, real_t> &f_qp,
const qfunc_t &qfunc,
args_ts &args,
const std::array<DeviceTensor<2>, num_args> &u,
int qp)
{
process_qf_args(u, args, qp);
process_qf_result(f_qp, get<0>(apply(qfunc, args)));
}
template <typename qfunc_t, typename arg_ts, size_t num_args>
MFEM_HOST_DEVICE inline
void apply_kernel_native_dual(
DeviceTensor<1, real_t> &f_qp,
const qfunc_t &qfunc,
arg_ts &args,
const std::array<DeviceTensor<2>, num_args> &u,
const std::array<DeviceTensor<2>, num_args> &v,
const int &qp_idx)
{
process_qf_args(u, v, args, qp_idx);
auto r = get<0>(apply(qfunc, args));
process_derivative_from_native_dual(f_qp, r);
}
#ifdef MFEM_USE_ENZYME
template <typename func_t, typename... arg_ts>
MFEM_HOST_DEVICE inline
auto qfunction_wrapper(const func_t &f, arg_ts &&...args)
{
return f(args...);
}
// Version for active function arguments only
//
// This is an Enzyme regression and can be removed in later versions.
template <typename qfunc_t, typename arg_ts, std::size_t... Is,
typename inactive_arg_ts>
MFEM_HOST_DEVICE inline
auto fwddiff_apply_enzyme_indexed(qfunc_t &qfunc, arg_ts &&args,
arg_ts &&shadow_args,
std::index_sequence<Is...>,
inactive_arg_ts &&inactive_args,
std::index_sequence<>)
{
using qf_return_t = typename create_function_signature<
decltype(&qfunc_t::operator())>::type::return_t;
return __enzyme_fwddiff<qf_return_t>(
qfunction_wrapper<qfunc_t, decltype(get<Is>(args))...>, enzyme_const,
(void *)&qfunc, enzyme_dup, &get<Is>(args)..., enzyme_interleave,
&get<Is>(shadow_args)...);
}
// Interleave function arguments for enzyme
template <typename qfunc_t, typename arg_ts, std::size_t... Is,
typename inactive_arg_ts, std::size_t... Js>
MFEM_HOST_DEVICE inline
auto fwddiff_apply_enzyme_indexed(qfunc_t &qfunc, arg_ts &&args,
arg_ts &&shadow_args,
std::index_sequence<Is...>,
inactive_arg_ts &&inactive_args,
std::index_sequence<Js...>)
{
using qf_return_t = typename create_function_signature<
decltype(&qfunc_t::operator())>::type::return_t;
return __enzyme_fwddiff<qf_return_t>(
qfunction_wrapper<qfunc_t, decltype(get<Is>(args))...,
decltype(get<Js>(inactive_args))...>,
enzyme_const, (void *)&qfunc, enzyme_dup, &get<Is>(args)...,
enzyme_const, &get<Js>(inactive_args)..., enzyme_interleave,
&get<Is>(shadow_args)...);
}
template <typename qfunc_t, typename arg_ts, typename inactive_arg_ts>
MFEM_HOST_DEVICE inline
auto fwddiff_apply_enzyme(qfunc_t &qfunc, arg_ts &&args,
arg_ts &&shadow_args,
inactive_arg_ts &&inactive_args)
{
auto arg_indices = std::make_index_sequence<
tuple_size<std::remove_reference_t<arg_ts>>::value> {};
auto inactive_arg_indices = std::make_index_sequence<
tuple_size<std::remove_reference_t<inactive_arg_ts>>::value> {};
return fwddiff_apply_enzyme_indexed(qfunc, args, shadow_args, arg_indices,
inactive_args, inactive_arg_indices);
}
template <typename qfunc_t, typename arg_ts, size_t num_args>
MFEM_HOST_DEVICE inline
void apply_kernel_fwddiff_enzyme(
DeviceTensor<1, real_t> &f_qp,
qfunc_t &qfunc,
arg_ts &args,
arg_ts &shadow_args,
const std::array<DeviceTensor<2>, num_args> &u,
const std::array<DeviceTensor<2>, num_args> &v,
int qp_idx)
{
process_qf_args(u, args, qp_idx);
process_qf_args(v, shadow_args, qp_idx);
process_qf_result(f_qp,
get<0>(fwddiff_apply_enzyme(qfunc, args, shadow_args, tuple<> {})));
}
#endif // MFEM_USE_ENZYME
} // namespace mfem::future
-346
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@@ -1,346 +0,0 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "util.hpp"
#include "../../linalg/tensor.hpp"
namespace mfem::future
{
template <typename T0, typename T1, typename T2>
MFEM_HOST_DEVICE
void process_qf_arg(const T0 &, const T1 &, T2 &)
{
static_assert(dfem::always_false<T0, T1, T2>,
"process_qf_arg not implemented for arg type");
}
template <typename T>
MFEM_HOST_DEVICE
void process_qf_arg(
const DeviceTensor<1, T> &u,
const DeviceTensor<1, T> &v,
T &arg)
{
arg = u(0);
}
template <typename T, int n, int m>
MFEM_HOST_DEVICE inline
void process_qf_arg(
const DeviceTensor<1> &u,
tensor<dual<T, T>, n, m> &arg)
{
for (int i = 0; i < m; i++)
{
for (int j = 0; j < n; j++)
{
arg(j, i).value = u((i * n) + j);
}
}
}
template <typename T>
MFEM_HOST_DEVICE inline
void process_qf_arg(
const DeviceTensor<1> &u,
dual<T, T> &arg)
{
arg.value = u(0);
}
template <typename T>
MFEM_HOST_DEVICE inline
void process_qf_arg(
const DeviceTensor<1> &u,
const DeviceTensor<1> &v,
dual<T, T> &arg)
{
arg.value = u(0);
arg.gradient = v(0);
}
template <typename T, int n>
MFEM_HOST_DEVICE inline
void process_qf_arg(
const DeviceTensor<1> &u,
const DeviceTensor<1> &v,
tensor<dual<T, T>, n> &arg)
{
for (int i = 0; i < n; i++)
{
arg(i).value = u(i);
arg(i).gradient = v(i);
}
}
template <typename T, int n, int m>
MFEM_HOST_DEVICE inline
void process_qf_arg(
const DeviceTensor<1> &u,
const DeviceTensor<1> &v,
tensor<dual<T, T>, n, m> &arg)
{
for (int i = 0; i < m; i++)
{
for (int j = 0; j < n; j++)
{
arg(j, i).value = u((i * n) + j);
arg(j, i).gradient = v((i * n) + j);
}
}
}
template <typename T, int n>
MFEM_HOST_DEVICE inline
void process_qf_result(
DeviceTensor<1, T> &r,
const tensor<dual<T, T>, n> &x)
{
for (size_t i = 0; i < n; i++)
{
r(i) = x(i).value;
}
}
template <typename T, int n, int m>
MFEM_HOST_DEVICE inline
void process_qf_result(
DeviceTensor<1, T> &r,
const tensor<dual<T, T>, n, m> &x)
{
for (size_t i = 0; i < n; i++)
{
for (size_t j = 0; j < m; j++)
{
r(i + n * j) = x(i, j).value;
}
}
}
template <typename arg_type>
MFEM_HOST_DEVICE inline
void process_qf_arg(
const DeviceTensor<2> &u,
const DeviceTensor<2> &v,
arg_type &arg,
const int &qp)
{
const auto u_qp = Reshape(&u(0, qp), u.GetShape()[0]);
const auto v_qp = Reshape(&v(0, qp), v.GetShape()[0]);
process_qf_arg(u_qp, v_qp, arg);
}
template <size_t num_fields, typename qf_args>
MFEM_HOST_DEVICE inline
void process_qf_args(
const std::array<DeviceTensor<2>, num_fields> &u,
const std::array<DeviceTensor<2>, num_fields> &v,
qf_args &args,
const int &qp)
{
for_constexpr<tuple_size<qf_args>::value>([&](auto i)
{
process_qf_arg(u[i], v[i], get<i>(args), qp);
});
}
template <typename T, int n, int m>
MFEM_HOST_DEVICE inline
void process_derivative_from_native_dual(
DeviceTensor<1, T> &r,
const tensor<dual<T, T>, n, m> &x)
{
for (size_t i = 0; i < n; i++)
{
for (size_t j = 0; j < m; j++)
{
r(i + n * j) = x(i, j).gradient;
}
}
}
template <typename T, int n>
MFEM_HOST_DEVICE inline
void process_derivative_from_native_dual(
DeviceTensor<1, T> &r,
const tensor<dual<T, T>, n> &x)
{
for (size_t i = 0; i < n; i++)
{
r(i) = x(i).gradient;
}
}
template <typename T>
MFEM_HOST_DEVICE inline
void process_derivative_from_native_dual(
DeviceTensor<1, T> &r,
const dual<T, T> &x)
{
r(0) = x.gradient;
}
template <typename T0, typename T1>
MFEM_HOST_DEVICE inline
void process_qf_arg(const T0 &, T1 &)
{
static_assert(dfem::always_false<T0, T1>,
"process_qf_arg not implemented for arg type");
}
template <typename T>
MFEM_HOST_DEVICE inline
void process_qf_arg(
const DeviceTensor<1, T> &u,
T &arg)
{
arg = u(0);
}
template <typename T>
MFEM_HOST_DEVICE inline
void process_qf_arg(
const DeviceTensor<1, T> &u,
tensor<T> &arg)
{
arg(0) = u(0);
}
template <typename T, int n>
MFEM_HOST_DEVICE inline
void process_qf_arg(
const DeviceTensor<1> &u,
tensor<T, n> &arg)
{
for (int i = 0; i < n; i++)
{
arg(i) = u(i);
}
}
template <typename T, int n, int m>
MFEM_HOST_DEVICE inline
void process_qf_arg(
const DeviceTensor<1> &u,
tensor<T, n, m> &arg)
{
for (int i = 0; i < m; i++)
{
for (int j = 0; j < n; j++)
{
arg(j, i) = u((i * n) + j);
}
}
}
template <typename arg_type>
MFEM_HOST_DEVICE inline
void process_qf_arg(const DeviceTensor<2> &u, arg_type &arg, int qp)
{
const auto u_qp = Reshape(&u(0, qp), u.GetShape()[0]);
process_qf_arg(u_qp, arg);
}
template <size_t num_fields, typename qf_args>
MFEM_HOST_DEVICE inline
void process_qf_args(
const std::array<DeviceTensor<2>, num_fields> &u,
qf_args &args,
const int &qp)
{
for_constexpr<tuple_size<qf_args>::value>([&](auto i)
{
process_qf_arg(u[i], get<i>(args), qp);
});
}
template <typename T0, typename T1>
MFEM_HOST_DEVICE inline
Vector process_qf_result(T0, T1)
{
static_assert(dfem::always_false<T0, T1>,
"process_qf_result not implemented for result type");
return Vector{};
}
template <typename T>
MFEM_HOST_DEVICE inline
void process_qf_result(
DeviceTensor<1, T> &r,
const T &x)
{
r(0) = x;
}
template <typename T>
MFEM_HOST_DEVICE inline
void process_qf_result(
DeviceTensor<1> &r,
const dual<T, T> &x)
{
r(0) = x.value;
}
template <typename T>
MFEM_HOST_DEVICE inline
void process_qf_result(
DeviceTensor<1, T> &r,
const tensor<T> &x)
{
r(0) = x(0);
}
template <typename T, int n>
MFEM_HOST_DEVICE inline
void process_qf_result(
DeviceTensor<1, T> &r,
const tensor<T, n> &x)
{
for (size_t i = 0; i < n; i++)
{
r(i) = x(i);
}
}
template <typename T, int n, int m>
MFEM_HOST_DEVICE inline
void process_qf_result(
DeviceTensor<1, T> &r,
const tensor<T, n, m> &x)
{
for (size_t i = 0; i < n; i++)
{
for (size_t j = 0; j < m; j++)
{
r(i + n * j) = x(i, j);
}
}
}
template <typename T, int n, int m>
MFEM_HOST_DEVICE inline
void process_qf_arg(
const DeviceTensor<1, T> &u,
const DeviceTensor<1, T> &v,
tensor<T, n, m> &arg)
{
for (int i = 0; i < m; i++)
{
for (int j = 0; j < n; j++)
{
arg(j, i) = u((i * n) + j);
}
}
}
} // namespace mfem::future
+638 -738
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+1119 -792
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+1 -1
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@@ -52,7 +52,7 @@
#include "bounds.hpp"
#include "particleset.hpp"
#include "dfem/doperator.hpp"
// #include "dfem/doperator.hpp"
#ifdef MFEM_USE_MPI
#include "pfespace.hpp"
+12 -8
View File
@@ -48,7 +48,11 @@ namespace mfem
#define MFEM_REGISTER_KERNELS(KernelName, KernelType, ...) \
MFEM_EXPAND(MFEM_EXPAND(MFEM_REGISTER_KERNELS_N(__VA_ARGS__,2,1,)) \
(KernelName,KernelType,__VA_ARGS__))
(MFEM_EXPORT, KernelName, KernelType, __VA_ARGS__))
#define MFEM_REGISTER_KERNELS_HEADER_ONLY(KernelName, KernelType, ...) \
MFEM_EXPAND(MFEM_EXPAND(MFEM_REGISTER_KERNELS_N(__VA_ARGS__,2,1,)) \
(, KernelName, KernelType, __VA_ARGS__))
#define MFEM_REGISTER_KERNELS_N(_1, _2, N, ...) MFEM_REGISTER_KERNELS_##N
@@ -58,19 +62,19 @@ namespace mfem
// Version of MFEM_REGISTER_KERNELS without any "optional" (non-dispatch)
// parameters.
#define MFEM_REGISTER_KERNELS_1(KernelName, KernelType, Params) \
MFEM_REGISTER_KERNELS_(KernelName, KernelType, Params, (), Params)
#define MFEM_REGISTER_KERNELS_1(ExportMacro, KernelName, KernelType, Params) \
MFEM_REGISTER_KERNELS_(ExportMacro, KernelName, KernelType, Params, (), Params)
// Version of MFEM_REGISTER_KERNELS without any optional (non-dispatch)
// parameters (e.g. NBZ).
#define MFEM_REGISTER_KERNELS_2(KernelName, KernelType, Params, OptParams) \
MFEM_REGISTER_KERNELS_(KernelName, KernelType, Params, OptParams, \
#define MFEM_REGISTER_KERNELS_2(ExportMacro, KernelName, KernelType, Params, OptParams) \
MFEM_REGISTER_KERNELS_(ExportMacro, KernelName, KernelType, Params, OptParams, \
(MFEM_PARAM_LIST Params, MFEM_PARAM_LIST OptParams))
// P1 are the parameters, P2 are the optional (non-dispatch parameters), and P3
// is the concatenation of P1 and P2. We need to pass it as a separate argument
// to avoid a trailing comma in the case that P2 is empty.
#define MFEM_REGISTER_KERNELS_(KernelName, KernelType, P1, P2, P3) \
#define MFEM_REGISTER_KERNELS_(ExportMacro, KernelName, KernelType, P1, P2, P3) \
class KernelName \
: public ::mfem::KernelDispatchTable< \
KernelName, KernelType, \
@@ -80,8 +84,8 @@ namespace mfem
const char *kernel_name = MFEM_KERNEL_NAME(KernelName); \
using KernelSignature = KernelType; \
template <MFEM_PARAM_LIST P3> static KernelSignature Kernel(); \
static MFEM_EXPORT KernelSignature Fallback(MFEM_PARAM_LIST P1); \
static MFEM_EXPORT KernelName &Get() { \
static ExportMacro KernelSignature Fallback(MFEM_PARAM_LIST P1); \
static ExportMacro KernelName &Get() { \
static KernelName table; \
return table; \
} \
+1828 -21
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+3
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@@ -224,6 +224,9 @@ public:
/** @see GetGradient(const Vector &) */
Operator &GetGradient(const Vector &x, bool finalize) const;
/// Suppress a warning about hiding overloaded virtual function.
using Operator::GetGradient;
/// Update the NonlinearForm to propagate updates of the associated FE space.
/** After calling this method, the essential boundary conditions need to be
set again. */
+21
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@@ -79,6 +79,27 @@ public:
Vector::operator=(orig);
}
/** @brief Construct a QuadratureFunction on the given
VectorQuadratureSpace, @a vqspace.
After construction, the QuadratureFunction does not need the
VectorQuadratureSpace object. Instead, it uses directly its underlying
QuadratureSpaceBase object. */
QuadratureFunction(VectorQuadratureSpace &vqspace)
: QuadratureFunction(*vqspace.GetSpace(), vqspace.GetVDim())
{ }
/** @brief Construct a QuadratureFunction on the given
VectorQuadratureSpace, @a vqspace, with the given MemoryType, @a mt, used
for the underlying Vector object.
After construction, the QuadratureFunction does not need the
VectorQuadratureSpace object. Instead, it uses directly its underlying
QuadratureSpaceBase object. */
QuadratureFunction(VectorQuadratureSpace &vqspace, MemoryType mt)
: QuadratureFunction(*vqspace.GetSpace(), mt, vqspace.GetVDim())
{ }
/// Read a QuadratureFunction from the stream @a in.
/** The QuadratureFunction assumes ownership of the read QuadratureSpace. */
QuadratureFunction(Mesh *mesh, std::istream &in);
+44
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@@ -0,0 +1,44 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "../quadinterpolator.hpp"
#include "eval_transpose.hpp"
namespace mfem
{
/// @cond Suppress_Doxygen_warnings
QuadratureInterpolator::TensorEvalTransposeKernelType
QuadratureInterpolator::TensorEvalTransposeKernels::Fallback(
int DIM, QVectorLayout Q_LAYOUT, int, int, int)
{
using namespace internal::quadrature_interpolator;
if (Q_LAYOUT == QVectorLayout::byNODES)
{
if (DIM == 1) { return ValuesTranspose1D<QVectorLayout::byNODES>; }
else if (DIM == 2) { return ValuesTranspose2D<QVectorLayout::byNODES>; }
else if (DIM == 3) { return ValuesTranspose3D<QVectorLayout::byNODES>; }
}
else
{
if (DIM == 1) { return ValuesTranspose1D<QVectorLayout::byVDIM>; }
else if (DIM == 2) { return ValuesTranspose2D<QVectorLayout::byVDIM>; }
else if (DIM == 3) { return ValuesTranspose3D<QVectorLayout::byVDIM>; }
}
MFEM_ABORT("Invalid dimension");
return nullptr;
}
/// @endcond
} // namespace mfem
+304
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@@ -0,0 +1,304 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../quadinterpolator.hpp"
#include "../../general/forall.hpp"
#include "../../linalg/dtensor.hpp"
#include "../../linalg/kernels.hpp"
#include "../kernels.hpp"
namespace mfem
{
namespace internal
{
namespace quadrature_interpolator
{
template<QVectorLayout Q_LAYOUT>
static void ValuesTranspose1D(const int NE,
const real_t *b_,
const real_t *q_,
real_t *e_,
const int vdim,
const int d1d,
const int q1d)
{
const auto b = Reshape(b_, q1d, d1d);
const auto qd = Q_LAYOUT == QVectorLayout::byNODES ?
Reshape(q_, q1d, vdim, NE) :
Reshape(q_, vdim, q1d, NE);
auto e = Reshape(e_, d1d, vdim, NE);
mfem::forall(NE, [=] MFEM_HOST_DEVICE (int el)
{
for (int c = 0; c < vdim; c++)
{
for (int d = 0; d < d1d; d++)
{
real_t u = 0.0;
for (int q = 0; q < q1d; q++)
{
const real_t qval = Q_LAYOUT == QVectorLayout::byVDIM ?
qd(c, q, el) : qd(q, c, el);
u += b(q, d) * qval;
}
e(d, c, el) += u;
}
}
});
}
template<QVectorLayout Q_LAYOUT,
int T_VDIM = 0, int T_D1D = 0, int T_Q1D = 0,
int T_NBZ = 1>
static void ValuesTranspose2D(const int NE,
const real_t *b_,
const real_t *q_,
real_t *e_,
const int vdim = 0,
const int d1d = 0,
const int q1d = 0)
{
static constexpr int NBZ = T_NBZ ? T_NBZ : 1;
const int D1D = T_D1D ? T_D1D : d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
const int VDIM = T_VDIM ? T_VDIM : vdim;
const auto b = Reshape(b_, Q1D, D1D);
const auto q = Q_LAYOUT == QVectorLayout::byNODES ?
Reshape(q_, Q1D, Q1D, VDIM, NE) :
Reshape(q_, VDIM, Q1D, Q1D, NE);
auto e = Reshape(e_, D1D, D1D, VDIM, NE);
mfem::forall_2D_batch(NE, D1D, D1D, NBZ, [=] MFEM_HOST_DEVICE (int el)
{
const int D1D = T_D1D ? T_D1D : d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
const int VDIM = T_VDIM ? T_VDIM : vdim;
constexpr int MQ1 = T_Q1D ? T_Q1D : DofQuadLimits::MAX_Q1D;
constexpr int MD1 = T_D1D ? T_D1D : DofQuadLimits::MAX_D1D;
constexpr int MDQ = (MQ1 > MD1) ? MQ1 : MD1;
const int tidz = MFEM_THREAD_ID(z);
MFEM_SHARED real_t sB[MQ1*MD1];
MFEM_SHARED real_t sm0[NBZ][MDQ*MDQ];
MFEM_SHARED real_t sm1[NBZ][MDQ*MDQ];
kernels::internal::LoadB<MD1,MQ1>(D1D,Q1D,b,sB);
ConstDeviceMatrix B(sB, D1D, Q1D);
DeviceMatrix QQ(sm0[tidz], MQ1, MQ1);
DeviceMatrix DQ(sm1[tidz], MD1, MQ1);
DeviceMatrix DD(sm0[tidz], MD1, MD1);
for (int c = 0; c < VDIM; c++)
{
// Load Q data
MFEM_FOREACH_THREAD(qy,y,Q1D)
{
MFEM_FOREACH_THREAD(qx,x,Q1D)
{
QQ(qx,qy) = Q_LAYOUT == QVectorLayout::byVDIM ?
q(c,qx,qy,el) : q(qx,qy,c,el);
}
}
MFEM_SYNC_THREAD;
// Transpose in y: QQ -> DQ (apply B^T in y-direction)
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(qx,x,Q1D)
{
real_t u = 0.0;
for (int qy = 0; qy < Q1D; ++qy)
{
u += B(dy,qy) * QQ(qx,qy);
}
DQ(dy,qx) = u;
}
}
MFEM_SYNC_THREAD;
// Transpose in x: DQ -> DD (apply B^T in x-direction)
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
real_t u = 0.0;
for (int qx = 0; qx < Q1D; ++qx)
{
u += B(dx,qx) * DQ(dy,qx);
}
DD(dx,dy) = u;
}
}
MFEM_SYNC_THREAD;
// Store result
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
e(dx,dy,c,el) += DD(dx,dy);
}
}
MFEM_SYNC_THREAD;
}
});
}
template<QVectorLayout Q_LAYOUT,
int T_VDIM = 0, int T_D1D = 0, int T_Q1D = 0>
static void ValuesTranspose3D(const int NE,
const real_t *b_,
const real_t *q_,
real_t *e_,
const int vdim = 0,
const int d1d = 0,
const int q1d = 0)
{
const int D1D = T_D1D ? T_D1D : d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
const int VDIM = T_VDIM ? T_VDIM : vdim;
const auto b = Reshape(b_, Q1D, D1D);
const auto q = Q_LAYOUT == QVectorLayout::byNODES ?
Reshape(q_, Q1D, Q1D, Q1D, VDIM, NE) :
Reshape(q_, VDIM, Q1D, Q1D, Q1D, NE);
auto e = Reshape(e_, D1D, D1D, D1D, VDIM, NE);
mfem::forall_3D(NE, D1D, D1D, D1D, [=] MFEM_HOST_DEVICE (int el)
{
const int D1D = T_D1D ? T_D1D : d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
const int VDIM = T_VDIM ? T_VDIM : vdim;
constexpr int MQ1 = T_Q1D ? T_Q1D : DofQuadLimits::MAX_INTERP_1D;
constexpr int MD1 = T_D1D ? T_D1D : DofQuadLimits::MAX_INTERP_1D;
constexpr int MDQ = (MQ1 > MD1) ? MQ1 : MD1;
MFEM_SHARED real_t sB[MQ1*MD1];
MFEM_SHARED real_t sm0[MDQ*MDQ*MDQ];
MFEM_SHARED real_t sm1[MDQ*MDQ*MDQ];
kernels::internal::LoadB<MD1,MQ1>(D1D,Q1D,b,sB);
ConstDeviceMatrix B(sB, D1D, Q1D);
DeviceCube QQQ(sm0, MQ1, MQ1, MQ1);
DeviceCube DQQ(sm1, MD1, MQ1, MQ1);
DeviceCube DDQ(sm0, MD1, MD1, MQ1);
DeviceCube DDD(sm1, MD1, MD1, MD1);
for (int c = 0; c < VDIM; c++)
{
// Load Q data
MFEM_FOREACH_THREAD(qz,z,Q1D)
{
MFEM_FOREACH_THREAD(qy,y,Q1D)
{
MFEM_FOREACH_THREAD(qx,x,Q1D)
{
QQQ(qx,qy,qz) = Q_LAYOUT == QVectorLayout::byVDIM ?
q(c,qx,qy,qz,el) : q(qx,qy,qz,c,el);
}
}
}
MFEM_SYNC_THREAD;
// Transpose in z
MFEM_FOREACH_THREAD(dz,z,D1D)
{
MFEM_FOREACH_THREAD(qy,y,Q1D)
{
MFEM_FOREACH_THREAD(qx,x,Q1D)
{
real_t u = 0.0;
for (int qz = 0; qz < Q1D; ++qz)
{
u += B(dz,qz) * QQQ(qx,qy,qz);
}
DQQ(dz,qx,qy) = u;
}
}
}
MFEM_SYNC_THREAD;
// Transpose in y
MFEM_FOREACH_THREAD(dz,z,D1D)
{
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(qx,x,Q1D)
{
real_t u = 0.0;
for (int qy = 0; qy < Q1D; ++qy)
{
u += B(dy,qy) * DQQ(dz,qx,qy);
}
DDQ(dz,dy,qx) = u;
}
}
}
MFEM_SYNC_THREAD;
// Transpose in x
MFEM_FOREACH_THREAD(dz,z,D1D)
{
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
real_t u = 0.0;
for (int qx = 0; qx < Q1D; ++qx)
{
u += B(dx,qx) * DDQ(dz,dy,qx);
}
DDD(dx,dy,dz) = u;
}
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD(dz,z,D1D)
{
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
e(dx,dy,dz,c,el) += DDD(dx,dy,dz);
}
}
}
MFEM_SYNC_THREAD;
}
});
}
} // namespace quadrature_interpolator
} // namespace internal
/// \cond DO_NOT_DOCUMENT
template<int DIM, QVectorLayout Q_LAYOUT,
int VDIM, int D1D, int Q1D, int NBZ>
QuadratureInterpolator::TensorEvalTransposeKernelType
QuadratureInterpolator::TensorEvalTransposeKernels::Kernel()
{
if (DIM == 1) { return internal::quadrature_interpolator::ValuesTranspose1D<Q_LAYOUT>; }
else if (DIM == 2) { return internal::quadrature_interpolator::ValuesTranspose2D<Q_LAYOUT, VDIM, D1D, Q1D, NBZ>; }
else if (DIM == 3) { return internal::quadrature_interpolator::ValuesTranspose3D<Q_LAYOUT, VDIM, D1D, Q1D>; }
else { MFEM_ABORT(""); }
}
/// \endcond DO_NOT_DOCUMENT
} // namespace mfem
+61
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@@ -0,0 +1,61 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "../quadinterpolator.hpp"
#include "eval_transpose.hpp"
namespace mfem
{
namespace internal
{
namespace quadrature_interpolator
{
void InitEvalTransposeByVDimKernels()
{
using k = QuadratureInterpolator::TensorEvalTransposeKernels;
constexpr auto L = QVectorLayout::byVDIM;
// 2D
k::Specialization<2,L,1,2,4>::Opt<8>::Add();
k::Specialization<2,L,1,3,6>::Opt<4>::Add();
k::Specialization<2,L,1,4,8>::Opt<2>::Add();
k::Specialization<2,L,2,2,4>::Opt<8>::Add();
k::Specialization<2,L,2,3,4>::Opt<8>::Add();
k::Specialization<2,L,2,3,6>::Opt<4>::Add();
k::Specialization<2,L,2,4,6>::Opt<2>::Add();
k::Specialization<2,L,2,4,8>::Opt<2>::Add();
// 3D
k::Specialization<3,L,1,2,4>::Opt<1>::Add();
k::Specialization<3,L,1,3,6>::Opt<1>::Add();
k::Specialization<3,L,1,4,8>::Opt<1>::Add();
k::Specialization<3,L,3,2,4>::Opt<1>::Add();
k::Specialization<3,L,3,3,6>::Opt<1>::Add();
k::Specialization<3,L,3,4,8>::Opt<1>::Add();
k::Specialization<3,L,3,2,2>::Opt<1>::Add();
k::Specialization<3,L,3,3,3>::Opt<1>::Add();
k::Specialization<3,L,3,4,4>::Opt<1>::Add();
k::Specialization<3,L,3,5,5>::Opt<1>::Add();
k::Specialization<3,L,3,6,6>::Opt<1>::Add();
k::Specialization<3,L,3,7,7>::Opt<1>::Add();
k::Specialization<3,L,3,8,8>::Opt<1>::Add();
k::Specialization<3,L,3,9,9>::Opt<1>::Add();
k::Specialization<3,L,3,4,6>::Opt<1>::Add();
k::Specialization<3,L,3,3,4>::Opt<1>::Add();
}
} // namespace quadrature_interpolator
} // namespace internal
} // namespace mfem
+62
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@@ -0,0 +1,62 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "../quadinterpolator.hpp"
#include "grad_transpose.hpp"
namespace mfem
{
/// @cond Suppress_Doxygen_warnings
QuadratureInterpolator::GradTransposeKernelType
QuadratureInterpolator::GradTransposeKernels::Fallback(
int DIM, QVectorLayout Q_LAYOUT, bool GRAD_PHYS, int, int, int)
{
using namespace internal::quadrature_interpolator;
if (Q_LAYOUT == QVectorLayout::byNODES)
{
if (GRAD_PHYS)
{
if (DIM == 1) { return DerivativesTranspose1D<QVectorLayout::byNODES, true>; }
else if (DIM == 2) { return DerivativesTranspose2D<QVectorLayout::byNODES, true>; }
else if (DIM == 3) { return DerivativesTranspose3D<QVectorLayout::byNODES, true>; }
}
else
{
if (DIM == 1) { return DerivativesTranspose1D<QVectorLayout::byNODES, false>; }
else if (DIM == 2) { return DerivativesTranspose2D<QVectorLayout::byNODES, false>; }
else if (DIM == 3) { return DerivativesTranspose3D<QVectorLayout::byNODES, false>; }
}
}
else
{
if (GRAD_PHYS)
{
if (DIM == 1) { return DerivativesTranspose1D<QVectorLayout::byVDIM, true>; }
else if (DIM == 2) { return DerivativesTranspose2D<QVectorLayout::byVDIM, true>; }
else if (DIM == 3) { return DerivativesTranspose3D<QVectorLayout::byVDIM, true>; }
}
else
{
if (DIM == 1) { return DerivativesTranspose1D<QVectorLayout::byVDIM, false>; }
else if (DIM == 2) { return DerivativesTranspose2D<QVectorLayout::byVDIM, false>; }
else if (DIM == 3) { return DerivativesTranspose3D<QVectorLayout::byVDIM, false>; }
}
}
MFEM_ABORT("Invalid dimension");
return nullptr;
}
/// @endcond
} // namespace mfem
+741
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@@ -0,0 +1,741 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#pragma once
#include "../quadinterpolator.hpp"
#include "../../general/forall.hpp"
#include "../../linalg/dtensor.hpp"
#include "../../linalg/kernels.hpp"
#include "../kernels.hpp"
namespace mfem
{
namespace internal
{
namespace quadrature_interpolator
{
// Transpose gradient operation: integrate against shape function derivatives
// This is the adjoint of the Derivatives operation
template<QVectorLayout Q_LAYOUT, bool GRAD_PHYS>
static void DerivativesTranspose1D(const int NE,
const real_t *b_,
const real_t *g_,
const real_t *j_,
const real_t *q_,
real_t *e_,
const int sdim,
const int vdim,
const int d1d,
const int q1d)
{
MFEM_CONTRACT_VAR(b_);
const int SDIM = GRAD_PHYS ? sdim : 1;
const auto g = Reshape(g_, q1d, d1d);
const auto j = Reshape(j_, q1d, SDIM, NE);
const auto q = Q_LAYOUT == QVectorLayout::byNODES ?
Reshape(q_, q1d, vdim, SDIM, NE):
Reshape(q_, vdim, SDIM, q1d, NE);
auto e = Reshape(e_, d1d, vdim, NE);
mfem::forall(NE, [=] MFEM_HOST_DEVICE (int el)
{
for (int c = 0; c < vdim; c++)
{
for (int d = 0; d < d1d; d++)
{
real_t u = 0.0;
for (int qx = 0; qx < q1d; qx++)
{
// Load gradient from q-vector
real_t dq[3] = {0.0, 0.0, 0.0};
for (int s = 0; s < SDIM; ++s)
{
if (Q_LAYOUT == QVectorLayout::byVDIM) { dq[s] = q(c, s, qx, el); }
if (Q_LAYOUT == QVectorLayout::byNODES) { dq[s] = q(qx, c, s, el); }
}
// Apply inverse Jacobian transpose (adjoint of physical gradient)
real_t du = dq[0];
if (GRAD_PHYS)
{
if (SDIM == 1) { du = dq[0] / j(qx, 0, el); }
else if (SDIM == 2)
{
const real_t Jloc[2] = {j(qx,0,el), j(qx,1,el)};
real_t Jinv[3];
kernels::CalcLeftInverse<2,1>(Jloc, Jinv);
du = Jinv[0]*dq[0] + Jinv[1]*dq[1];
}
else // SDIM == 3
{
const real_t Jloc[3] = {j(qx,0,el), j(qx,1,el), j(qx,2,el)};
real_t Jinv[3];
kernels::CalcLeftInverse<3,1>(Jloc, Jinv);
du = Jinv[0]*dq[0] + Jinv[1]*dq[1] + Jinv[2]*dq[2];
}
}
// Accumulate contribution (transpose of G matrix)
u += g(qx, d) * du;
}
e(d, c, el) += u;
}
}
});
}
template<QVectorLayout Q_LAYOUT, bool GRAD_PHYS,
int T_VDIM = 0, int T_D1D = 0, int T_Q1D = 0,
int T_NBZ = 1>
static void DerivativesTranspose2D(const int NE,
const real_t *b_,
const real_t *g_,
const real_t *j_,
const real_t *q_,
real_t *e_,
const int sdim = 2,
const int vdim = 0,
const int d1d = 0,
const int q1d = 0)
{
const int D1D = T_D1D ? T_D1D : d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
const int VDIM = T_VDIM ? T_VDIM : vdim;
const int SDIM = GRAD_PHYS ? sdim : 2;
static constexpr int NBZ = T_NBZ ? T_NBZ : 1;
const auto b = Reshape(b_, Q1D, D1D);
const auto g = Reshape(g_, Q1D, D1D);
const auto j = Reshape(j_, Q1D, Q1D, SDIM, 2, NE);
const auto q = Q_LAYOUT == QVectorLayout::byNODES ?
Reshape(q_, Q1D, Q1D, VDIM, SDIM, NE):
Reshape(q_, VDIM, SDIM, Q1D, Q1D, NE);
auto e = Reshape(e_, D1D, D1D, VDIM, NE);
mfem::forall_2D_batch(NE, D1D, D1D, NBZ, [=] MFEM_HOST_DEVICE (int el)
{
const int D1D = T_D1D ? T_D1D : d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
const int VDIM = T_VDIM ? T_VDIM : vdim;
constexpr int MQ1 = T_Q1D ? T_Q1D : DofQuadLimits::MAX_Q1D;
constexpr int MD1 = T_D1D ? T_D1D : DofQuadLimits::MAX_D1D;
constexpr int MDQ = (MQ1 > MD1) ? MQ1 : MD1;
const int tidz = MFEM_THREAD_ID(z);
MFEM_SHARED real_t BG[2][MQ1*MD1];
kernels::internal::LoadBG<MD1,MQ1>(D1D,Q1D,b,g,BG);
DeviceMatrix B(BG[0], D1D, Q1D);
DeviceMatrix G(BG[1], D1D, Q1D);
MFEM_SHARED real_t sm0[NBZ][MDQ*MDQ];
MFEM_SHARED real_t sm1[NBZ][MDQ*MDQ];
DeviceMatrix QQ(sm0[tidz], MQ1, MQ1);
DeviceMatrix DQ0(sm1[tidz], MD1, MQ1);
DeviceMatrix DQ1(sm1[tidz], MD1, MQ1); // Reuse sm1 after DQ0 is done
DeviceMatrix DD(sm0[tidz], MD1, MD1); // Reuse sm0 after QQ is done
for (int c = 0; c < VDIM; c++)
{
// Load Q data and apply inverse Jacobian
MFEM_FOREACH_THREAD(qy,y,Q1D)
{
MFEM_FOREACH_THREAD(qx,x,Q1D)
{
// Load gradient components
real_t dq[3] = {0.0, 0.0, 0.0};
for (int d = 0; d < SDIM; ++d)
{
if (Q_LAYOUT == QVectorLayout::byVDIM) { dq[d] = q(c, d, qx, qy, el); }
else { dq[d] = q(qx, qy, c, d, el); }
}
// Apply inverse Jacobian transpose (adjoint of physical gradient)
real_t du[2] = {dq[0], dq[1]};
if (GRAD_PHYS)
{
if (SDIM == 2)
{
real_t Jloc[4], Jinv[4];
Jloc[0] = j(qx,qy,0,0,el);
Jloc[1] = j(qx,qy,1,0,el);
Jloc[2] = j(qx,qy,0,1,el);
Jloc[3] = j(qx,qy,1,1,el);
kernels::CalcInverse<2>(Jloc, Jinv);
const real_t U = Jinv[0]*dq[0] + Jinv[2]*dq[1];
const real_t V = Jinv[1]*dq[0] + Jinv[3]*dq[1];
du[0] = U;
du[1] = V;
}
else // SDIM == 3
{
real_t Jloc[6], Jinv[6];
Jloc[0] = j(qx,qy,0,0,el);
Jloc[1] = j(qx,qy,1,0,el);
Jloc[2] = j(qx,qy,2,0,el);
Jloc[3] = j(qx,qy,0,1,el);
Jloc[4] = j(qx,qy,1,1,el);
Jloc[5] = j(qx,qy,2,1,el);
kernels::CalcLeftInverse<3,2>(Jloc, Jinv);
const real_t U = Jinv[0]*dq[0] + Jinv[2]*dq[1] + Jinv[4]*dq[2];
const real_t V = Jinv[1]*dq[0] + Jinv[3]*dq[1] + Jinv[5]*dq[2];
du[0] = U;
du[1] = V;
}
}
QQ(qx, qy) = du[0]; // Store du/dx component
}
}
MFEM_SYNC_THREAD;
// Apply B^T in y-direction: QQ -> DQ0
// (Transpose of d/dx which uses DQ1(dy,qx)*B(dy,qy))
// Must produce DQ0(dy,qx) to match forward's DQ1 indexing
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(qx,x,Q1D)
{
real_t u = 0.0;
for (int qy = 0; qy < Q1D; ++qy)
{
u += B(dy,qy) * QQ(qx,qy);
}
DQ0(dy,qx) = u;
}
}
MFEM_SYNC_THREAD;
// Apply G^T in x-direction: DQ0 -> DD
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
real_t u = 0.0;
for (int qx = 0; qx < Q1D; ++qx)
{
u += G(dx,qx) * DQ0(dy,qx);
}
DD(dx,dy) = u;
}
}
MFEM_SYNC_THREAD;
// Accumulate to output
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
e(dx,dy,c,el) += DD(dx,dy);
}
}
MFEM_SYNC_THREAD;
// Now process du/dy component
MFEM_FOREACH_THREAD(qy,y,Q1D)
{
MFEM_FOREACH_THREAD(qx,x,Q1D)
{
// Load gradient components
real_t dq[3] = {0.0, 0.0, 0.0};
for (int d = 0; d < SDIM; ++d)
{
if (Q_LAYOUT == QVectorLayout::byVDIM) { dq[d] = q(c, d, qx, qy, el); }
else { dq[d] = q(qx, qy, c, d, el); }
}
// Apply inverse Jacobian transpose
real_t du[2] = {dq[0], dq[1]};
if (GRAD_PHYS)
{
if (SDIM == 2)
{
real_t Jloc[4], Jinv[4];
Jloc[0] = j(qx,qy,0,0,el);
Jloc[1] = j(qx,qy,1,0,el);
Jloc[2] = j(qx,qy,0,1,el);
Jloc[3] = j(qx,qy,1,1,el);
kernels::CalcInverse<2>(Jloc, Jinv);
const real_t U = Jinv[0]*dq[0] + Jinv[2]*dq[1];
const real_t V = Jinv[1]*dq[0] + Jinv[3]*dq[1];
du[0] = U;
du[1] = V;
}
else // SDIM == 3
{
real_t Jloc[6], Jinv[6];
Jloc[0] = j(qx,qy,0,0,el);
Jloc[1] = j(qx,qy,1,0,el);
Jloc[2] = j(qx,qy,2,0,el);
Jloc[3] = j(qx,qy,0,1,el);
Jloc[4] = j(qx,qy,1,1,el);
Jloc[5] = j(qx,qy,2,1,el);
kernels::CalcLeftInverse<3,2>(Jloc, Jinv);
const real_t U = Jinv[0]*dq[0] + Jinv[2]*dq[1] + Jinv[4]*dq[2];
const real_t V = Jinv[1]*dq[0] + Jinv[3]*dq[1] + Jinv[5]*dq[2];
du[0] = U;
du[1] = V;
}
}
QQ(qx, qy) = du[1]; // Store du/dy component
}
}
MFEM_SYNC_THREAD;
// Apply G^T in y-direction: QQ -> DQ1
// (Transpose of d/dy which uses DQ0(dy,qx)*G(dy,qy))
// Must produce DQ1(dy,qx) to match forward's DQ0 indexing
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(qx,x,Q1D)
{
real_t u = 0.0;
for (int qy = 0; qy < Q1D; ++qy)
{
u += G(dy,qy) * QQ(qx,qy);
}
DQ1(dy,qx) = u;
}
}
MFEM_SYNC_THREAD;
// Apply B^T in x-direction: DQ1 -> DD
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
real_t u = 0.0;
for (int qx = 0; qx < Q1D; ++qx)
{
u += B(dx,qx) * DQ1(dy,qx);
}
DD(dx,dy) = u;
}
}
MFEM_SYNC_THREAD;
// Accumulate to output
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
e(dx,dy,c,el) += DD(dx,dy);
}
}
MFEM_SYNC_THREAD;
}
});
}
template<QVectorLayout Q_LAYOUT, bool GRAD_PHYS,
int T_VDIM = 0, int T_D1D = 0, int T_Q1D = 0>
static void DerivativesTranspose3D(const int NE,
const real_t *b_,
const real_t *g_,
const real_t *j_,
const real_t *q_, // q_der
real_t *e_, // e_vec
const int sdim = 3,
const int vdim = 0,
const int d1d = 0,
const int q1d = 0)
{
const int D1D = T_D1D ? T_D1D : d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
const int VDIM = T_VDIM ? T_VDIM : vdim;
const auto b = Reshape(b_, Q1D, D1D);
const auto g = Reshape(g_, Q1D, D1D);
const auto j = Reshape(j_, Q1D, Q1D, Q1D, 3, 3, NE);
const auto q = Q_LAYOUT == QVectorLayout::byNODES ?
Reshape(q_, Q1D, Q1D, Q1D, VDIM, 3, NE):
Reshape(q_, VDIM, 3, Q1D, Q1D, Q1D, NE);
auto e = Reshape(e_, D1D, D1D, D1D, VDIM, NE);
mfem::forall_3D(NE, Q1D, Q1D, Q1D, [=] MFEM_HOST_DEVICE (int el)
{
const int D1D = T_D1D ? T_D1D : d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
const int VDIM = T_VDIM ? T_VDIM : vdim;
constexpr int MQ1 = T_Q1D ? T_Q1D : DofQuadLimits::MAX_INTERP_1D;
constexpr int MD1 = T_D1D ? T_D1D : DofQuadLimits::MAX_INTERP_1D;
MFEM_SHARED real_t BG[2][MQ1*MD1];
kernels::internal::LoadBG<MD1,MQ1>(D1D,Q1D,b,g,BG);
DeviceMatrix B(BG[0], D1D, Q1D);
DeviceMatrix G(BG[1], D1D, Q1D);
MFEM_SHARED real_t sm0[1][MQ1*MQ1*MQ1];
MFEM_SHARED real_t sm1[1][MQ1*MQ1*MQ1];
DeviceCube QQQ(sm0[0], MQ1, MQ1, MQ1);
DeviceCube DQQ(sm1[0], MD1, MQ1, MQ1);
DeviceCube DDQ(sm0[0], MD1, MD1, MQ1);
DeviceCube DDD(sm1[0], MD1, MD1, MD1);
for (int c = 0; c < VDIM; c++)
{
// Process du/dx component
MFEM_FOREACH_THREAD(qz,z,Q1D)
{
MFEM_FOREACH_THREAD(qy,y,Q1D)
{
MFEM_FOREACH_THREAD(qx,x,Q1D)
{
real_t dq[3];
if (Q_LAYOUT == QVectorLayout::byVDIM)
{
dq[0] = q(c,0,qx,qy,qz,el);
dq[1] = q(c,1,qx,qy,qz,el);
dq[2] = q(c,2,qx,qy,qz,el);
}
else
{
dq[0] = q(qx,qy,qz,c,0,el);
dq[1] = q(qx,qy,qz,c,1,el);
dq[2] = q(qx,qy,qz,c,2,el);
}
real_t du[3] = {dq[0], dq[1], dq[2]};
if (GRAD_PHYS)
{
real_t Jloc[9], Jinv[9];
for (int col = 0; col < 3; col++)
{
for (int row = 0; row < 3; row++)
{
Jloc[row+3*col] = j(qx,qy,qz,row,col,el);
}
}
kernels::CalcInverse<3>(Jloc, Jinv);
const real_t U = Jinv[0]*dq[0] + Jinv[3]*dq[1] + Jinv[6]*dq[2];
const real_t V = Jinv[1]*dq[0] + Jinv[4]*dq[1] + Jinv[7]*dq[2];
const real_t W = Jinv[2]*dq[0] + Jinv[5]*dq[1] + Jinv[8]*dq[2];
du[0] = U; du[1] = V; du[2] = W;
}
QQQ(qx,qy,qz) = du[0];
}
}
}
MFEM_SYNC_THREAD;
// Apply G^T in x: QQQ -> DQQ (transpose of G⊗B⊗B)
MFEM_FOREACH_THREAD(qz,z,Q1D)
{
MFEM_FOREACH_THREAD(qy,y,Q1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
real_t u = 0.0;
for (int qx = 0; qx < Q1D; ++qx)
{
u += G(dx,qx) * QQQ(qx,qy,qz);
}
DQQ(dx,qy,qz) = u;
}
}
}
MFEM_SYNC_THREAD;
// Apply B^T in y: DQQ -> DDQ
MFEM_FOREACH_THREAD(qz,z,Q1D)
{
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
real_t u = 0.0;
for (int qy = 0; qy < Q1D; ++qy)
{
u += B(dy,qy) * DQQ(dx,qy,qz);
}
DDQ(dx,dy,qz) = u;
}
}
}
MFEM_SYNC_THREAD;
// Apply B^T in z: DDQ -> DDD
MFEM_FOREACH_THREAD(dz,z,D1D)
{
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
real_t u = 0.0;
for (int qz = 0; qz < Q1D; ++qz)
{
u += B(dz,qz) * DDQ(dx,dy,qz);
}
DDD(dx,dy,dz) = u;
}
}
}
MFEM_SYNC_THREAD;
// Accumulate result
MFEM_FOREACH_THREAD(dz,z,D1D)
{
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
e(dx,dy,dz,c,el) += DDD(dx,dy,dz);
}
}
}
MFEM_SYNC_THREAD;
// Process du/dy component
MFEM_FOREACH_THREAD(qz,z,Q1D)
{
MFEM_FOREACH_THREAD(qy,y,Q1D)
{
MFEM_FOREACH_THREAD(qx,x,Q1D)
{
real_t dq[3];
if (Q_LAYOUT == QVectorLayout::byVDIM)
{
dq[0] = q(c,0,qx,qy,qz,el);
dq[1] = q(c,1,qx,qy,qz,el);
dq[2] = q(c,2,qx,qy,qz,el);
}
else
{
dq[0] = q(qx,qy,qz,c,0,el);
dq[1] = q(qx,qy,qz,c,1,el);
dq[2] = q(qx,qy,qz,c,2,el);
}
real_t du[3] = {dq[0], dq[1], dq[2]};
if (GRAD_PHYS)
{
real_t Jloc[9], Jinv[9];
for (int col = 0; col < 3; col++)
{
for (int row = 0; row < 3; row++)
{
Jloc[row+3*col] = j(qx,qy,qz,row,col,el);
}
}
kernels::CalcInverse<3>(Jloc, Jinv);
const real_t U = Jinv[0]*dq[0] + Jinv[3]*dq[1] + Jinv[6]*dq[2];
const real_t V = Jinv[1]*dq[0] + Jinv[4]*dq[1] + Jinv[7]*dq[2];
const real_t W = Jinv[2]*dq[0] + Jinv[5]*dq[1] + Jinv[8]*dq[2];
du[0] = U; du[1] = V; du[2] = W;
}
QQQ(qx,qy,qz) = du[1];
}
}
}
MFEM_SYNC_THREAD;
// Apply B^T in x: QQQ -> DQQ (transpose of B⊗G⊗B)
MFEM_FOREACH_THREAD(qz,z,Q1D)
{
MFEM_FOREACH_THREAD(qy,y,Q1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
real_t u = 0.0;
for (int qx = 0; qx < Q1D; ++qx)
{
u += B(dx,qx) * QQQ(qx,qy,qz);
}
DQQ(dx,qy,qz) = u;
}
}
}
MFEM_SYNC_THREAD;
// Apply G^T in y: DQQ -> DDQ
MFEM_FOREACH_THREAD(qz,z,Q1D)
{
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
real_t u = 0.0;
for (int qy = 0; qy < Q1D; ++qy)
{
u += G(dy,qy) * DQQ(dx,qy,qz);
}
DDQ(dx,dy,qz) = u;
}
}
}
MFEM_SYNC_THREAD;
// Apply B^T in z: DDQ -> DDD
MFEM_FOREACH_THREAD(dz,z,D1D)
{
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
real_t u = 0.0;
for (int qz = 0; qz < Q1D; ++qz)
{
u += B(dz,qz) * DDQ(dx,dy,qz);
}
DDD(dx,dy,dz) = u;
}
}
}
MFEM_SYNC_THREAD;
// Accumulate result
MFEM_FOREACH_THREAD(dz,z,D1D)
{
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
e(dx,dy,dz,c,el) += DDD(dx,dy,dz);
}
}
}
MFEM_SYNC_THREAD;
// Process du/dz component
MFEM_FOREACH_THREAD(qz,z,Q1D)
{
MFEM_FOREACH_THREAD(qy,y,Q1D)
{
MFEM_FOREACH_THREAD(qx,x,Q1D)
{
real_t dq[3];
if (Q_LAYOUT == QVectorLayout::byVDIM)
{
dq[0] = q(c,0,qx,qy,qz,el);
dq[1] = q(c,1,qx,qy,qz,el);
dq[2] = q(c,2,qx,qy,qz,el);
}
else
{
dq[0] = q(qx,qy,qz,c,0,el);
dq[1] = q(qx,qy,qz,c,1,el);
dq[2] = q(qx,qy,qz,c,2,el);
}
real_t du[3] = {dq[0], dq[1], dq[2]};
if (GRAD_PHYS)
{
real_t Jloc[9], Jinv[9];
for (int col = 0; col < 3; col++)
{
for (int row = 0; row < 3; row++)
{
Jloc[row+3*col] = j(qx,qy,qz,row,col,el);
}
}
kernels::CalcInverse<3>(Jloc, Jinv);
const real_t U = Jinv[0]*dq[0] + Jinv[3]*dq[1] + Jinv[6]*dq[2];
const real_t V = Jinv[1]*dq[0] + Jinv[4]*dq[1] + Jinv[7]*dq[2];
const real_t W = Jinv[2]*dq[0] + Jinv[5]*dq[1] + Jinv[8]*dq[2];
du[0] = U; du[1] = V; du[2] = W;
}
QQQ(qx,qy,qz) = du[2];
}
}
}
MFEM_SYNC_THREAD;
// Apply G^T in z: QQQ -> DQQ (transpose of B⊗B⊗G)
MFEM_FOREACH_THREAD(dz,z,D1D)
{
MFEM_FOREACH_THREAD(qy,y,Q1D)
{
MFEM_FOREACH_THREAD(qx,x,Q1D)
{
real_t u = 0.0;
for (int qz = 0; qz < Q1D; ++qz)
{
u += G(dz,qz) * QQQ(qx,qy,qz);
}
DQQ(dz,qy,qx) = u;
}
}
}
MFEM_SYNC_THREAD;
// Apply B^T in y: DQQ -> DDQ
MFEM_FOREACH_THREAD(dz,z,D1D)
{
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(qx,x,Q1D)
{
real_t u = 0.0;
for (int qy = 0; qy < Q1D; ++qy)
{
u += B(dy,qy) * DQQ(dz,qy,qx);
}
DDQ(dz,dy,qx) = u;
}
}
}
MFEM_SYNC_THREAD;
// Apply B^T in x: DDQ -> DDD
MFEM_FOREACH_THREAD(dz,z,D1D)
{
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
real_t u = 0.0;
for (int qx = 0; qx < Q1D; ++qx)
{
u += B(dx,qx) * DDQ(dz,dy,qx);
}
DDD(dx,dy,dz) = u;
}
}
}
MFEM_SYNC_THREAD;
// Accumulate result
MFEM_FOREACH_THREAD(dz,z,D1D)
{
MFEM_FOREACH_THREAD(dy,y,D1D)
{
MFEM_FOREACH_THREAD(dx,x,D1D)
{
e(dx,dy,dz,c,el) += DDD(dx,dy,dz);
}
}
}
MFEM_SYNC_THREAD;
}
});
}
} // namespace quadrature_interpolator
} // namespace internal
/// \cond DO_NOT_DOCUMENT
template<int DIM, QVectorLayout Q_LAYOUT, bool GRAD_PHYS, int VDIM, int D1D,
int Q1D, int NBZ>
QuadratureInterpolator::GradTransposeKernelType
QuadratureInterpolator::GradTransposeKernels::Kernel()
{
if (DIM == 1) { return internal::quadrature_interpolator::DerivativesTranspose1D<Q_LAYOUT, GRAD_PHYS>; }
else if (DIM == 2) { return internal::quadrature_interpolator::DerivativesTranspose2D<Q_LAYOUT, GRAD_PHYS, VDIM, D1D, Q1D, NBZ>; }
else if (DIM == 3) { return internal::quadrature_interpolator::DerivativesTranspose3D<Q_LAYOUT, GRAD_PHYS, VDIM, D1D, Q1D>; }
else { MFEM_ABORT(""); }
}
/// \endcond DO_NOT_DOCUMENT
} // namespace mfem
+50
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@@ -0,0 +1,50 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "../quadinterpolator.hpp"
#include "grad_transpose.hpp"
namespace mfem
{
namespace internal
{
namespace quadrature_interpolator
{
template <bool P>
void InitGradTransposeByNodesKernels()
{
using k = QuadratureInterpolator::GradTransposeKernels;
constexpr auto L = QVectorLayout::byNODES;
// 2D
k::Specialization<2,L,P,1,3,4>::template Opt<8>::Add();
k::Specialization<2,L,P,1,4,6>::template Opt<4>::Add();
k::Specialization<2,L,P,1,5,8>::template Opt<2>::Add();
k::Specialization<2,L,P,2,3,3>::template Opt<8>::Add();
k::Specialization<2,L,P,2,3,4>::template Opt<8>::Add();
k::Specialization<2,L,P,2,4,6>::template Opt<4>::Add();
k::Specialization<2,L,P,2,5,8>::template Opt<2>::Add();
// 3D
k::Specialization<3,L,P,1,3,4>::Add();
k::Specialization<3,L,P,1,4,6>::Add();
k::Specialization<3,L,P,1,5,8>::Add();
k::Specialization<3,L,P,3,3,4>::Add();
k::Specialization<3,L,P,3,4,6>::Add();
k::Specialization<3,L,P,3,5,8>::Add();
}
template void InitGradTransposeByNodesKernels<false>();
template void InitGradTransposeByNodesKernels<true>();
} // namespace quadrature_interpolator
} // namespace internal
} // namespace mfem
+50
View File
@@ -0,0 +1,50 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "../quadinterpolator.hpp"
#include "grad_transpose.hpp"
namespace mfem
{
namespace internal
{
namespace quadrature_interpolator
{
template <bool P>
void InitGradTransposeByVDimKernels()
{
using k = QuadratureInterpolator::GradTransposeKernels;
constexpr auto L = QVectorLayout::byVDIM;
// 2D
k::Specialization<2,L,P,1,3,4>::template Opt<8>::Add();
k::Specialization<2,L,P,1,4,6>::template Opt<4>::Add();
k::Specialization<2,L,P,1,5,8>::template Opt<2>::Add();
k::Specialization<2,L,P,2,3,3>::template Opt<8>::Add();
k::Specialization<2,L,P,2,3,4>::template Opt<8>::Add();
k::Specialization<2,L,P,2,4,6>::template Opt<4>::Add();
k::Specialization<2,L,P,2,5,8>::template Opt<2>::Add();
// 3D
k::Specialization<3,L,P,1,3,4>::Add();
k::Specialization<3,L,P,1,4,6>::Add();
k::Specialization<3,L,P,1,5,8>::Add();
k::Specialization<3,L,P,3,3,4>::Add();
k::Specialization<3,L,P,3,4,6>::Add();
k::Specialization<3,L,P,3,5,8>::Add();
}
template void InitGradTransposeByVDimKernels<false>();
template void InitGradTransposeByVDimKernels<true>();
} // namespace quadrature_interpolator
} // namespace internal
} // namespace mfem
+65 -3
View File
@@ -27,7 +27,11 @@ enum class QSpaceOffsetStorage
/// Abstract base class for QuadratureSpace and FaceQuadratureSpace.
/** This class represents the storage layout for QuadratureFunction%s, that may
be defined either on mesh elements or mesh faces. */
be defined either on mesh elements or mesh faces.
This class represents the layout for a single scalar value at each
quadrature point. Use class VectorQuadratureSpace to represent a space with
multiple (vector) values at each quadrature point. */
class QuadratureSpaceBase
{
protected:
@@ -158,8 +162,62 @@ public:
virtual ~QuadratureSpaceBase() { }
};
/// Vector version of the scalar class QuadratureSpaceBase.
class VectorQuadratureSpace
{
protected:
/// Points to an external object provided during construction. Not owned.
QuadratureSpaceBase *qspace;
/// Vector dimension.
int vdim;
public:
/** @brief Construct a VectorQuadratureSpace on the given
QuadratureSpaceBase, @a qspace_, with the given vector dimension,
@a vdim_.
The VectorQuadratureSpace does not assume ownership of the
QuadratureSpaceBase, @a qspace_. */
VectorQuadratureSpace(QuadratureSpaceBase &qspace_, int vdim_)
: qspace(&qspace_),
vdim(vdim_)
{ }
/// Copy constructor: default.
VectorQuadratureSpace(const VectorQuadratureSpace &) = default;
/// Copy assignment: default.
VectorQuadratureSpace &operator=(const VectorQuadratureSpace &) = default;
/// Move construction is not allowed.
VectorQuadratureSpace(VectorQuadratureSpace &&) = delete;
/// Move assignment is not allowed.
VectorQuadratureSpace &operator=(VectorQuadratureSpace &&) = delete;
/// Destructor: default.
~VectorQuadratureSpace() = default;
/// Get the associated scalar QuadratureSpaceBase object.
QuadratureSpaceBase *GetSpace() { return qspace; }
/// Get the associated scalar QuadratureSpaceBase object (const version).
const QuadratureSpaceBase *GetSpace() const { return qspace; }
/// Get the vector dimension.
int GetVDim() const { return vdim; }
/** @brief Get the total size (on this MPI-rank in parallel) of the
VectorQuadratureSpace. */
int GetVSize() const { return qspace->GetSize() * vdim; }
};
/// Class representing the storage layout of a QuadratureFunction.
/** Multiple QuadratureFunction%s can share the same QuadratureSpace. */
/** Multiple QuadratureFunction%s can share the same QuadratureSpace.
This class represents the layout for a single scalar value at each
quadrature point. Use class VectorQuadratureSpace to represent a space with
multiple (vector) values at each quadrature point. */
class QuadratureSpace : public QuadratureSpaceBase
{
protected:
@@ -209,7 +267,11 @@ public:
/// Class representing the storage layout of a FaceQuadratureFunction.
/** FaceQuadratureSpace is defined on either the interior or boundary faces
of a mesh, depending on the provided FaceType. */
of a mesh, depending on the provided FaceType.
This class represents the layout for a single scalar value at each
quadrature point. Use class VectorQuadratureSpace to represent a space with
multiple (vector) values at each quadrature point. */
class FaceQuadratureSpace : public QuadratureSpaceBase
{
FaceType face_type; ///< Is the space defined on interior or boundary faces?
+63 -9
View File
@@ -11,6 +11,7 @@
#include "quadinterpolator.hpp"
#include "qinterp/grad.hpp"
#include "qinterp/grad_transpose.hpp"
#include "qinterp/eval.hpp"
#include "qspace.hpp"
#include "../general/forall.hpp"
@@ -30,7 +31,10 @@ void InitEvalKernels();
void InitDetKernels();
template <bool P> void InitGradByNodesKernels();
template <bool P> void InitGradByVDimKernels();
template <bool P> void InitGradTransposeByNodesKernels();
template <bool P> void InitGradTransposeByVDimKernels();
void InitTensorEvalHDivKernels();
void InitEvalTransposeByVDimKernels();
struct Kernels
{
Kernels()
@@ -45,12 +49,19 @@ struct Kernels
// Phys grad kernels
InitGradByNodesKernels<true>();
InitGradByVDimKernels<true>();
// Non-phys grad transpose kernels
InitGradTransposeByNodesKernels<false>();
InitGradTransposeByVDimKernels<false>();
// Phys grad transpose kernels
InitGradTransposeByNodesKernels<true>();
InitGradTransposeByVDimKernels<true>();
// Determinants
InitDetKernels();
// Non-tensor
InitEvalKernels();
// Tensor (quad,hex) H(div)
InitTensorEvalHDivKernels();
InitEvalTransposeByVDimKernels();
}
};
}
@@ -646,16 +657,59 @@ void QuadratureInterpolator::MultHDiv(const Vector &e_vec,
MFEM_CONTRACT_VAR(q_div);
}
void QuadratureInterpolator::MultTranspose(unsigned eval_flags,
const Vector &q_val,
const Vector &q_der,
Vector &e_vec) const
void QuadratureInterpolator::AddMultTranspose(unsigned eval_flags,
const Vector &q_val,
const Vector &q_der,
Vector &e_vec) const
{
MFEM_CONTRACT_VAR(eval_flags);
MFEM_CONTRACT_VAR(q_val);
MFEM_CONTRACT_VAR(q_der);
MFEM_CONTRACT_VAR(e_vec);
MFEM_ABORT("this method is not implemented yet");
const int ne = fespace->GetNE();
if (ne == 0) { return; }
const FiniteElement *fe = fespace->GetFE(0);
const int vdim = fespace->GetVDim();
const int sdim = fespace->GetMesh()->SpaceDimension();
const bool use_tensor_eval =
use_tensor_products &&
dynamic_cast<const TensorBasisElement*>(fe) != nullptr;
const IntegrationRule *ir =
IntRule ? IntRule : &qspace->GetElementIntRule(0);
const DofToQuad::Mode mode =
use_tensor_eval ? DofToQuad::TENSOR : DofToQuad::FULL;
const DofToQuad &maps = fe->GetDofToQuad(*ir, mode);
const int dim = maps.FE->GetDim();
const int nd = maps.ndof;
const int nq = maps.nqpt;
const GeometricFactors *geom = nullptr;
if (eval_flags & PHYSICAL_DERIVATIVES)
{
const int jacobians = GeometricFactors::JACOBIANS;
geom = fespace->GetMesh()->GetGeometricFactors(*ir, jacobians);
}
if (use_tensor_eval)
{
if (eval_flags & (VALUES | PHYSICAL_VALUES))
{
TensorEvalTransposeKernels::Run(dim, q_layout, vdim, nd, nq, ne,
maps.B.Read(), q_val.Read(),
e_vec.ReadWrite(), vdim, nd, nq);
}
if (eval_flags & (DERIVATIVES | PHYSICAL_DERIVATIVES))
{
const bool phys = (eval_flags & PHYSICAL_DERIVATIVES);
const real_t *J = phys ? geom->J.Read() : nullptr;
const int s_dim = phys ? sdim : dim;
GradTransposeKernels::Run(dim, q_layout, phys, vdim, nd, nq, ne,
maps.B.Read(), maps.G.Read(), J,
q_der.Read(), e_vec.ReadWrite(),
s_dim, vdim, nd, nq);
}
}
else
{
MFEM_ABORT("Non-tensor MultTranspose not yet implemented");
}
}
void QuadratureInterpolator::Values(const Vector &e_vec,
+13 -2
View File
@@ -152,8 +152,8 @@ public:
void Determinants(const Vector &e_vec, Vector &q_det) const;
/// Perform the transpose operation of Mult(). (TODO)
void MultTranspose(unsigned eval_flags, const Vector &q_val,
const Vector &q_der, Vector &e_vec) const;
void AddMultTranspose(unsigned eval_flags, const Vector &q_val,
const Vector &q_der, Vector &e_vec) const;
/// @brief Returns true if the given finite element space is supported by
/// QuadratureInterpolator.
@@ -178,6 +178,13 @@ public:
using TensorEvalHDivKernelType =
void(*)(const int, const real_t *, const real_t *, const real_t *,
const real_t *, real_t *, const int, const int);
using TensorEvalTransposeKernelType = void(*)(const int, const real_t *,
const real_t *,
real_t *, const int, const int, const int);
using GradTransposeKernelType = void(*)(const int, const real_t *,
const real_t *, const real_t *,
const real_t *, real_t *,
const int, const int, const int, const int);
MFEM_REGISTER_KERNELS(TensorEvalKernels, TensorEvalKernelType,
(int, QVectorLayout, int, int, int), (int));
@@ -189,6 +196,10 @@ public:
(int, QVectorLayout, bool, int, int), (int));
MFEM_REGISTER_KERNELS(TensorEvalHDivKernels, TensorEvalHDivKernelType,
(int, QVectorLayout, unsigned, int, int));
MFEM_REGISTER_KERNELS(TensorEvalTransposeKernels, TensorEvalTransposeKernelType,
(int, QVectorLayout, int, int, int), (int));
MFEM_REGISTER_KERNELS(GradTransposeKernels, GradTransposeKernelType,
(int, QVectorLayout, bool, int, int, int), (int));
};
}
+251
View File
@@ -299,6 +299,17 @@ void ElementRestriction::FillSparseMatrix(const Vector &mat_ea,
FillJAndData(mat_ea, mat);
}
void ElementRestriction::FillSparseMatrix(
const Vector &mat_ea, SparseMatrix &mat,
const ElementRestriction &trial_restr) const
{
mat.GetMemoryI().New(mat.Height()+1, mat.GetMemoryI().GetMemoryType());
const int nnz = FillI(mat, trial_restr);
mat.GetMemoryJ().New(nnz, mat.GetMemoryJ().GetMemoryType());
mat.GetMemoryData().New(nnz, mat.GetMemoryData().GetMemoryType());
FillJAndData(mat_ea, mat, trial_restr);
}
static MFEM_HOST_DEVICE int GetMinElt(const int *my_elts, const int nbElts,
const int *nbr_elts, const int nbrNbElts)
{
@@ -328,6 +339,23 @@ static MFEM_HOST_DEVICE int GetAndIncrementNnzIndex(const int i_L, int* I)
return ind;
}
static MFEM_HOST_DEVICE int DofToVDof(const int dof, const int c,
const int ndofs, const int vdim,
const bool byvdim)
{
return byvdim ? dof*vdim + c : c*ndofs + dof;
}
static MFEM_HOST_DEVICE int SignedIndexAbs(const int i)
{
return (i >= 0) ? i : -1 - i;
}
static MFEM_HOST_DEVICE int SignedIndexSign(const int i)
{
return (i >= 0) ? 1 : -1;
}
int ElementRestriction::FillI(SparseMatrix &mat) const
{
const int all_dofs = ndofs;
@@ -405,6 +433,100 @@ int ElementRestriction::FillI(SparseMatrix &mat) const
return h_I[nTdofs];
}
int ElementRestriction::FillI(SparseMatrix &mat,
const ElementRestriction &trial_restr) const
{
MFEM_VERIFY(ne == trial_restr.ne,
"ElementRestriction::FillI: test/trial NE mismatch");
const int test_all_dofs = ndofs;
const int trial_all_dofs = trial_restr.ndofs;
const int test_vd = vdim;
const int trial_vd = trial_restr.vdim;
const int test_elt_dofs = dof;
const int trial_elt_dofs = trial_restr.dof;
const bool test_byvdim = byvdim;
const bool trial_byvdim = trial_restr.byvdim;
auto I = mat.ReadWriteI();
auto test_offsets = offsets.Read();
auto test_indices = indices.Read();
auto test_gather_map = gather_map.Read();
auto trial_offsets = trial_restr.offsets.Read();
auto trial_indices = trial_restr.indices.Read();
auto trial_gather_map = trial_restr.gather_map.Read();
Array<int> test_elts(indices.Size());
Array<int> trial_elts(trial_restr.indices.Size());
auto d_test_elts = test_elts.Write();
auto d_trial_elts = trial_elts.Write();
mfem::forall(test_vd*test_all_dofs+1, [=] MFEM_HOST_DEVICE (int i_L)
{
I[i_L] = 0;
});
mfem::forall(ne*test_elt_dofs*test_vd, [=] MFEM_HOST_DEVICE (int iE)
{
const int e = iE/(test_elt_dofs*test_vd);
const int it = iE%(test_elt_dofs*test_vd);
const int i = it%test_elt_dofs;
const int test_c = it/test_elt_dofs;
const int i_gm = e*test_elt_dofs + i;
const int i_dof = SignedIndexAbs(test_gather_map[i_gm]);
const int i_L = DofToVDof(i_dof, test_c, test_all_dofs, test_vd,
test_byvdim);
const int i_offset = test_offsets[i_dof];
const int i_next_offset = test_offsets[i_dof+1];
const int i_nbElts = i_next_offset - i_offset;
int *i_elts = &d_test_elts[i_offset];
for (int e_i = 0; e_i < i_nbElts; ++e_i)
{
const int i_loc = SignedIndexAbs(test_indices[i_offset+e_i]);
i_elts[e_i] = i_loc/test_elt_dofs;
}
for (int trial_c = 0; trial_c < trial_vd; ++trial_c)
{
MFEM_CONTRACT_VAR(trial_c);
for (int j = 0; j < trial_elt_dofs; j++)
{
const int j_gm = e*trial_elt_dofs + j;
const int j_dof = SignedIndexAbs(trial_gather_map[j_gm]);
const int j_offset = trial_offsets[j_dof];
const int j_next_offset = trial_offsets[j_dof+1];
const int j_nbElts = j_next_offset - j_offset;
if (i_nbElts == 1 || j_nbElts == 1)
{
GetAndIncrementNnzIndex(i_L, I);
}
else
{
int *j_elts = &d_trial_elts[j_offset];
for (int e_j = 0; e_j < j_nbElts; ++e_j)
{
const int j_loc = SignedIndexAbs(trial_indices[j_offset+e_j]);
j_elts[e_j] = j_loc/trial_elt_dofs;
}
const int min_e = GetMinElt(i_elts, i_nbElts,
j_elts, j_nbElts);
if (e == min_e) { GetAndIncrementNnzIndex(i_L, I); }
}
}
}
});
auto h_I = mat.HostReadWriteI();
const int nTdofs = test_vd*test_all_dofs;
int sum = 0;
for (int i = 0; i < nTdofs; i++)
{
const int nnz = h_I[i];
h_I[i] = sum;
sum += nnz;
}
h_I[nTdofs] = sum;
return h_I[nTdofs];
}
void ElementRestriction::FillJAndData(const Vector &ea_data,
SparseMatrix &mat) const
{
@@ -501,6 +623,135 @@ void ElementRestriction::FillJAndData(const Vector &ea_data,
h_I[0] = 0;
}
void ElementRestriction::FillJAndData(
const Vector &ea_data, SparseMatrix &mat,
const ElementRestriction &trial_restr) const
{
MFEM_VERIFY(ne == trial_restr.ne,
"ElementRestriction::FillJAndData: test/trial NE mismatch");
const int test_all_dofs = ndofs;
const int trial_all_dofs = trial_restr.ndofs;
const int test_vd = vdim;
const int trial_vd = trial_restr.vdim;
const int test_elt_dofs = dof;
const int trial_elt_dofs = trial_restr.dof;
const bool test_byvdim = byvdim;
const bool trial_byvdim = trial_restr.byvdim;
auto I = mat.ReadWriteI();
auto J = mat.WriteJ();
auto Data = mat.WriteData();
auto test_offsets = offsets.Read();
auto test_indices = indices.Read();
auto test_gather_map = gather_map.Read();
auto trial_offsets = trial_restr.offsets.Read();
auto trial_indices = trial_restr.indices.Read();
auto trial_gather_map = trial_restr.gather_map.Read();
auto mat_ea = Reshape(ea_data.Read(), test_elt_dofs, test_vd,
trial_elt_dofs, trial_vd, ne);
Array<int> test_el(indices.Size() * 3);
Array<int> trial_el(trial_restr.indices.Size() * 3);
auto d_test_el = Reshape(test_el.Write(), indices.Size(), 3);
auto d_trial_el = Reshape(trial_el.Write(), trial_restr.indices.Size(), 3);
mfem::forall(ne*test_elt_dofs*test_vd, [=] MFEM_HOST_DEVICE (int iE)
{
const int e = iE/(test_elt_dofs*test_vd);
const int it = iE%(test_elt_dofs*test_vd);
const int i = it%test_elt_dofs;
const int test_c = it/test_elt_dofs;
const int i_gm = e*test_elt_dofs + i;
const int i_gm_s = test_gather_map[i_gm];
const int i_dof = SignedIndexAbs(i_gm_s);
const int i_sgn = SignedIndexSign(i_gm_s);
const int i_L = DofToVDof(i_dof, test_c, test_all_dofs, test_vd,
test_byvdim);
const int i_offset = test_offsets[i_dof];
const int i_next_offset = test_offsets[i_dof+1];
const int i_nbElts = i_next_offset - i_offset;
int *i_elts = &d_test_el(i_offset, 0);
int *i_B = &d_test_el(i_offset, 1);
int *i_sgns = &d_test_el(i_offset, 2);
for (int e_i = 0; e_i < i_nbElts; ++e_i)
{
const int i_idx_s = test_indices[i_offset+e_i];
const int i_idx = SignedIndexAbs(i_idx_s);
i_elts[e_i] = i_idx/test_elt_dofs;
i_B[e_i] = i_idx%test_elt_dofs;
i_sgns[e_i] = SignedIndexSign(i_idx_s);
}
for (int trial_c = 0; trial_c < trial_vd; ++trial_c)
{
for (int j = 0; j < trial_elt_dofs; j++)
{
const int j_gm = e*trial_elt_dofs + j;
const int j_gm_s = trial_gather_map[j_gm];
const int j_dof = SignedIndexAbs(j_gm_s);
const int j_sgn = SignedIndexSign(j_gm_s);
const int j_L = DofToVDof(j_dof, trial_c, trial_all_dofs,
trial_vd, trial_byvdim);
const int j_offset = trial_offsets[j_dof];
const int j_next_offset = trial_offsets[j_dof+1];
const int j_nbElts = j_next_offset - j_offset;
if (i_nbElts == 1 || j_nbElts == 1)
{
const int nnz = GetAndIncrementNnzIndex(i_L, I);
J[nnz] = j_L;
Data[nnz] = i_sgn*j_sgn*mat_ea(i, test_c, j, trial_c, e);
}
else
{
int *j_elts = &d_trial_el(j_offset, 0);
int *j_B = &d_trial_el(j_offset, 1);
int *j_sgns = &d_trial_el(j_offset, 2);
for (int e_j = 0; e_j < j_nbElts; ++e_j)
{
const int j_idx_s = trial_indices[j_offset+e_j];
const int j_idx = SignedIndexAbs(j_idx_s);
j_elts[e_j] = j_idx/trial_elt_dofs;
j_B[e_j] = j_idx%trial_elt_dofs;
j_sgns[e_j] = SignedIndexSign(j_idx_s);
}
const int min_e = GetMinElt(i_elts, i_nbElts,
j_elts, j_nbElts);
if (e == min_e)
{
real_t val = 0.0;
for (int k = 0; k < i_nbElts; k++)
{
const int e_i = i_elts[k];
const int i_Bloc = i_B[k];
for (int l = 0; l < j_nbElts; l++)
{
const int e_j = j_elts[l];
const int j_Bloc = j_B[l];
if (e_i == e_j)
{
val += i_sgns[k]*j_sgns[l]*
mat_ea(i_Bloc, test_c, j_Bloc, trial_c, e_i);
}
}
}
const int nnz = GetAndIncrementNnzIndex(i_L, I);
J[nnz] = j_L;
Data[nnz] = val;
}
}
}
}
});
auto h_I = mat.HostReadWriteI();
const int size = test_vd*test_all_dofs;
for (int i = 0; i < size; i++)
{
h_I[size-i] = h_I[size-(i+1)];
}
h_I[0] = 0;
}
L2ElementRestriction::L2ElementRestriction(const FiniteElementSpace &fes)
: ne(fes.GetNE()),
vdim(fes.GetVDim()),
+13
View File
@@ -87,12 +87,25 @@ public:
/// Fill a Sparse Matrix with Element Matrices.
void FillSparseMatrix(const Vector &mat_ea, SparseMatrix &mat) const;
/** Fill a SparseMatrix with element matrices for this (test) restriction and
the given trial restriction. The element matrix layout is
test_dof x test_vdim x trial_dof x trial_vdim x ne. */
void FillSparseMatrix(const Vector &mat_ea, SparseMatrix &mat,
const ElementRestriction &trial_restr) const;
/** Fill the I array of SparseMatrix corresponding to the sparsity pattern
given by this ElementRestriction. */
int FillI(SparseMatrix &mat) const;
/** Fill the I array for this (test) and the given trial restriction. */
int FillI(SparseMatrix &mat, const ElementRestriction &trial_restr) const;
/** Fill the J and Data arrays of SparseMatrix corresponding to the sparsity
pattern given by this ElementRestriction, and the values of ea_data. */
void FillJAndData(const Vector &ea_data, SparseMatrix &mat) const;
/** Fill the J and Data arrays for this (test) and the given trial
restriction, using element matrix layout
test_dof x test_vdim x trial_dof x trial_vdim x ne. */
void FillJAndData(const Vector &ea_data, SparseMatrix &mat,
const ElementRestriction &trial_restr) const;
/// @private Not part of the public interface (device kernel limitation).
///
/// Performs either MultTranspose or AddMultTranspose depending on the
+20 -6
View File
@@ -8,12 +8,22 @@
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "../config/config.hpp"
#ifndef MFEM_ENZYME_HPP
#define MFEM_ENZYME_HPP
#include "../config/config.hpp" // IWYU pragma: keep
namespace mfem
{
inline constexpr bool UseEnzyme =
#ifdef MFEM_USE_ENZYME
true
#else
false
#endif
;
} // namespace mfem
#ifdef MFEM_USE_ENZYME
/*
* Variables prefixed with enzyme_* or function types prefixed with __enzyme_*,
@@ -27,6 +37,7 @@ extern int enzyme_dupnoneed;
extern int enzyme_out;
extern int enzyme_const;
extern int enzyme_interleave;
extern int enzyme_runtime_activity;
#if defined(MFEM_USE_CUDA) || defined(MFEM_USE_HIP)
#define MFEM_DEVICE_EXTERN_STMT(name) extern __device__ int name;
@@ -39,6 +50,7 @@ MFEM_DEVICE_EXTERN_STMT(enzyme_dupnoneed)
MFEM_DEVICE_EXTERN_STMT(enzyme_out)
MFEM_DEVICE_EXTERN_STMT(enzyme_const)
MFEM_DEVICE_EXTERN_STMT(enzyme_interleave)
MFEM_DEVICE_EXTERN_STMT(enzyme_runtime_activity)
// warning: if inlined, triggers function '__enzyme_autodiff' is not defined
template <typename return_type, typename... Args>
@@ -54,13 +66,15 @@ return_type __enzyme_fwddiff(Args...);
#define MFEM_ENZYME_INACTIVE __attribute__((enzyme_inactive))
#define MFEM_ENZYME_FN_LIKE(x) __attribute__((enzyme_function_like(#x)))
#else
#else // MFEM_USE_ENZYME
#define MFEM_ENZYME_INACTIVENOFREE
#define MFEM_ENZYME_INACTIVE
#define MFEM_ENZYME_FN_LIKE(x)
#endif
#endif // MFEM_USE_ENZYME
#define MFEM_ENZYME_FN_LIKE_FREE MFEM_ENZYME_FN_LIKE(free)
#define MFEM_ENZYME_FN_LIKE_DYNCAST MFEM_ENZYME_FN_LIKE(__dynamic_cast)
#endif
#endif // MFEM_ENZYME_HPP
+115 -16
View File
@@ -753,7 +753,7 @@ static void CuKernel3DLaunchBounds(const int N, BODY body)
for (int k = blockIdx.x; k < N; k += gridDim.x) { body(k); }
}
template <const int BLCK = MFEM_CUDA_BLOCKS, typename DBODY>
template <const int BLCK, typename DBODY>
void CuWrap1D(const int N, DBODY &&d_body)
{
if (N==0) { return; }
@@ -812,6 +812,11 @@ void CuWrap3DLaunchBounds(const int N, DBODY &&d_body,
MFEM_GPU_CHECK(cudaGetLastError());
}
#ifdef MFEM_USE_ENZYME
template <const int BLCK, typename DBODY>
void CuWrap1DWithEnzyme(const int N, DBODY &&d_body);
#endif
template <int Dim, int MAX_THREADS_PER_BLOCK> struct CuWrap;
template <int MAX_THREADS_PER_BLOCK>
@@ -870,6 +875,87 @@ struct CuWrap<3, MAX_THREADS_PER_BLOCK>
}
};
#ifdef MFEM_USE_ENZYME
template <typename BODY> struct DerivativeKernelWrapperStruct
{
MFEM_DEVICE static void CuWrap1DEnzymeBody(BODY *body, const int k)
{
(*body)(k);
}
__global__ static void FwdLaunch(const int N, BODY body, BODY d_body)
{
const int k = blockDim.x * blockIdx.x + threadIdx.x;
if (k >= N)
{
return;
}
__enzyme_fwddiff<void>(
(void*)CuWrap1DEnzymeBody, enzyme_dup,
(void*)&body, (void*)&d_body, enzyme_const, k, enzyme_runtime_activity);
}
__global__ static void Launch(const int N, BODY body)
{
const int k = blockDim.x * blockIdx.x + threadIdx.x;
if (k >= N)
{
return;
}
body(k);
}
};
template <const int BLCK, typename DBODY> struct CuWrap1DStruct
{
static constexpr int ACTUAL_BLCK = BLCK == 0 ? MFEM_CUDA_BLOCKS : BLCK;
static void Call(const int N, DBODY *body)
{
if (N == 0)
{
return;
}
const int GRID = (N + ACTUAL_BLCK - 1) / ACTUAL_BLCK;
DerivativeKernelWrapperStruct<DBODY>::Launch<<<GRID, ACTUAL_BLCK>>>(N, *body);
MFEM_GPU_CHECK(cudaGetLastError());
}
static void FwdCall(const int N, int dN, DBODY *body, DBODY *d_body)
{
MFEM_CONTRACT_VAR(dN);
if (N == 0)
{
return;
}
const int GRID = (N + ACTUAL_BLCK - 1) / ACTUAL_BLCK;
DerivativeKernelWrapperStruct<DBODY>::FwdLaunch<<<GRID, ACTUAL_BLCK>>>(N, *body,
*d_body);
MFEM_GPU_CHECK(cudaGetLastError());
}
inline static void *__enzyme_register_derivative_CuWrap1D[2] =
{
(void *)&Call, (void *)&FwdCall
};
};
template <const int BLCK, typename DBODY>
void CuWrap1DWithEnzyme(const int N, DBODY &&d_body)
{
using DBODY_BASE = std::remove_reference_t<DBODY>;
// Taking the address forces instantiation/emission of the registration
// global for this lambda type so Enzyme can find the custom derivative for
// CuWrap1DStruct<..., DBODY_BASE>::Call before trying to differentiate the
// CUDA runtime launch inside it.
[[maybe_unused]] auto *enzyme_registration =
&CuWrap1DStruct<BLCK, DBODY_BASE>::__enzyme_register_derivative_CuWrap1D;
MFEM_CONTRACT_VAR(enzyme_registration);
CuWrap1DStruct<BLCK, DBODY_BASE>::Call(N, &d_body);
}
#endif
#endif // defined(MFEM_USE_CUDA) && defined(__CUDACC__)
@@ -1037,7 +1123,7 @@ struct HipWrap<3, MAX_THREADS_PER_BLOCK>
///////////////////////////////////////////////////////////////////////////////
/// Forall host & device kernel dispatch
template <int DIM, int MAX_THREADS_PER_BLOCK = 0,
template <int DIM, int MAX_THREADS_PER_BLOCK = 0, bool use_enzyme = false,
typename d_lambda, typename h_lambda>
inline void ForallWrap(const bool use_dev, const int N,
d_lambda &&d_body, h_lambda &&h_body,
@@ -1071,6 +1157,20 @@ inline void ForallWrap(const bool use_dev, const int N,
// If Backend::CUDA is allowed, use it
if (Device::Allows(Backend::CUDA))
{
if constexpr (use_enzyme)
{
#ifdef MFEM_USE_ENZYME
static_assert(DIM == 1,
"Enzyme CUDA Wrappers are only implemented "
"for one dimensional thread blocks");
constexpr int BLCK = MAX_THREADS_PER_BLOCK == 0 ? MFEM_CUDA_BLOCKS :
MAX_THREADS_PER_BLOCK;
return CuWrap1DWithEnzyme<BLCK>(N, d_body);
#else
MFEM_ABORT("Enzyme not available");
#endif
}
return CuWrap<DIM, MAX_THREADS_PER_BLOCK>::run(N, d_body, X, Y, Z, G);
}
#endif
@@ -1110,26 +1210,25 @@ backend_cpu:
///////////////////////////////////////////////////////////////////////////////
/// Forall host & device kernel wrappers
template <int DIM, typename lambda>
template <int DIM, int MAX_THREADS_PER_BLOCK = 0, bool use_enzyme = false,
typename lambda>
inline void ForallWrap(const bool use_dev, const int N, lambda &&body,
const int X=0, const int Y=0, const int Z=0,
const int G=0)
{
ForallWrap<DIM>(use_dev, N, body, body, X, Y, Z, G);
}
template <int DIM, int MAX_THREADS_PER_BLOCK, typename lambda>
inline void ForallWrap(const bool use_dev, const int N, lambda &&body,
const int X=0, const int Y=0, const int Z=0,
const int G=0)
{
ForallWrap<DIM, MAX_THREADS_PER_BLOCK>(use_dev, N, body, body, X, Y, Z, G);
ForallWrap<DIM, MAX_THREADS_PER_BLOCK, use_enzyme>(use_dev, N, body, body, X, Y,
Z, G);
}
///////////////////////////////////////////////////////////////////////////////
// forall interfaces
template<typename lambda>
inline void forall(int N, lambda &&body) { ForallWrap<1>(true, N, body); }
template<bool use_enzyme = false, typename lambda>
inline void forall(int N, lambda &&body)
{
constexpr int MAX_THREADS_PER_BLOCK = 0;
ForallWrap<1, MAX_THREADS_PER_BLOCK, use_enzyme>(true, N, body);
}
template<typename lambda>
inline void forall(int Nx, int Ny, lambda &&body)
@@ -1277,9 +1376,9 @@ template<typename lambda>
inline void hypre_forall_gpu(int N, lambda &&body)
{
#if defined(HYPRE_USING_CUDA)
CuWrap1D(N, body);
CuWrap1D<MFEM_CUDA_BLOCKS>(N, body);
#elif defined(HYPRE_USING_HIP)
HipWrap1D(N, body);
HipWrap1D<MFEM_HIP_BLOCKS>(N, body);
#else
#error Unknown HYPRE GPU backend!
#endif
+2
View File
@@ -27,6 +27,7 @@ list(APPEND SRCS
handle.cpp
matrix.cpp
mma.cpp
multivector.cpp
ode.cpp
operator.cpp
ordering.cpp
@@ -63,6 +64,7 @@ list(APPEND HDRS
linalg.hpp
matrix.hpp
mma.hpp
multivector.hpp
ode.hpp
operator.hpp
ordering.hpp
+2
View File
@@ -15,6 +15,7 @@
// Linear algebra header file
#include "vector.hpp"
#include "multivector.hpp"
#include "operator.hpp"
#include "matrix.hpp"
#include "sparsemat.hpp"
@@ -37,6 +38,7 @@
#include "batched/gpu_blas.hpp"
#include "batched/solver.hpp"
#include "tensor.hpp"
#include "tensor_arrays.hpp"
#include "filteredsolver.hpp"
#include "ordering.hpp"
#include "particlevector.hpp"
+60
View File
@@ -0,0 +1,60 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "multivector.hpp"
namespace mfem
{
MultiVector::MultiVector(const Array<int> &vector_sizes)
{
SetSizes(vector_sizes);
}
MultiVector::MultiVector(const Array<int> &vector_sizes, MemoryType mt)
{
SetSizes(vector_sizes, mt);
}
MultiVector::MultiVector(Vector &base, const Array<int> &vector_sizes)
{
MakeRef(base, vector_sizes);
}
void MultiVector::SetSizes(const Array<int> &vector_sizes)
{
blocks.resize(vector_sizes.Size());
for (int i = 0; i < vector_sizes.Size(); i++)
{
operator[](i).SetSize(vector_sizes[i]);
}
}
void MultiVector::SetSizes(const Array<int> &vector_sizes, MemoryType mt)
{
blocks.resize(vector_sizes.Size());
for (int i = 0; i < vector_sizes.Size(); i++)
{
operator[](i).SetSize(vector_sizes[i], mt);
}
}
void MultiVector::MakeRef(Vector &base, const Array<int> &vector_sizes)
{
blocks.resize(vector_sizes.Size());
for (int offset = 0, i = 0; i < vector_sizes.Size(); i++)
{
blocks[i].emplace<0>(base, offset, vector_sizes[i]);
offset += vector_sizes[i];
}
}
} // namespace mfem
+240
View File
@@ -0,0 +1,240 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#ifndef MFEM_MULTIVECTOR_HPP
#define MFEM_MULTIVECTOR_HPP
#include "../general/array.hpp"
#include "vector.hpp"
#include <vector>
#include <array>
#include <variant>
namespace mfem
{
/// Class representing an array of Vectors with generally different sizes.
/** This class is similar to BlockVector with the following two main
differences:
- the data for the individual Vector blocks does not need to be part of one
big contiguous memory allocation;
- this class does not inherit from class Vector (as a consequence of the
first bullet).
Internally, each Vector block is represented as either:
- (default) a Vector object constructed and owned by this class; this
object, in turn, as any Vector object, can own its Memory allocation or
refer to a sub-Memory of another Memory object; or
- a pointer to an externally allocated Vector or classes derived from
Vector. */
class MultiVector
{
private:
std::vector<std::variant<Vector,Vector*,const Vector*>> blocks;
public:
/// Create an empty MultiVector with zero blocks.
MultiVector() = default;
/** @brief Create a MultiVector with @a num_blocks blocks. The individual
Vector blocks are default initialized, i.e. they all have size zero. */
MultiVector(int num_blocks)
: blocks(num_blocks) { }
/** @brief Construct a MultiVector with number of blocks and individual block
Vector sizes given by @a vector_sizes.
@note The memory of the individual Vector blocks is NOT initialized. */
MultiVector(const Array<int> &vector_sizes);
/** @brief Construct a MultiVector with number of blocks and individual block
Vector sizes given by @a vector_sizes. All Vector blocks use the
MemoryType @a mt.
@note The memory of the individual Vector blocks is NOT initialized. */
MultiVector(const Array<int> &vector_sizes, MemoryType mt);
/** @brief Construct a MultiVector referencing data within a given monolithic
Vector @a base.
With this constructor, the Memory flags of @a base and of the individual
Vector blocks may need to be explicitly synchronized when data is moved
between host and device. */
MultiVector(Vector &base, const Array<int> &vector_sizes);
/** @brief Construct a MultiVector referencing multiple Vectors given as
arguments.
The VectorTypes reference arguments are expected to be static_cast-able
to (Vector &) which is the case if the types are derived from Vector,
e.g. HypreParVector, GridFunction, etc.
With this constructor, operations on individual Vector blocks are
performed directly on the objects @a vs. In particular, there is no need
to synchronize the Memory flags of @a vs and the ones of the individual
Vector blocks when data is moved between host and device. */
template <typename... VectorTypes,
std::enable_if_t<
std::conjunction_v<
std::is_convertible<VectorTypes&,Vector&>...>, bool> = true>
MultiVector(VectorTypes &...vs) { MakeRef(vs...); }
/// Return the number of Vectors in the MultiVector.
int NumBlocks() const { return blocks.size(); }
/** @brief Set the number of Vectors in the MultiVector. Existing Vector
blocks will remain unmodified. New Vector blocks will be default
initialized, i.e. they all have size zero. */
void SetNumBlocks(int num_blocks) { blocks.resize(num_blocks); }
/// Read-write access to the i-th Vector.
inline Vector &operator[](int i);
/// Read-only access to the i-th Vector.
inline const Vector &operator[](int i) const;
/** @brief Update the MultiVector according to the given @a vector_sizes.
This method can be used to add or remove blocks. The individual Vector
sizes are updated using the method Vector::SetSize(int). */
void SetSizes(const Array<int> &vector_sizes);
/** @brief Update the MultiVector according to the given @a vector_sizes and
MemoryType @a mt.
This method can be used to add or remove blocks. The individual Vector
sizes and MemoryType are updated using the method
Vector::SetSize(int, MemoryType). */
void SetSizes(const Array<int> &vector_sizes, MemoryType mt);
/** @brief Update the MultiVector to reference data within a given monolithic
Vector @a base.
After calling this method, the Memory flags of @a base and of the
individual Vector blocks may need to be explicitly synchronized when data
is moved between host and device.*/
void MakeRef(Vector &base, const Array<int> &vector_sizes);
/** @brief Update the @a i-th MultiVector block to reference data within the
given monolithic Vector @a base at the given @a offset and with the given
@a size.
After calling this method, the Memory flags of @a base and of the @a i-th
Vector block may need to be explicitly synchronized when data is moved
between host and device.*/
inline void MakeRef(int i, Vector &base, int offset, int size)
{
blocks[i].emplace<0>(base, offset, size);
}
/** @brief Update the MultiVector to reference multiple Vectors given as
arguments.
The VectorTypes reference arguments are expected to be static_cast-able
to (Vector &) which is the case if the types are derived from Vector,
e.g. HypreParVector, GridFunction, etc.
After calling this method, operations on individual Vector blocks are
performed directly on the objects @a vs. In particular, there is no need
to synchronize the Memory flags of @a vs and the ones of the individual
Vector blocks when data is moved between host and device. */
template <typename... VectorTypes,
std::enable_if_t<
std::conjunction_v<
std::is_convertible<VectorTypes&,Vector&>...>, bool> = true>
inline void MakeRef(VectorTypes &...vs);
/** @brief Update the @a i-th MultiVector block to reference the given
Vector @a v.
After calling this method, operations on the @a i-th Vector block are
performed directly on the Vector @a v. In particular, there is no need
to synchronize the Memory flags of @a v and the ones of the @a i-th
Vector blocks when data is moved between host and device. */
inline void MakeRef(int i, Vector &v) { blocks[i] = &v; }
/** @brief Construct a MultiVector referencing multiple const Vectors given
as arguments. Individual blocks are read-only; non-const operator[]
will assert. */
template <typename... VectorTypes,
std::enable_if_t<
std::conjunction_v<
std::is_convertible<const VectorTypes&,const Vector&>...>, bool> = true>
MultiVector(const VectorTypes &...vs) { MakeRef(vs...); }
/** @brief Update the @a i-th MultiVector block to reference the given
const Vector @a v. The block becomes read-only. */
inline void MakeRef(int i, const Vector &v) { blocks[i] = &v; }
/** @brief Update the MultiVector to reference multiple const Vectors given
as arguments. Individual blocks are read-only; non-const operator[]
will assert. */
template <typename... VectorTypes,
std::enable_if_t<
std::conjunction_v<
std::is_convertible<const VectorTypes&,const Vector&>...>, bool> = true>
inline void MakeRef(const VectorTypes &...vs);
};
// Inline and template methods
inline Vector &MultiVector::operator[](int i)
{
auto &bi = blocks[i];
MFEM_ASSERT(bi.index() != 2, "Non-const access to a const Vector block");
return (bi.index() == 0) ? std::get<0>(bi) : *std::get<1>(bi);
}
inline const Vector &MultiVector::operator[](int i) const
{
auto &bi = blocks[i];
return (bi.index() == 0) ? std::get<0>(bi) :
(bi.index() == 1) ? *std::get<1>(bi) :
/**/ *std::get<2>(bi);
}
template <typename... VectorTypes,
std::enable_if_t<
std::conjunction_v<
std::is_convertible<VectorTypes&,Vector&>...>, bool>>
inline void MultiVector::MakeRef(VectorTypes &...vs)
{
blocks.resize(sizeof...(vs));
if constexpr (sizeof...(vs) > 0)
{
const std::array vs_p{&static_cast<Vector&>(vs)...};
for (std::size_t i = 0; i < sizeof...(vs); i++)
{
blocks[i] = vs_p[i];
}
}
}
template <typename... VectorTypes,
std::enable_if_t<
std::conjunction_v<
std::is_convertible<const VectorTypes&,const Vector&>...>, bool>>
inline void MultiVector::MakeRef(const VectorTypes &...vs)
{
blocks.resize(sizeof...(vs));
if constexpr (sizeof...(vs) > 0)
{
const std::array vs_p{&static_cast<const Vector&>(vs)...};
for (std::size_t i = 0; i < sizeof...(vs); i++)
{
blocks[i] = vs_p[i];
}
}
}
} // namespace mfem
#endif // MFEM_MULTIVECTOR_HPP
+1
View File
@@ -13,6 +13,7 @@
#define MFEM_OPERATOR
#include "vector.hpp"
#include "multivector.hpp"
namespace mfem
{
+157 -121
View File
@@ -17,150 +17,145 @@
#pragma once
#include "../general/backends.hpp"
#include "dual.hpp"
#include <limits>
#include <utility>
#include <type_traits> // for std::false_type
// Force-inline every tensor operation under clang
#if defined(__clang__)
#pragma clang attribute push (__attribute__((always_inline)), apply_to = function)
#endif
namespace mfem
{
namespace future
{
template <typename T, int... n>
template <typename T, int... Dims>
struct tensor;
/// The implementation can be drastically generalized by using concepts of the
/// c++17 standard.
template < typename T >
template <typename T>
struct tensor<T>
{
using type = T;
static constexpr int ndim = 1;
static constexpr int ndim = 1;
static constexpr int first_dim = 0;
MFEM_HOST_DEVICE T& operator[](int /*unused*/) { return values; }
MFEM_HOST_DEVICE const T& operator[](int /*unused*/) const { return values; }
MFEM_HOST_DEVICE T& operator()(int /*unused*/) { return values; }
MFEM_HOST_DEVICE const T& operator()(int /*unused*/) const { return values; }
MFEM_HOST_DEVICE tensor() = default;
MFEM_HOST_DEVICE tensor(T val) : values(val) {}
MFEM_HOST_DEVICE T& operator[](int) { return values; }
MFEM_HOST_DEVICE const T& operator[](int) const { return values; }
MFEM_HOST_DEVICE T& operator()() { return values; }
MFEM_HOST_DEVICE const T& operator()() const { return values; }
MFEM_HOST_DEVICE T& operator()(int) { return values; }
MFEM_HOST_DEVICE const T& operator()(int) const { return values; }
MFEM_HOST_DEVICE operator T() const { return values; }
MFEM_HOST_DEVICE tensor& operator=(T val) { values = val; return *this; }
T values;
};
template < typename T, int n0 >
struct tensor<T, n0>
template <typename T, int N0>
struct tensor<T, N0>
{
using type = T;
static constexpr int ndim = 1;
static constexpr int first_dim = n0;
static constexpr int ndim = 1;
static constexpr int first_dim = N0;
MFEM_HOST_DEVICE T& operator[](int i) { return values[i]; }
MFEM_HOST_DEVICE const T& operator[](int i) const { return values[i]; }
MFEM_HOST_DEVICE T& operator()(int i) { return values[i]; }
MFEM_HOST_DEVICE const T& operator()(int i) const { return values[i]; }
T values[n0];
T values[N0];
};
template < typename T >
template <typename T>
struct tensor<T, 0>
{
using type = T;
static constexpr int ndim = 1;
static constexpr int ndim = 1;
static constexpr int first_dim = 0;
MFEM_HOST_DEVICE T& operator[](int /*unused*/) { return values; }
MFEM_HOST_DEVICE const T& operator[](int /*unused*/) const { return values; }
MFEM_HOST_DEVICE T& operator()(int /*unused*/) { return values; }
MFEM_HOST_DEVICE const T& operator()(int /*unused*/) const { return values; }
MFEM_HOST_DEVICE T& operator[](int) { return values; }
MFEM_HOST_DEVICE const T& operator[](int) const { return values; }
MFEM_HOST_DEVICE T& operator()(int) { return values; }
MFEM_HOST_DEVICE const T& operator()(int) const { return values; }
T values;
};
template < typename T, int n0, int n1 >
struct tensor<T, n0, n1>
template <typename T, int N0, int N1, int... Rest>
struct tensor<T, N0, N1, Rest...>
{
using type = T;
static constexpr int ndim = 2;
static constexpr int first_dim = n0;
MFEM_HOST_DEVICE tensor< T, n1 >& operator[](int i) { return values[i]; }
MFEM_HOST_DEVICE const tensor< T, n1 >& operator[](int i) const { return values[i]; }
MFEM_HOST_DEVICE tensor< T, n1 >& operator()(int i) { return values[i]; }
MFEM_HOST_DEVICE const tensor< T, n1 >& operator()(int i) const { return values[i]; }
MFEM_HOST_DEVICE T& operator()(int i, int j) { return values[i][j]; }
MFEM_HOST_DEVICE const T& operator()(int i, int j) const { return values[i][j]; }
tensor < T, n1 > values[n0];
};
using sub_tensor = tensor<T, N1, Rest...>;
static constexpr int ndim = 2 + sizeof...(Rest);
static constexpr int first_dim = N0;
template < typename T, int n1 >
struct tensor<T, 0, n1>
{
using type = T;
static constexpr int ndim = 2;
static constexpr int first_dim = 0;
MFEM_HOST_DEVICE tensor< T, n1 >& operator[](int /*unused*/) { return values; }
MFEM_HOST_DEVICE const tensor< T, n1 >& operator[](int /*unused*/) const { return values; }
MFEM_HOST_DEVICE tensor< T, n1 >& operator()(int /*unused*/) { return values; }
MFEM_HOST_DEVICE const tensor< T, n1 >& operator()(int /*unused*/) const { return values; }
MFEM_HOST_DEVICE T& operator()(int /*unused*/, int j) { return values[j]; }
MFEM_HOST_DEVICE const T& operator()(int /*unused*/, int j) const { return values[j]; }
tensor < T, n1 > values;
};
static constexpr bool is_zero_dim = (N0 == 0);
static constexpr int storage_size = is_zero_dim ? 1 : N0;
using storage_type =
std::conditional_t<is_zero_dim, sub_tensor, sub_tensor[storage_size]>;
storage_type values;
template < typename T, int n0, int n1, int n2 >
struct tensor<T, n0, n1, n2>
{
using type = T;
static constexpr int ndim = 3;
static constexpr int first_dim = n0;
MFEM_HOST_DEVICE tensor< T, n1, n2 >& operator[](int i) { return values[i]; }
MFEM_HOST_DEVICE const tensor< T, n1, n2 >& operator[](int i) const { return values[i]; }
MFEM_HOST_DEVICE tensor< T, n1, n2 >& operator()(int i) { return values[i]; }
MFEM_HOST_DEVICE const tensor< T, n1, n2 >& operator()(int i) const { return values[i]; }
MFEM_HOST_DEVICE tensor< T, n2 >& operator()(int i, int j) { return values[i][j]; }
MFEM_HOST_DEVICE const tensor< T, n2 >& operator()(int i, int j) const { return values[i][j]; }
MFEM_HOST_DEVICE T& operator()(int i, int j, int k) { return values[i][j][k]; }
MFEM_HOST_DEVICE const T& operator()(int i, int j, int k) const { return values[i][j][k]; }
tensor < T, n1, n2 > values[n0];
};
MFEM_HOST_DEVICE sub_tensor& operator[](int i)
{
if constexpr (is_zero_dim)
{
static_cast<void>(i);
return values;
}
else { return values[i]; }
}
template < typename T, int n0, int n1, int n2, int n3 >
struct tensor<T, n0, n1, n2, n3>
{
using type = T;
static constexpr int ndim = 4;
static constexpr int first_dim = n0;
MFEM_HOST_DEVICE tensor< T, n1, n2, n3 >& operator[](int i) { return values[i]; }
MFEM_HOST_DEVICE const tensor< T, n1, n2, n3 >& operator[](int i) const { return values[i]; }
MFEM_HOST_DEVICE tensor< T, n1, n2, n3 >& operator()(int i) { return values[i]; }
MFEM_HOST_DEVICE const tensor< T, n1, n2, n3 >& operator()(int i) const { return values[i]; }
MFEM_HOST_DEVICE tensor< T, n2, n3 >& operator()(int i, int j) { return values[i][j]; }
MFEM_HOST_DEVICE const tensor< T, n2, n3 >& operator()(int i, int j) const { return values[i][j]; }
MFEM_HOST_DEVICE tensor< T, n3 >& operator()(int i, int j, int k) { return values[i][j][k]; }
MFEM_HOST_DEVICE const tensor< T, n3 >& operator()(int i, int j, int k) const { return values[i][j][k]; }
MFEM_HOST_DEVICE T& operator()(int i, int j, int k, int l) { return values[i][j][k][l]; }
MFEM_HOST_DEVICE const T& operator()(int i, int j, int k, int l) const { return values[i][j][k][l]; }
tensor < T, n1, n2, n3 > values[n0];
};
MFEM_HOST_DEVICE const sub_tensor& operator[](int i) const
{
if constexpr (is_zero_dim)
{
static_cast<void>(i);
return values;
}
else { return values[i]; }
}
template < typename T, int n0, int n1, int n2, int n3, int n4 >
struct tensor<T, n0, n1, n2, n3, n4>
{
using type = T;
static constexpr int ndim = 5;
static constexpr int first_dim = n0;
MFEM_HOST_DEVICE tensor< T, n1, n2, n3, n4 >& operator[](int i) { return values[i]; }
MFEM_HOST_DEVICE const tensor< T, n1, n2, n3, n4 >& operator[](int i) const { return values[i]; }
MFEM_HOST_DEVICE tensor< T, n1, n2, n3, n4 >& operator()(int i) { return values[i]; }
MFEM_HOST_DEVICE const tensor< T, n1, n2, n3, n4 >& operator()(int i) const { return values[i]; }
MFEM_HOST_DEVICE tensor< T, n2, n3, n4 >& operator()(int i, int j) { return values[i][j]; }
MFEM_HOST_DEVICE const tensor< T, n2, n3, n4 >& operator()(int i,
int j) const { return values[i][j]; }
MFEM_HOST_DEVICE tensor< T, n3, n4>& operator()(int i, int j, int k) { return values[i][j][k]; }
MFEM_HOST_DEVICE const tensor< T, n3, n4>& operator()(int i, int j,
int k) const { return values[i][j][k]; }
MFEM_HOST_DEVICE tensor< T, n4 >& operator()(int i, int j, int k, int l) { return values[i][j][k][l]; }
MFEM_HOST_DEVICE const tensor< T, n4 >& operator()(int i, int j, int k,
int l) const { return values[i][j][k][l]; }
MFEM_HOST_DEVICE T& operator()(int i, int j, int k, int l, int m) { return values[i][j][k][l][m]; }
MFEM_HOST_DEVICE const T& operator()(int i, int j, int k, int l, int m) const { return values[i][j][k][l][m]; }
tensor < T, n1, n2, n3, n4 > values[n0];
MFEM_HOST_DEVICE sub_tensor& operator()(int i)
{
return (*this)[i];
}
MFEM_HOST_DEVICE const sub_tensor& operator()(int i) const
{
return (*this)[i];
}
template <typename... Is>
MFEM_HOST_DEVICE auto& operator()(int i, int j, Is... rest)
{
if constexpr (sizeof...(rest) == 0)
{
return (*this)[i][j];
}
else
{
return (*this)[i](j, rest...);
}
}
template <typename... Is>
MFEM_HOST_DEVICE const auto& operator()(int i, int j, Is... rest) const
{
if constexpr (sizeof...(rest) == 0)
{
return (*this)[i][j];
}
else
{
return (*this)[i](j, rest...);
}
}
};
/**
@@ -270,10 +265,10 @@ MFEM_HOST_DEVICE constexpr zero operator/(zero, T /*other*/)
return zero{};
}
/** @brief `zero` plus `zero` is `zero */
/** @brief `zero` plus `zero` is `zero` */
MFEM_HOST_DEVICE constexpr zero operator+=(zero, zero) { return zero{}; }
/** @brief `zero` minus `zero` is `zero */
/** @brief `zero` minus `zero` is `zero` */
MFEM_HOST_DEVICE constexpr zero operator-=(zero, zero) { return zero{}; }
/** @brief let `zero` be accessed like a tuple */
@@ -305,13 +300,10 @@ MFEM_HOST_DEVICE zero dot(zero, const T&)
* @tparam n2 The second dimension
*/
template <typename T, int n1, int n2 = 1>
using reduced_tensor = typename std::conditional<
(n1 == 1 && n2 == 1), T,
typename std::conditional<n1 == 1, tensor<T, n2>,
typename std::conditional<n2 == 1, tensor<T, n1>, tensor<T, n1, n2>
>::type
>::type
>::type;
using reduced_tensor =
std::conditional_t<(n1 == 1 && n2 == 1), T,
std::conditional_t<(n1 == 1), tensor<T, n2>,
std::conditional_t<(n2 == 1), tensor<T, n1>, tensor<T, n1, n2>>>>;
/**
* @brief Creates a tensor of requested dimension by subsequent calls to a functor
@@ -462,7 +454,7 @@ tensor<T, n> get_col(tensor<T, m, n> A, int j)
/// @overload
template <typename T> MFEM_HOST_DEVICE
tensor<T, 1> get_col(tensor<T, 1, 1> A, int j)
tensor<T, 1> get_col(tensor<T, 1, 1> A, [[maybe_unused]] int j)
{
return tensor<T, 1> {A[0][0]};
}
@@ -541,9 +533,16 @@ MFEM_HOST_DEVICE auto operator*(S scale, const tensor<T, n...>& A) ->
tensor<decltype(S {} * T{}), n...>
{
tensor<decltype(S{} * T{}), n...> C{};
for (int i = 0; i < tensor<T, n...>::first_dim; i++)
if constexpr (sizeof...(n) == 0)
{
C[i] = scale * A[i];
C.values = scale * A.values;
}
else
{
for (int i = 0; i < tensor<T, n...>::first_dim; i++)
{
C[i] = scale * A[i];
}
}
return C;
}
@@ -563,9 +562,16 @@ MFEM_HOST_DEVICE auto operator*(const tensor<T, n...>& A, S scale) ->
tensor<decltype(T {} * S{}), n...>
{
tensor<decltype(T{} * S{}), n...> C{};
for (int i = 0; i < tensor<T, n...>::first_dim; i++)
if constexpr (sizeof...(n) == 0)
{
C[i] = A[i] * scale;
C.values = A.values * scale;
}
else
{
for (int i = 0; i < tensor<T, n...>::first_dim; i++)
{
C[i] = A[i] * scale;
}
}
return C;
}
@@ -729,9 +735,9 @@ auto outer(S A, T B) -> decltype(A * B)
}
template <typename T, int n, int m> MFEM_HOST_DEVICE
tensor<T, n + m> flatten(tensor<T, n, m> A)
tensor<T, n * m> flatten(tensor<T, n, m> A)
{
tensor<T, n + m> B{};
tensor<T, n * m> B{};
for (int i = 0; i < n; i++)
{
for (int j = 0; j < m; j++)
@@ -1218,6 +1224,32 @@ decltype(S {} * T{})
return AB;
}
// tensor<T> (rank-0 scalar wrapper) acts as a scalar in multiplication
template <typename S, typename T, int... m,
typename = typename std::enable_if<(sizeof...(m) > 0)>::type>
MFEM_HOST_DEVICE
auto operator*(const tensor<S, m...>& A, const tensor<T>& scale) ->
tensor<decltype(S {} * T{}), m...>
{
return A * static_cast<T>(scale);
}
template <typename S, typename T, int... m,
typename = typename std::enable_if<(sizeof...(m) > 0)>::type>
MFEM_HOST_DEVICE
auto operator*(const tensor<T>& scale, const tensor<S, m...>& A) ->
tensor<decltype(T {} * S{}), m...>
{
return static_cast<T>(scale) * A;
}
template <typename S, typename T> MFEM_HOST_DEVICE
auto operator*(const tensor<S>& A, const tensor<T>& B) ->
tensor<decltype(S {} * T{})>
{
return tensor<decltype(S{} * T{})>{A.values * B.values};
}
/**
* @brief this is a shorthand for dot(A, B)
*/
@@ -1507,7 +1539,7 @@ void GetScalingFactor(const T &d_max, T &mult)
}
template <typename T> MFEM_HOST_DEVICE
T calcsv(const tensor<T, 1, 1> A, const int i)
T calcsv(const tensor<T, 1, 1> A, [[maybe_unused]] const int i)
{
return A[0][0];
}
@@ -2288,3 +2320,7 @@ auto ddot(const isotropic_tensor<S, m, m, m, m>& I,
} // namespace future
} // namespace mfem
#if defined(__clang__)
#pragma clang attribute pop
#endif
+390
View File
@@ -0,0 +1,390 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#ifndef MFEM_TENSOR_ARRAYS_HPP
#define MFEM_TENSOR_ARRAYS_HPP
#include "tensor.hpp"
#include <array> // std::array, std::size_t (indirectly)
#include <type_traits> /* std::remove_cv_t, std::remove_reference_t,
std::is_const_v */
#include <utility> /* std::forward, std::index_sequence,
std::make_index_sequence */
#include <algorithm> // std::min
#include <tuple> // std::apply, std::tuple_size_v
#include <numeric> // std::iota
namespace mfem::future
{
template <std::size_t... Is, typename Fn>
constexpr inline void for_unrolled_simple(std::index_sequence<Is...>, Fn &&fn)
{
(fn(Is), ...);
}
template <int... loop_sizes>
#ifdef MFEM_USE_ENZYME
__attribute__((annotate("enzyme_inactive")))
#endif
constexpr inline auto to_multiindex(std::size_t i)
{
constexpr auto dims = sizeof...(loop_sizes);
constexpr std::array<std::size_t,dims> sizes{loop_sizes...};
std::array<std::size_t,dims> is{}; // value initialization with zeros
for (std::size_t d = 0; d < dims; d++)
{
is[d] = i%sizes[d];
i /= sizes[d];
}
return is;
}
/// lambda_t:
/// - input: const std::array<std::size_t,sizeof...(loop_sizes)> &
/// - output: void
/// Note: 0D loop executes the lambda one time with an array of dim 0.
template <int... loop_sizes, typename lambda_t>
constexpr inline void for_multiindex(lambda_t f)
{
constexpr auto dims = sizeof...(loop_sizes);
if constexpr (dims == 0)
{
f(std::array<std::size_t,0> {});
}
else
{
if constexpr (std::min({loop_sizes...}) <= 0) { return; }
constexpr auto total_loop_size = (loop_sizes * ...);
for_unrolled_simple(std::make_index_sequence<total_loop_size> {},
[&f](std::size_t i)
{
f(to_multiindex<loop_sizes...>(i));
});
}
}
namespace detail
{
template <typename Fn, typename Tuple, std::size_t... Is>
inline constexpr decltype(auto) apply_impl(Fn&& f, Tuple&& t,
std::index_sequence<Is...>)
{
using std::get;
return std::forward<Fn>(f)(get<Is>(std::forward<Tuple>(t))...);
}
} // namespace detail
/// Extend std::apply to work with 0-size arrays and mfem::future::tuple.
template <typename Fn, typename Tuple>
inline constexpr decltype(auto) apply(Fn&& f, Tuple&& t)
{
constexpr auto size = std::tuple_size_v<std::remove_reference_t<Tuple>>;
if constexpr (size == 0)
{ return std::forward<Fn>(f)(); }
return detail::apply_impl(std::forward<Fn>(f), std::forward<Tuple>(t),
std::make_index_sequence<size> {});
}
/// Multi-dimensional array of tensors of the same size.
/** The array sizes are dynamic while the tensor sizes are static, i.e. template
parameters.
This class provides flexible global data layout where the dynamic (array)
dimnsions and the tensor dimnsions are stored in memory using a runtime
defined strided layout. */
template <typename scalar_t, int ndims, int... tensor_sizes>
class tensor_ndarray
{
public:
using scalar_type = scalar_t;
using tensor_type = tensor<std::remove_cv_t<scalar_t>,tensor_sizes...>;
static constexpr auto tensor_dims = sizeof...(tensor_sizes);
static constexpr auto total_dims = ndims + tensor_dims;
static constexpr auto tensor_sizes_array() noexcept
{
return std::array<std::size_t, tensor_dims> {tensor_sizes...};
}
private:
scalar_t *data; /// Not owned
public:
std::array<std::size_t,ndims> dyn_sizes;
mutable std::array<std::size_t,total_dims> strides;
public:
/** @brief Constructor with the default, column-major or left, layout where
the dynamic dimensions are first, on the left, and the tensor dimensions
are second. */
tensor_ndarray(scalar_t *ptr, std::array<std::size_t,ndims> dynamic_sizes)
: data(ptr), dyn_sizes(dynamic_sizes)
{
std::array<std::size_t,total_dims> default_perm;
std::iota(default_perm.begin(), default_perm.end(), 0); // 0, 1, 2, ...
set_layout(default_perm);
}
/// Number of dynamic array dimensions.
static constexpr std::size_t rank() { return ndims; }
/// Array size in the @a k-th dynamic dimension.
MFEM_HOST_DEVICE std::size_t size(int k = 0) const { return dyn_sizes[k]; }
/// Returns the product of all sizes of the dynamic dimensions.
MFEM_HOST_DEVICE std::size_t total_size() const
{
std::size_t t = 1;
for (int d = 0; d < ndims; d++)
{
t *= dyn_sizes[d];
}
return t;
}
/// Number of tensor (static) dimensions.
static constexpr std::size_t tensor_rank()
{ return sizeof...(tensor_sizes); }
/// Tensor size in the @a k-th tensor (static) dimension.
static constexpr std::size_t tensor_size(int k = 0)
{
return tensor_sizes_array()[k];
}
/// Returns the product of all sizes of the static (tensor) dimensions.
static constexpr std::size_t total_tensor_size()
{ return (tensor_sizes * ...); }
/// Set the global data layout based on the given permutation @a perm.
/** The entries of @a perm are numbers identifying either a dynamic or a
tensor (static) dimension. Values in the range [0,rank()) identify the
dynamic dimensions and values in the range [rank(),rank()+tensor_rank())
identify the tensor dymensions. The first entry in @a perm determines
which dynamic or tensor dimension will have stride 1. The k-th entry of
@a perm determines which dimension will use the next stride which is
defined as the product of the sizes of all k-1 previous dimensions from
@a perm.
@note The default layout corresponds to the identity permutation:
{ 0, 1, ..., rank()+tensor_rank()-1 }.
@note This method does not permute the global 1D data array. */
MFEM_HOST_DEVICE
#ifdef MFEM_USE_ENZYME
__attribute__((annotate("enzyme_inactive")))
#endif
void set_layout(std::array<std::size_t,rank()+tensor_rank()> perm) const
{
std::size_t stride = 1;
for (std::size_t d_g = 0; d_g < total_dims; d_g++)
{
const auto d_l = perm[d_g];
strides[d_l] = stride;
stride *= (d_l < ndims) ? dyn_sizes[d_l] :
tensor_sizes_array()[d_l-ndims];
}
}
/** @brief Comute the dynamic offset for a given dynamic multi-index @a is.
The total offset in the global data array is the sum of the dynamic and
static (tensor) offsets. */
MFEM_HOST_DEVICE
std::size_t get_dynamic_offset(
const std::array<std::size_t,rank()> &is) const
{
std::size_t dynamic_offset = 0;
for (std::size_t d = 0; d < ndims; d++)
{
dynamic_offset += is[d]*strides[d];
}
return dynamic_offset;
}
/** @brief Comute the static (tensor) offset for a given tensor multi-index
@a js. The total offset in the global data array is the sum of the
dynamic and static (tensor) offsets. */
MFEM_HOST_DEVICE
std::size_t get_static_offset(
const std::array<std::size_t,tensor_rank()> &js) const
{
std::size_t static_offset = 0;
if constexpr (tensor_dims > 0)
{
for (std::size_t d = 0; d < tensor_dims; d++)
{
static_offset += js[d]*strides[ndims+d];
}
}
return static_offset;
}
/** @brief Return a local tensor extracted from the global data array
corresponding to the given dynamic multi-index @a is. */
/** @note Return a const tensor to prevent attempts to assign to the
temporary object which is considered a mistake. */
MFEM_HOST_DEVICE
const tensor_type get_tensor(std::array<std::size_t,rank()> is) const
{
tensor_type result;
const std::size_t dynamic_offset = get_dynamic_offset(is);
for_multiindex<tensor_sizes...>(
[&result, this, dynamic_offset](
const std::array<std::size_t,tensor_rank()> &js)
{
::mfem::future::apply(result, js) =
data[dynamic_offset + get_static_offset(js)];
});
return result;
}
/** @brief Return a local tensor extracted from the global data array
corresponding to the given dynamic indices @a is. */
/** @note Return a const tensor to prevent attempts to assign to the
temporary object which is considered a mistake. */
template <typename... index_types> MFEM_HOST_DEVICE
const tensor_type get_tensor(index_types... is) const
{
static_assert(sizeof...(is) == rank(), "invalid number of indices!");
return get_tensor(std::array<std::size_t,rank()> {std::size_t(is)...});
}
/** @brief Returns one of the following depending on the type scalar_t:
- get_tensor(std::array<std::size_t,rank()>) iff scalar_t is const,
- get_accessor(std::array<std::size_t,rank()>) iff scalar_t is not
const. */
MFEM_HOST_DEVICE
decltype(auto) operator()(std::array<std::size_t,rank()> is) const
{
if constexpr (std::is_const_v<scalar_t>) { return get_tensor(is); }
else { return get_accessor(is); }
}
/** @brief Returns one of the following depending on the type scalar_t:
- get_tensor(index_types...) iff scalar_t is const,
- get_accessor(index_types...) iff scalar_t is not const. */
template <typename... index_types> MFEM_HOST_DEVICE
decltype(auto) operator()(index_types... is) const
{
if constexpr (std::is_const_v<scalar_t>) { return get_tensor(is...); }
else { return get_accessor(is...); }
}
/** @brief Helper class facilitating the reading/writing of local tensor
objects to the global data array of the tensor_ndarray. */
class tensor_accessor
{
private:
const tensor_ndarray &base_array;
scalar_t *offset_data; /// Not owned
public:
/** @brief Construct a tensor_accessor to @a base for the given dynamic
multi-index @a is.
During its life time, this object assumes that the @a base object
remains unmodified. */
MFEM_HOST_DEVICE
tensor_accessor(const tensor_ndarray &base,
const std::array<std::size_t,rank()> &is)
: base_array(base)
{
offset_data = base_array.data + base_array.get_dynamic_offset(is);
}
/// Read-write access to a particular entry of the referenced tensor.
/** The returned reference points to the corresponding entry in the global
data array of the base tensor_ndarray. */
MFEM_HOST_DEVICE
scalar_t &operator()(const std::array<std::size_t,tensor_rank()> &js)
{
return offset_data[base_array.get_static_offset(js)];
}
/** @brief Write a tensor to the referenced tensor in the global data
array of the base tensor_ndarray. */
MFEM_HOST_DEVICE
tensor_accessor &operator=(const tensor_type &rhs)
{
for_multiindex<tensor_sizes...>(
[&](const std::array<std::size_t,tensor_rank()> &js)
{
operator()(js) = ::mfem::future::apply(rhs, js);
});
return *this;
}
/** @brief For 0D (scalar) tensor arrays, allow direct binding as a
scalar reference so that @c array(i) can be passed to functions
expecting a @c scalar_t& in/out parameter. */
template <bool Enable = (sizeof...(tensor_sizes) == 0),
std::enable_if_t<Enable, int> = 0>
MFEM_HOST_DEVICE
operator scalar_t &()
{
return *offset_data;
}
};
/** @brief Get a tensor_accessor object referencing the tensor stored at the
dynamic multi-index @a is. This object can be used to write tensor
objects into the global data array of the tensor_ndarray. */
MFEM_HOST_DEVICE
tensor_accessor get_accessor(std::array<std::size_t,rank()> is) const
{
return tensor_accessor(*this, is);
}
/** @brief Get a tensor_accessor object referencing the tensor stored at the
dynamic indices @a is. This object can be used to write tensor objects
into the global data array of the tensor_ndarray. */
template <typename... index_types> MFEM_HOST_DEVICE
tensor_accessor get_accessor(index_types... is) const
{
static_assert(sizeof...(is) == rank(), "invalid number of indices!");
return get_accessor(std::array<std::size_t,rank()> {std::size_t(is)...});
}
};
/** @brief Construct a tensor_ndarray where only the tensor sizes have to be
explicitly given as template parameters, the rest can be deduced from the
function call arguments. */
template <int... tensor_sizes, typename scalar_t, typename... dyn_sizes_t>
decltype(auto) make_tensor_ndarray(scalar_t *ptr, dyn_sizes_t... dynamic_sizes)
{
return tensor_ndarray<scalar_t,sizeof...(dynamic_sizes),tensor_sizes...>(
ptr, {std::size_t(dynamic_sizes)...});
}
/// Alias for make_tensor_ndarray = make_tensor_array.
template <int... tensor_sizes, typename scalar_t, typename... dyn_sizes_t>
decltype(auto) make_tensor_array(scalar_t *ptr, dyn_sizes_t... dynamic_sizes)
{
return tensor_ndarray<scalar_t,sizeof...(dynamic_sizes),tensor_sizes...>(
ptr, {std::size_t(dynamic_sizes)...});
}
/// Short name for one-dimensional tensor_ndarray: tensor_array.
template <typename scalar_t, int... tensor_sizes>
using tensor_array = tensor_ndarray<scalar_t, 1, tensor_sizes...>;
} // namespace mfem::future
#endif // MFEM_TENSOR_ARRAYS_HPP
+2 -1
View File
@@ -451,7 +451,8 @@ DIRS = general linalg linalg/batched linalg/simd mesh mesh/submesh fem \
fem/ceed/integrators/diffusion fem/ceed/integrators/nlconvection \
fem/ceed/interface fem/ceed/solvers fem/eltrans fem/fe fem/gslib \
fem/integ fem/lor fem/moonolith fem/qinterp fem/tmop fem/dfem \
fem/tmop/assemble fem/tmop/metrics fem/tmop/mult fem/tmop/tools
fem/dfem/backends fem/dfem/backends/local_qf fem/dfem/backends/global_qf\
fem/tmop/assemble fem/tmop/metrics fem/tmop/mult fem/tmop/tools
ifeq ($(MFEM_USE_MOONOLITH),YES)
MFEM_CXXFLAGS += $(MOONOLITH_CXX_FLAGS)
+1 -1
View File
@@ -318,7 +318,7 @@ protected:
void LoadSharedEntities(std::istream &input);
/// If the mesh is curved, make sure 'Nodes' is ParGridFunction.
/** Note that this method is not related to the public 'Mesh::EnsureNodes`.*/
/** Note that this method is not related to the public 'Mesh::EnsureNodes'.*/
void EnsureParNodes();
/// Internal function used in ParMesh::MakeRefined (and related constructor)
+50 -52
View File
@@ -23,10 +23,8 @@
// mpirun -np 4 dfem-minimal-surface -der 2
//
// Device sample runs:
// mpirun -np 4 dfem-minimal-surface -der 0 -r 1 -o 2 -d cuda
// mpirun -np 4 dfem-minimal-surface -der 1 -r 1 -o 2 -d cuda
// * mpirun -np 4 dfem-minimal-surface -der 0 -r 1 -o 2 -d hip
// * mpirun -np 4 dfem-minimal-surface -der 1 -r 1 -o 2 -d hip
// mpirun -np 4 dfem-minimal-surface -der 0 -r 1 -o 2 -d gpu
// mpirun -np 4 dfem-minimal-surface -der 1 -r 1 -o 2 -d gpu
//
// Description: This example code demonstrates the use of MFEM to solve the
// minimal surface problem in 2D:
@@ -48,6 +46,8 @@
// visualization.
#include "mfem.hpp"
#include "../../fem/dfem/doperator.hpp"
#include "../../fem/dfem/backends/local_qf/prelude.hpp"
using namespace mfem;
@@ -116,11 +116,12 @@ public:
auto operator()(
const tensor<dscalar_t, dim> &dudxi,
const tensor<real_t, dim, dim> &J,
const real_t &w) const
const real_t &w,
tensor<dscalar_t, dim> &dvdx) const
{
const auto invJ = inv(J);
const auto dudx = dudxi * invJ;
return tuple{coeff(dudx) * dudx * transpose(invJ) * det(J) * w};
dvdx = coeff(dudx) * dudx * transpose(invJ) * det(J) * w;
}
};
@@ -135,7 +136,8 @@ public:
const tensor<real_t, dim> &ddelta_udxi,
const tensor<real_t, dim> &dudxi,
const tensor<real_t, dim, dim> &J,
const real_t &w) const
const real_t &w,
tensor<real_t, dim> &dvdx) const
{
const auto invJ = inv(J);
const auto dudx = dudxi * invJ;
@@ -145,7 +147,7 @@ public:
const auto term1 = c * ddelta_udx;
const auto term2 = c * c * c * dot(dudx, ddelta_udx) * dudx;
return tuple{(term1 - term2) * transpose(invJ) * det(J) * w};
dvdx = (term1 - term2) * transpose(invJ) * det(J) * w;
}
};
@@ -162,14 +164,9 @@ public:
z(minsurface->Height())
{
minsurface->u.SetFromTrueDofs(x);
auto mesh_nodes = static_cast<ParGridFunction*>
(minsurface->H1.GetParMesh()->GetNodes());
// One can retrieve the derivative of a DifferentiableOperator wrt a
// field variable if the derivative has been requested during the
// DifferentiableOperator::AddDomainIntegrator call.
dres_du = minsurface->res->GetDerivative(
SOLUTION_U, {&minsurface->u}, {mesh_nodes});
MultiVector X{x, minsurface->mesh_nodes_tdofs};
dres_du = minsurface->res->GetDerivative(SOLUTION_U, X);
}
void Mult(const Vector &x, Vector &y) const override
@@ -177,7 +174,8 @@ public:
z = x;
z.SetSubVector(minsurface->ess_tdofs, 0.0);
dres_du->Mult(z, y);
MultiVector Y{y};
dres_du->Mult(z, Y);
auto d_y = y.ReadWrite();
const auto d_x = x.Read();
@@ -216,22 +214,20 @@ public:
Array<int> all_domain_attr(minsurface->H1.GetMesh()->attributes.Max());
all_domain_attr = 1;
auto &mesh_nodes = *static_cast<ParGridFunction *>
(minsurface->H1.GetParMesh()->GetNodes());
auto &mesh_nodes_fes = *mesh_nodes.ParFESpace();
std::vector<FieldDescriptor> solutions =
{
{DIRECTION_U, &minsurface->H1}
};
std::vector<FieldDescriptor> parameters =
std::vector<FieldDescriptor> inputs =
{
{DIRECTION_U, &minsurface->H1},
{SOLUTION_U, &minsurface->H1},
{MESH_NODES, &mesh_nodes_fes}
{MESH_NODES, minsurface->mesh_nodes_fes}
};
std::vector<FieldDescriptor> outputs =
{
{SOLUTION_U, &minsurface->H1}
};
dres_du = std::make_shared<DifferentiableOperator>(
solutions, parameters, *minsurface->H1.GetParMesh());
inputs, outputs, *minsurface->H1.GetParMesh());
auto input_operators = tuple
{
@@ -247,12 +243,13 @@ public:
};
ManualDerivativeApply manual_derivative_apply;
dres_du->AddDomainIntegrator(manual_derivative_apply, input_operators,
output_operators, minsurface->ir,
all_domain_attr);
dres_du->AddDomainIntegrator<LocalQFBackend>(manual_derivative_apply,
input_operators,
output_operators, minsurface->ir,
all_domain_attr);
minsurface->u.SetFromTrueDofs(x);
dres_du->SetParameters({&minsurface->u, &mesh_nodes});
x0.SetSize(x.Size());
x0 = x;
}
void Mult(const Vector &x, Vector &y) const override
@@ -260,7 +257,9 @@ public:
z = x;
z.SetSubVector(minsurface->ess_tdofs, 0.0);
dres_du->Mult(z, y);
MultiVector X{z, x0, minsurface->mesh_nodes_tdofs};
MultiVector Y{y};
dres_du->Mult(X, Y);
auto d_y = y.HostReadWrite();
const auto d_x = x.HostRead();
@@ -272,10 +271,10 @@ public:
const MinimalSurface *minsurface = nullptr;
std::shared_ptr<DifferentiableOperator> dres_du;
Vector x0;
mutable Vector z;
};
public:
MinimalSurface(ParFiniteElementSpace &H1,
const IntegrationRule &ir,
@@ -291,7 +290,8 @@ public:
auto &mesh_nodes =
*static_cast<ParGridFunction *>(H1.GetParMesh()->GetNodes());
auto &mesh_nodes_fes = *mesh_nodes.ParFESpace();
mesh_nodes_fes = mesh_nodes.ParFESpace();
mesh_nodes.GetTrueDofs(mesh_nodes_tdofs);
// The following section is the heart of this example. It shows how to
// create and interact with the DifferentialOperator class.
@@ -299,14 +299,16 @@ public:
// The constructor of DifferentiableOperator takes two vectors of
// FieldDescriptors. A FieldDescriptor can be viewed as a a pair of an
// identifier (the field ID) and it's accompanying space.
std::vector<FieldDescriptor> solutions;
solutions.push_back(FieldDescriptor(SOLUTION_U, &H1));
std::vector<FieldDescriptor> parameters;
parameters.push_back(FieldDescriptor(MESH_NODES, &mesh_nodes_fes));
std::vector<FieldDescriptor> inputs;
inputs.emplace_back(SOLUTION_U, &H1);
inputs.emplace_back(MESH_NODES, mesh_nodes_fes);
std::vector<FieldDescriptor> outputs;
outputs.emplace_back(SOLUTION_U, &H1);
// Create the DifferentiableOperator on the desired mesh.
res = std::make_shared<DifferentiableOperator>(
solutions, parameters, *H1.GetParMesh());
inputs, outputs, *H1.GetParMesh());
// DifferentiableOperator::AddIntegrator consists mainly of multiple
// components. The input and output operators and the pointwise
@@ -353,16 +355,9 @@ public:
// formed integrator should be formed. This is necessary to specify at
// compile time in order to instantiate the correct functions.
auto derivatives = std::integer_sequence<size_t, SOLUTION_U> {};
res->AddDomainIntegrator(mf_apply_qf, input_operators, output_operators,
ir, all_domain_attr, derivatives);
// Before we are able to use DifferentiableOperator::Mult, we need to call
// DifferentiableOperator::SetParameters to set the parameters of the
// operator. Here, only the mesh node function is required. We do this
// here once, because we know that the nodes won't change. If they do,
// we'd have to call SetParameters before each call to Mult. This is done
// to be mathematically consistent with fixing paramaters.
res->SetParameters({&mesh_nodes});
res->AddDomainIntegrator<LocalQFBackend>(
mf_apply_qf, input_operators, output_operators,
ir, all_domain_attr, derivatives);
Array<int> ess_bdr(H1.GetParMesh()->bdr_attributes.Max());
ess_bdr = 1;
@@ -371,7 +366,9 @@ public:
void Mult(const Vector &x, Vector &y) const override
{
res->Mult(x, y);
MultiVector X{x, mesh_nodes_tdofs};
MultiVector Y{y};
res->Mult(X, Y);
y.SetSubVector(ess_tdofs, 0.0);
}
@@ -408,10 +405,11 @@ public:
}
private:
ParFiniteElementSpace &H1;
ParFiniteElementSpace &H1, *mesh_nodes_fes = nullptr;
const IntegrationRule &ir;
mutable ParGridFunction u;
Vector mesh_nodes_tdofs;
Array<int> ess_tdofs;
@@ -80,6 +80,8 @@ public:
// limitations
void MultRT_2D(const Vector &x, Vector &y, Mode mode) const;
void MultRT_3D(const Vector &x, Vector &y, Mode mode) const;
// suppress warning about hiding overloaded virtual function:
using Operator::Mult;
};
} // namespace mfem
+9 -2
View File
@@ -12,8 +12,9 @@
# Skip dFEM qfunction with floats
if(MFEM_USE_MPI AND MFEM_USE_DOUBLE)
list(APPEND PAR_MTOP_SOURCES mtop_solvers.cpp)
list(APPEND PAR_MTOP_HEADERS mtop_solvers.hpp)
list(APPEND PAR_MTOP_SOURCES mtop_solvers.cpp tmop_ad_err.cpp)
list(APPEND PAR_MTOP_HEADERS mtop_solvers.hpp tmop_ad_err.hpp)
convert_filenames_to_full_paths(PAR_MTOP_SOURCES)
convert_filenames_to_full_paths(PAR_MTOP_HEADERS)
@@ -27,4 +28,10 @@ if(MFEM_USE_MPI AND MFEM_USE_DOUBLE)
${PAR_MTOP_COMMON_FILES}
LIBRARIES mfem)
add_mfem_miniapp(mtop_Rref_TO
MAIN mtop_Rref_TO.cpp
${PAR_MTOP_COMMON_FILES}
LIBRARIES mfem)
endif (MFEM_USE_MPI AND MFEM_USE_DOUBLE)
File diff suppressed because it is too large Load Diff
+46 -28
View File
@@ -35,12 +35,13 @@ template <int DIM> struct QFunction
MFEM_HOST_DEVICE inline auto operator()(const matd_t &dudxi,
const real_t &L, const real_t &M,
const matd_t &J,
const real_t &w) const
const real_t &w,
matd_t &rtn) const
{
const matd_t JxW = transpose(inv(J)) * det(J) * w;
constexpr auto I = mfem::future::IsotropicIdentity<DIM>();
const auto eps = mfem::future::sym(dudxi * mfem::future::inv(J));
return tuple{(L * tr(eps) * I + 2.0 * M * eps) * JxW};
rtn = (L * tr(eps) * I + 2.0 * M * eps) * JxW;
}
};
};
@@ -78,12 +79,12 @@ IsoLinElasticSolver::IsoLinElasticSolver(ParMesh *mesh, int vorder,
ir(IntRules.Get(fe->GetGeomType(),
fe->GetOrder() + fe->GetOrder() + fe->GetDim() - 1)),
qs(*pmesh, ir),
Lambda_ps(*pmesh, ir, 1),
Mu_ps(*pmesh, ir, 1),
Lambda_qs(qs, 1),
Mu_qs(qs, 1),
lf(nullptr)
{
MFEM_VERIFY(qs.GetSize() == Lambda_ps.GetTrueVSize(),
"QuadratureSpace and ParameterSpace size mismatch");
MFEM_VERIFY(qs.GetSize() == Lambda_qs.GetVSize(),
"QuadratureSpace and VectorQuadratureSpace size mismatch");
sol = 0.0;
rhs = 0.0;
@@ -120,13 +121,13 @@ IsoLinElasticSolver::~IsoLinElasticSolver()
delete lvforce;
for (auto it = load_coeff.begin(); it != load_coeff.end(); it++)
{
delete it->second;
}
// for (auto it = load_coeff.begin(); it != load_coeff.end(); it++)
// {
// delete it->second;
// }
delete lambda;
delete mu;
// delete lambda;
// delete mu;
}
void IsoLinElasticSolver::SetLinearSolver(real_t rtol,
@@ -374,12 +375,16 @@ void IsoLinElasticSolver::Assemble()
#ifdef MFEM_USE_DOUBLE
// define the differentiable operator
dop = std::make_unique<mfem::future::DifferentiableOperator>(
std::vector<mfem::future::FieldDescriptor> {{ U, vfes }},
std::vector<mfem::future::FieldDescriptor>
{
{ U, vfes },
{ LCoeff, &Lambda_qs},
{ MuCoeff, &Mu_qs},
{ Coords, mfes }
},
std::vector<mfem::future::FieldDescriptor>
{
{ LCoeff, &Lambda_ps},
{ MuCoeff, &Mu_ps},
{ Coords, mfes }
{ U, vfes }
},
*pmesh);
@@ -389,25 +394,23 @@ void IsoLinElasticSolver::Assemble()
// sample mu on the integration points
Mu_cv = std::make_unique<CoefficientVector>(*mu, qs);
// set the parameters of the differentiable operator
dop->SetParameters({ Lambda_cv.get(), Mu_cv.get(), nodes });
// define the q-function for dimensions 2 and 3
const auto inputs =
mfem::future::tuple{ Gradient<U>{},
Identity<LCoeff>{}, Identity<MuCoeff>{},
Gradient<Coords>{},
Weight{} };
const auto output = mfem::future::tuple{ Gradient<U>{} };
auto inputs =
mfem::future::Inputs< Gradient<U>,
Identity<LCoeff>, Identity<MuCoeff>,
Gradient<Coords>,
Weight> {};
auto output = mfem::future::Outputs< Gradient<U>> {};
using Backend = mfem::future::LocalQFBackend;
if (2 == spaceDim)
{
typename QFunction<2>::Elasticity e2qf;
dop->AddDomainIntegrator(e2qf, inputs, output, ir, domain_attributes);
dop->AddDomainIntegrator<Backend>(e2qf, inputs, output, ir, domain_attributes);
}
else if (3 == spaceDim)
{
typename QFunction<3>::Elasticity e3qf;
dop->AddDomainIntegrator(e3qf, inputs, output, ir, domain_attributes);
dop->AddDomainIntegrator<Backend>(e3qf, inputs, output, ir, domain_attributes);
}
else { MFEM_ABORT("Space dimension not supported"); }
#else
@@ -500,12 +503,16 @@ void IsoLinElasticSolver::Assemble()
else
{
prec = new HypreBoomerAMG();
//precILU->SetLevelOfFill (5);
//precILU->SetOperator(*K);
// set the rigid body modes
prec->SetElasticityOptions(vfes);
prec->SetPrintLevel(0);
ls->SetPreconditioner(*prec);
}
ls->SetOperator(((pa||dfem) ? *Kh->Ptr() : *K));
ls->SetPrintLevel(1);
ls->SetPrintLevel(0);
}
else
{
@@ -547,3 +554,14 @@ void IsoLinElasticSolver::FSolve()
delete lf;
lf = nullptr;
}
void IsoLinElasticSolver::ASolve( mfem::Vector dQdu )
{
if (pa || dfem) { Kc->EliminateRHS(adj, dQdu); }
else
{
K->EliminateBC(*Ke, ess_tdofv, adj, dQdu);
}
ls->Mult(dQdu, adj);
}
+20 -1
View File
@@ -14,6 +14,9 @@
#include "mfem.hpp"
#include "../../fem/dfem/doperator.hpp"
#include "../../fem/dfem/parameterspace.hpp"
using real_t = mfem::real_t;
///////////////////////////////////////////////////////////////////////////////
@@ -97,6 +100,10 @@ public:
/// Solves the forward problem.
void FSolve();
/// Solves the adjoint problem.
void ASolve( mfem::Vector dQdu );
/// Adds displacement BC in direction 0(x), 1(y), 2(z), or -1(all).
void AddDispBC(int id, int dir, real_t val);
@@ -191,6 +198,13 @@ public:
mu = new IsoElasticySchearCoeff(E, nu);
}
void SetMaterialLame(mfem::Coefficient &lambda_, mfem::Coefficient &mu_)
{
lambda = &lambda_;
mu = &mu_;
}
class NqptUniformParameterSpace : public
mfem::future::UniformParameterSpace
{
@@ -202,6 +216,10 @@ public:
{
dtq.nqpt = ir.GetNPoints();
}
const Operator* GetB() const override { return nullptr; }
const Operator* GetBt() const override { return nullptr; }
};
// creates a list with essential dofs
@@ -240,6 +258,7 @@ private:
int linear_iter;
mfem::HypreBoomerAMG *prec; // preconditioner
mfem::HypreILU *precILU; // preconditioner
mfem::CGSolver *ls; // linear solver
// PA LOR preconditioner
@@ -298,7 +317,7 @@ private:
mfem::Array<int> domain_attributes;
const mfem::IntegrationRule &ir;
mfem::QuadratureSpace qs;
NqptUniformParameterSpace Lambda_ps, Mu_ps;
mfem::VectorQuadratureSpace Lambda_qs, Mu_qs;
std::unique_ptr<mfem::CoefficientVector> Lambda_cv, Mu_cv;
std::unique_ptr<mfem::future::DifferentiableOperator> dop;
// end of dFEM definitions
File diff suppressed because it is too large Load Diff
+954
View File
@@ -0,0 +1,954 @@
#ifndef TMOP_AD_ERR_HPP
#define TMOP_AD_ERR_HPP
#include "mfem.hpp"
namespace mfem{
void IdentityMatrix(int dim, DenseMatrix &I);
void Vectorize(const DenseMatrix &A, Vector &a);
double MatrixInnerProduct(const DenseMatrix &A, const DenseMatrix &B);
void ConjugationProduct(const DenseMatrix &A, const DenseMatrix &B, const DenseMatrix &C, DenseMatrix &D);
void KroneckerProduct(const DenseMatrix &A, const DenseMatrix &B, DenseMatrix &C);
void IsotropicStiffnessMatrix(int dim, double mu, double lambda, DenseMatrix &C);
void IsotropicStiffnessMatrix3D(double E, double v, DenseMatrix &C);
void FourthOrderSymmetrizer(int dim, DenseMatrix &S);
void FourthOrderIdentity(int dim, DenseMatrix &I4);
void FourthOrderTranspose(int dim, DenseMatrix &T);
void VectorOuterProduct(const Vector &a, const Vector &b, DenseMatrix &C);
void UnitStrain(int dim, int i, int j, DenseMatrix &E);
void UnitStrain(int dim, int i, int j, Vector &E);
void MatrixConjugationProduct(const DenseMatrix &A, const DenseMatrix &B, DenseMatrix &C);
class NodeAwareTMOPQuality
{
public:
NodeAwareTMOPQuality(mfem::ParMesh* mesh_, int order_, TMOP_QualityMetric *metric, TargetConstructor *target_c)
{
pmesh=mesh_;
int dim=pmesh->Dimension();
fec = new H1_FECollection(order_,dim);
coord_fes_ = new ParFiniteElementSpace(pmesh,fec,dim);
X0_.SetSpace(coord_fes_);
designVar.SetSpace(coord_fes_);
mfem::Vector tempX0_;
pmesh->GetNodes(tempX0_);
X0_ = tempX0_;
dQdx_ = new mfem::ParLinearForm(coord_fes_);
metric_in = metric;
target_in = target_c;
}
~NodeAwareTMOPQuality()
{
}
void UpdateMesh(mfem::Vector const &U);
double EvalQoI();
void EvalQoIGrad();
mfem::ParLinearForm * GetDQDx(){ return dQdx_; };
void SetDesign( mfem::ParGridFunction & design){ designVar = design; };
private:
mfem::ParMesh* pmesh;
mfem::ParGridFunction X0_;
mfem::ParGridFunction designVar;
mfem::FiniteElementCollection *fec;
mfem::ParFiniteElementSpace *coord_fes_;
mfem::ParLinearForm * dQdx_;
TMOP_QualityMetric *metric_in = nullptr;
TargetConstructor *target_in = nullptr;
};
enum QoIType
{
L2_ERROR,
H1S_ERROR,
ZZ_ERROR,
AVG_ERROR,
ENERGY,
GZZ_ERROR,
H1_ERROR,
STRUC_COMPLIANCE
};
class QoIBaseCoefficient : public Coefficient {
public:
QoIBaseCoefficient() {};
virtual ~QoIBaseCoefficient() {};
virtual const DenseMatrix &explicitSolutionDerivative
(ElementTransformation &T, const IntegrationPoint &ip) = 0;
virtual const DenseMatrix &explicitSolutionGradientDerivative(ElementTransformation &T,
const IntegrationPoint &ip)
= 0;
virtual const DenseMatrix &gradTimesexplicitSolutionGradientDerivative(ElementTransformation &T,
const IntegrationPoint &ip)
= 0;
virtual const DenseMatrix &explicitShapeDerivative(ElementTransformation &T, const IntegrationPoint &ip) = 0;
virtual const Vector DerivativeExactWRTX(ElementTransformation &T, const IntegrationPoint &ip) {
Vector vec(T.GetSpaceDim());
vec = 0.0;
return vec;
}
private:
};
class Energy_QoI : public QoIBaseCoefficient {
public:
Energy_QoI(mfem::ParGridFunction * solutionField, mfem::Coefficient * force, VectorCoefficient * forceGrad, int Dim)
: solutionField_(solutionField), force_(force), forceGrad_(forceGrad), Dim_(Dim)
{};
~Energy_QoI() {};
double Eval( mfem::ElementTransformation &T, const mfem::IntegrationPoint &ip) override
{
double fieldVal = solutionField_->GetValue( T, ip );
double Val = force_->Eval( T, ip );
double energy = fieldVal*Val;
return energy;
};
const mfem::DenseMatrix &explicitSolutionDerivative( mfem::ElementTransformation & T, const mfem::IntegrationPoint & ip) override
{
dtheta_dU.SetSize(1);
double Val = force_->Eval( T, ip );
double & matVal = dtheta_dU.Elem(0,0);
matVal = Val;
return dtheta_dU;
};
const mfem::DenseMatrix &explicitSolutionGradientDerivative( mfem::ElementTransformation &T,
const mfem::IntegrationPoint &ip) override
{
dtheta_dGradU.SetSize(1, Dim_);
dtheta_dGradU = 0.0;
return dtheta_dGradU;
};
const mfem::DenseMatrix &explicitShapeDerivative( mfem::ElementTransformation &T, const mfem::IntegrationPoint &ip) override
{
dtheta_dX.SetSize(1, Dim_);
dtheta_dX = 0.0;
return dtheta_dX;
};
virtual const mfem::DenseMatrix &gradTimesexplicitSolutionGradientDerivative( mfem::ElementTransformation &T,
const mfem::IntegrationPoint &ip) override
{
dtheta_dX.SetSize(Dim_, Dim_);
dtheta_dX = 0.0;
return dtheta_dX;
};
const Vector DerivativeExactWRTX(ElementTransformation &T, const IntegrationPoint &ip) override
{
Vector trueGrad;
forceGrad_->Eval(trueGrad, T, ip);
double fieldVal = solutionField_->GetValue( T, ip );
trueGrad *= fieldVal;
return trueGrad;
}
private:
mfem::ParGridFunction * solutionField_;
mfem::Coefficient * force_;
VectorCoefficient * forceGrad_ = nullptr;
int Dim_;
double theta = 0.0;
mfem::DenseMatrix dtheta_dX;
mfem::DenseMatrix dtheta_dU;
mfem::DenseMatrix dtheta_dGradU;
};
class LFNodeCoordinateSensitivityIntegrator : public LinearFormIntegrator {
public:
LFNodeCoordinateSensitivityIntegrator( int IntegrationOrder = INT_MAX);
~LFNodeCoordinateSensitivityIntegrator() {};
void AssembleRHSElementVect(const FiniteElement &el, ElementTransformation &T, Vector &elvect);
void SetQoI(std::shared_ptr<QoIBaseCoefficient> QoI) { QoI_ = QoI; };
void SetGLLVec(Array<double> &gllvec) { gllvec_ = gllvec;}
void SetNqptsPerEl(int nqp) { nqptsperel = nqp; }
private:
std::shared_ptr<QoIBaseCoefficient> QoIFactoryFunction(const int dim);
const int IntegrationOrder_;
std::shared_ptr<QoIBaseCoefficient> QoI_ = nullptr;
Array<double> gllvec_;
int nqptsperel;
};
class LFAvgErrorNodeCoordinateSensitivityIntegrator : public LinearFormIntegrator {
public:
LFAvgErrorNodeCoordinateSensitivityIntegrator(
ParGridFunction * solutionField, GridFunctionCoefficient * elementVol,
int IntegrationOrder = INT_MAX);
~LFAvgErrorNodeCoordinateSensitivityIntegrator() {};
void AssembleRHSElementVect(const FiniteElement &el, ElementTransformation &T, Vector &elvect);
void SetQoI(std::shared_ptr<QoIBaseCoefficient> QoI) { QoI_ = QoI; };
private:
std::shared_ptr<QoIBaseCoefficient> QoIFactoryFunction(const int dim);
ParGridFunction * solutionField_ = nullptr;
GridFunctionCoefficient * elementVol_ = nullptr;
const int IntegrationOrder_;
std::shared_ptr<QoIBaseCoefficient> QoI_ = nullptr;
};
class LFErrorIntegrator : public LinearFormIntegrator {
public:
LFErrorIntegrator( int IntegrationOrder = INT_MAX);
~LFErrorIntegrator() {};
void AssembleRHSElementVect(const FiniteElement &el, ElementTransformation &T, Vector &elvect);
void SetQoI(std::shared_ptr<QoIBaseCoefficient> QoI) { QoI_ = QoI; };
void SetGLLVec(Array<double> &gllvec) { gllvec_ = gllvec;}
void SetNqptsPerEl(int nqp) { nqptsperel = nqp; }
private:
std::shared_ptr<QoIBaseCoefficient> QoIFactoryFunction(const int dim);
const int IntegrationOrder_;
std::shared_ptr<QoIBaseCoefficient> QoI_ = nullptr;
Array<double> gllvec_;
int nqptsperel;
};
class LFErrorDerivativeIntegrator : public LinearFormIntegrator {
public:
LFErrorDerivativeIntegrator( );
~LFErrorDerivativeIntegrator() {};
void AssembleRHSElementVect(const FiniteElement &el, ElementTransformation &T, Vector &elvect);
void SetQoI(std::shared_ptr<QoIBaseCoefficient> QoI) { QoI_ = QoI; };
private:
std::shared_ptr<QoIBaseCoefficient> QoIFactoryFunction(const int dim);
std::shared_ptr<QoIBaseCoefficient> QoI_ = nullptr;
};
class LFErrorDerivativeIntegrator_2 : public LinearFormIntegrator {
public:
LFErrorDerivativeIntegrator_2( ParFiniteElementSpace * fespace, Array<int> count, int IntegrationOrder = INT_MAX);
~LFErrorDerivativeIntegrator_2() {};
void AssembleRHSElementVect(const FiniteElement &el, ElementTransformation &T, Vector &elvect);
void SetQoI(std::shared_ptr<QoIBaseCoefficient> QoI) { QoI_ = QoI; };
private:
std::shared_ptr<QoIBaseCoefficient> QoIFactoryFunction(const int dim);
ParFiniteElementSpace * fespace_ = nullptr;
Array<int> count_;
const int IntegrationOrder_;
std::shared_ptr<QoIBaseCoefficient> QoI_ = nullptr;
};
class LFFilteredFieldErrorDerivativeIntegrator : public LinearFormIntegrator {
public:
LFFilteredFieldErrorDerivativeIntegrator( );
~LFFilteredFieldErrorDerivativeIntegrator() {};
void AssembleRHSElementVect(const FiniteElement &el, ElementTransformation &T, Vector &elvect);
void SetQoI(std::shared_ptr<QoIBaseCoefficient> QoI) { QoI_ = QoI; };
private:
std::shared_ptr<QoIBaseCoefficient> QoIFactoryFunction(const int dim);
std::shared_ptr<QoIBaseCoefficient> QoI_ = nullptr;
};
class LFAverageErrorDerivativeIntegrator : public LinearFormIntegrator {
public:
LFAverageErrorDerivativeIntegrator( ParFiniteElementSpace * fespace, GridFunctionCoefficient * elementVol, int IntegrationOrder = INT_MAX);
~LFAverageErrorDerivativeIntegrator() {};
void AssembleRHSElementVect(const FiniteElement &el, ElementTransformation &T, Vector &elvect);
void SetQoI(std::shared_ptr<QoIBaseCoefficient> QoI) { QoI_ = QoI; };
private:
std::shared_ptr<QoIBaseCoefficient> QoIFactoryFunction(const int dim);
ParFiniteElementSpace * fespace_ = nullptr;
Array<int> count_;
const int IntegrationOrder_;
GridFunctionCoefficient * elementVol_ = nullptr;
std::shared_ptr<QoIBaseCoefficient> QoI_ = nullptr;
};
class PenaltyMassShapeSensitivityIntegrator : public LinearFormIntegrator {
public:
PenaltyMassShapeSensitivityIntegrator(Coefficient &penalty, const ParGridFunction &t_primal,
const ParGridFunction &t_adjoint);
void AssembleRHSElementVect(const FiniteElement &el, ElementTransformation &T, Vector &elvect);
private:
Coefficient *penalty_;
const ParGridFunction *t_primal_;
const ParGridFunction *t_adjoint_;
};
class PenaltyShapeSensitivityIntegrator : public LinearFormIntegrator {
public:
PenaltyShapeSensitivityIntegrator(Coefficient &t_primal, const ParGridFunction &t_adjoint, Coefficient &t_penalty, VectorCoefficient *SolGrad_= nullptr, int oa = 2, int ob = 2);
void AssembleRHSElementVect(const FiniteElement &el, ElementTransformation &T, Vector &elvect);
private:
Coefficient *t_primal_ = nullptr;
Coefficient *t_penalty_ = nullptr;
VectorCoefficient *SolGradCoeff_= nullptr;
const ParGridFunction *t_adjoint_;
int oa_, ob_;
};
class GradProjectionShapeSensitivityIntegrator : public LinearFormIntegrator {
public:
GradProjectionShapeSensitivityIntegrator(const ParGridFunction &t_primal, const ParGridFunction &t_adjoin, VectorCoefficient & tempCoeff);
void AssembleRHSElementVect(const FiniteElement &el, ElementTransformation &T, Vector &elvect);
private:
const ParGridFunction *t_primal_;
const ParGridFunction *t_adjoint_;
VectorCoefficient *tempCoeff_;
};
class ElasticityStiffnessShapeSensitivityIntegrator : public LinearFormIntegrator
{
public:
ElasticityStiffnessShapeSensitivityIntegrator(Coefficient &lambda, Coefficient &mu,
const ParGridFunction &u_primal, const ParGridFunction &u_adjoint);
void AssembleRHSElementVect(const FiniteElement &el, ElementTransformation &T, Vector &elvect);
private:
Coefficient *lambda_;
Coefficient *mu_;
const ParGridFunction *u_primal_;
const ParGridFunction *u_adjoint_;
};
class ElasticityTractionIntegrator : public LinearFormIntegrator
{
public:
ElasticityTractionIntegrator(VectorCoefficient &f, int oa=2, int ob=2);
void AssembleRHSElementVect(const FiniteElement &el, ElementTransformation &T, Vector &elvect);
private:
VectorCoefficient *f_;
int oa_, ob_;
};
class ElasticityTractionShapeSensitivityIntegrator : public LinearFormIntegrator
{
public:
ElasticityTractionShapeSensitivityIntegrator(VectorCoefficient &f,
const ParGridFunction &u_adjoint, int oa=2, int ob=2);
void AssembleRHSElementVect(const FiniteElement &el, ElementTransformation &T, Vector &elvect);
private:
VectorCoefficient *f_;
const ParGridFunction *u_adjoint_;
int oa_, ob_;
};
class QuantityOfInterest
{
public:
QuantityOfInterest(ParMesh* mesh_, enum QoIType qoiType, int order_, int physics_order_, Array<int> NeumannBdr = {} ,int pdim = 1)
: pmesh(mesh_), qoiType_(qoiType), bdr(NeumannBdr)
{
int dim=pmesh->Dimension();
pmesh->GetNodes(X0_);
fec = new H1_FECollection(order_,dim);
pfec = new H1_FECollection(physics_order_,dim);
temp_fes_ = new ParFiniteElementSpace(pmesh,pfec,pdim);
coord_fes_ = new ParFiniteElementSpace(pmesh,fec,dim);
temp_fes_grad_ = new ParFiniteElementSpace(pmesh,pfec,dim*pdim);
solgf_.SetSpace(temp_fes_);
dQdu_ = new ParLinearForm(temp_fes_);
dQdx_ = new ParLinearForm(coord_fes_);
}
~QuantityOfInterest()
{
delete temp_fes_;
delete coord_fes_;
delete fec;
delete dQdu_;
delete dQdx_;
}
void setTrueSolCoeff( Coefficient * trueSolution ){ trueSolution_ = trueSolution; };
void setTrueSolGradCoeff( VectorCoefficient * trueSolutionGrad ){ trueSolutionGrad_ = trueSolutionGrad; };
void setTrueSolHessCoeff( MatrixCoefficient * trueSolutionHess ){ trueSolutionHess_ = trueSolutionHess; };
void setTrueSolHessCoeff( VectorCoefficient * trueSolutionHessV ){ trueSolutionHessV_ = trueSolutionHessV; };
void setTractionCoeff( VectorCoefficient * tractionLoad ){ tractionLoad_ = tractionLoad; }
void SetManufacturedSolution( Coefficient * QCoef ){ QCoef_ = QCoef; }
void SetManufacturedSolutionGrad( VectorCoefficient * QCoefGrad ){ QCoefGrad_ = QCoefGrad; }
void SetDesign( Vector & design){ designVar = design; };
void SetNodes( Vector & coords){ X0_ = coords; };
void SetDesignVarFromUpdatedLocations( Vector & design)
{
designVar = design;
designVar -= X0_;
};
void SetDiscreteSol( ParGridFunction & sol){ solgf_ = sol; };
void UpdateMesh(Vector const &U);
double EvalQoI();
void EvalQoIGrad();
ParLinearForm * GetDQDu(){ return dQdu_; };
ParLinearForm * GetDQDx(){ return dQdx_; };
void SetGLLVec(Array<double> &gllvec) { gllvec_ = gllvec;}
void SetNqptsPerEl(int nqp) { nqptsperel = nqp; }
void SetIntegrationRules(IntegrationRules *irule_, int quad_order_) { irules = irule_; quad_order = quad_order_; }
Coefficient * GetTrueSolCoeff() { return trueSolution_; }
VectorCoefficient *GetTrueSolGradCoeff() { return trueSolutionGrad_; }
private:
Coefficient * trueSolution_ = nullptr;
VectorCoefficient * trueSolutionGrad_ = nullptr;
MatrixCoefficient * trueSolutionHess_ = nullptr;
VectorCoefficient * trueSolutionHessV_ = nullptr;
VectorCoefficient * tractionLoad_ = nullptr;
Coefficient * QCoef_ = nullptr;
VectorCoefficient * QCoefGrad_ = nullptr;
ParMesh* pmesh;
enum QoIType qoiType_;
Vector X0_;
Vector designVar;
FiniteElementCollection *fec;
FiniteElementCollection *pfec;
ParFiniteElementSpace *temp_fes_;
ParFiniteElementSpace *coord_fes_;
ParFiniteElementSpace *temp_fes_grad_;
ParLinearForm * dQdu_;
ParLinearForm * dQdx_;
ParGridFunction solgf_;
ParaViewDataCollection *debug_pdc;
int pdc_cycle = 0;
std::shared_ptr<QoIBaseCoefficient> ErrorCoefficient_ = nullptr;
Array<double> gllvec_;
int nqptsperel;
IntegrationRules *irules;
int quad_order;
Array<int> bdr;
};
class PhysicsSolverBase
{
public:
PhysicsSolverBase( ParMesh* mesh_, int order_, int physics_order_)
{
pmesh=mesh_;
int dim=pmesh->Dimension();
pmesh->GetNodes(X0_);
fec = new H1_FECollection(order_,dim);
pfec = new H1_FECollection(physics_order_,dim);
coord_fes_ = new ParFiniteElementSpace(pmesh,fec,dim);
dQdx_ = new ParLinearForm(coord_fes_);
SetLinearSolver();
};
virtual ~PhysicsSolverBase()
{
delete physics_fes_;
delete coord_fes_;
delete fec;
delete dQdu_;
delete dQdx_;
};
void UpdateMesh(Vector const &U);
void SetLinearSolver(double rtol=1e-8, double atol=1e-12, int miter=2000)
{
linear_rtol=rtol;
linear_atol=atol;
linear_iter=miter;
}
virtual void FSolve() = 0;
virtual void ASolve( Vector & rhs ) = 0;
void SetDesign( Vector & design)
{
designVar = design;
};
void SetDesignVarFromUpdatedLocations( Vector & design)
{
designVar = design;
designVar -= X0_;
};
/// Returns the solution
ParGridFunction& GetSolution(){return solgf;}
/// Returns the solution vector.
Vector& GetSol(){return sol;}
/// Returns the adjoint solution vector.
Vector& GetAdj(){return adj;}
ParLinearForm * GetImplicitDqDx(){ return dQdx_; };
protected:
ParMesh* pmesh;
Vector X0_;
Vector designVar;
FiniteElementCollection *fec;
FiniteElementCollection *pfec;
ParFiniteElementSpace *physics_fes_;
ParFiniteElementSpace *coord_fes_;
//solution true vector
Vector sol;
Vector adj;
Vector rhs;
ParGridFunction solgf, projsolgf;
ParGridFunction adjgf;
ParGridFunction bcGridFunc_;
ParLinearForm * dQdu_;
ParLinearForm * dQdx_;
//Linear solver parameters
double linear_rtol;
double linear_atol;
int linear_iter;
int print_level = 1;
};
class Elasticity_Solver : public PhysicsSolverBase
{
public:
Elasticity_Solver(ParMesh* mesh_, std::vector<std::pair<int, double>> ess_bdr, const Array<int> & neumannBdr, int order_)
: PhysicsSolverBase( mesh_, order_ , order_), bdr(neumannBdr)
{
int dim=pmesh->Dimension();
physics_fes_ = new ParFiniteElementSpace(pmesh,fec,dim);
sol.SetSize(physics_fes_->GetTrueVSize()); sol=0.0;
rhs.SetSize(physics_fes_->GetTrueVSize()); rhs=0.0;
adj.SetSize(physics_fes_->GetTrueVSize()); adj=0.0;
solgf.SetSpace(physics_fes_);
adjgf.SetSpace(physics_fes_);
dQdu_ = new ParLinearForm(physics_fes_);
// store list of essential dofs
int maxAttribute = pmesh->bdr_attributes.Max();
Array<int> bdr_attr_is_ess(maxAttribute);
ess_tdof_list_.DeleteAll();
Vector ess_bc(physics_fes_->GetTrueVSize());
ess_bc = 0.0;
// loop over input attribute, value pairs
for (const auto &bc: ess_bdr)
{
int attribute = bc.first;
// get dofs associated with this attribute, component pair
bdr_attr_is_ess = 0;
bdr_attr_is_ess[attribute - 1] = 1; // mfem attributes 1-indexed, arrays 0-indexed
Array<int> u_tdofs;
physics_fes_->GetEssentialTrueDofs(bdr_attr_is_ess, u_tdofs);
// append to global dof list
ess_tdof_list_.Append(u_tdofs);
// set value in grid function
double value = bc.second;
ess_bc.SetSubVector(u_tdofs, value);
}
bcGridFunc_.SetSpace(physics_fes_);
bcGridFunc_.SetFromTrueDofs(ess_bc);
firstLameCoef = new ConstantCoefficient(0.5769230769);
secondLameCoef = new ConstantCoefficient(1.0/2.6);
}
~Elasticity_Solver(){
}
/// Solves the forward problem.
void FSolve() override ;
void ASolve( Vector & rhs ) override ;
void SetLoad( VectorCoefficient * QCoef )
{
QCoef_ = QCoef;
}
void setMaterial( Coefficient * firstLameCoef_, Coefficient * secondLameCoef_)
{
// delete(firstLameCoef);
// delete(secondLameCoef);
firstLameCoef = firstLameCoef_;
secondLameCoef = secondLameCoef_;
}
private:
// holds NBC in coefficient form
std::map<int, Coefficient*> ncc;
Array<int> ess_tdof_list_;
VectorCoefficient * QCoef_ = nullptr;
Array<int> bdr;
Coefficient * firstLameCoef = nullptr;
Coefficient * secondLameCoef = nullptr;
};
class VectorHelmholtz
{
public:
VectorHelmholtz(ParMesh* mesh_, std::vector<std::pair<int, int>> ess_bdr, real_t radius, int order_, int physics_order_)
{
radius_ = new ConstantCoefficient(radius);
pmesh=mesh_;
int dim=pmesh->Dimension();
pmesh->GetNodes(X0_);
fec = new H1_FECollection(order_,dim);
pfec = new H1_FECollection(physics_order_,dim);
temp_fes_ = new ParFiniteElementSpace(pmesh,pfec,dim);
temp_fes_scalar_ = new ParFiniteElementSpace(pmesh,pfec);
coord_fes_ = new ParFiniteElementSpace(pmesh,fec,dim);
// sol.SetSize(coord_fes_->GetTrueVSize()); sol=0.0;
rhs.SetSize(coord_fes_->GetTrueVSize()); rhs=0.0;
// adj.SetSize(coord_fes_->GetTrueVSize()); adj=0.0;
solgf.SetSpace(temp_fes_);
// adjgf.SetSpace(coord_fes_);
dQdx_ = new ParLinearForm(coord_fes_);
dQdu_ = new ParLinearForm(temp_fes_scalar_);
dQdxshape_ = new ParLinearForm(coord_fes_);
SetLinearSolver();
// store list of essential dofs
int maxAttribute = pmesh->bdr_attributes.Max();
Array<int> bdr_attr_is_ess(maxAttribute);
ess_tdof_list_.DeleteAll();
Vector ess_bc(coord_fes_->GetTrueVSize());
ess_bc = 0.0;
// loop over input attribute, value pairs
for (const auto &bc: ess_bdr)
{
int attribute = bc.first;
int component = bc.second;
// get dofs associated with this attribute, component pair
bdr_attr_is_ess = 0;
bdr_attr_is_ess[attribute - 1] = 1; // mfem attributes 1-indexed, arrays 0-indexed
Array<int> u_tdofs;
coord_fes_->GetEssentialTrueDofs(bdr_attr_is_ess, u_tdofs, component);
// append to global dof list
ess_tdof_list_.Append(u_tdofs);
}
}
VectorHelmholtz(ParMesh* mesh_, std::vector<std::pair<int, int>> ess_bdr, ProductCoefficient *radius, int order_, int physics_order_)
{
pradius_ = radius;
pmesh=mesh_;
int dim=pmesh->Dimension();
pmesh->GetNodes(X0_);
fec = new H1_FECollection(order_,dim);
pfec = new H1_FECollection(physics_order_,dim);
temp_fes_ = new ParFiniteElementSpace(pmesh,pfec, dim);
temp_fes_scalar_ = new ParFiniteElementSpace(pmesh,pfec);
coord_fes_ = new ParFiniteElementSpace(pmesh,fec,dim);
// sol.SetSize(coord_fes_->GetTrueVSize()); sol=0.0;
rhs.SetSize(coord_fes_->GetTrueVSize()); rhs=0.0;
// adj.SetSize(coord_fes_->GetTrueVSize()); adj=0.0;
solgf.SetSpace(temp_fes_);
// adjgf.SetSpace(coord_fes_);
dQdx_ = new ParLinearForm(coord_fes_);
dQdu_ = new ParLinearForm(temp_fes_scalar_);
dQdxshape_ = new ParLinearForm(coord_fes_);
SetLinearSolver();
// store list of essential dofs
int maxAttribute = pmesh->bdr_attributes.Max();
Array<int> bdr_attr_is_ess(maxAttribute);
ess_tdof_list_.DeleteAll();
Vector ess_bc(coord_fes_->GetTrueVSize());
ess_bc = 0.0;
// loop over input attribute, value pairs
for (const auto &bc: ess_bdr)
{
int attribute = bc.first;
int component = bc.second;
// get dofs associated with this attribute, component pair
bdr_attr_is_ess = 0;
bdr_attr_is_ess[attribute - 1] = 1; // mfem attributes 1-indexed, arrays 0-indexed
Array<int> u_tdofs;
coord_fes_->GetEssentialTrueDofs(bdr_attr_is_ess, u_tdofs, component);
// append to global dof list
ess_tdof_list_.Append(u_tdofs);
}
}
~VectorHelmholtz(){
delete coord_fes_;
delete temp_fes_;
delete fec;
delete dQdx_;
delete radius_;
delete dQdu_;
delete dQdxshape_;
delete QGF_;
delete QCoef_;
}
/// Set the Linear Solver
void SetLinearSolver(double rtol=1e-8, double atol=1e-12, int miter=2000)
{
linear_rtol=rtol;
linear_atol=atol;
linear_iter=miter;
}
/// Solves the forward problem.
void FSolve( );
void ASolve( Vector & rhs, bool isGradX = true );
void setLoadGridFunction( Vector & loadGF)
{
if(coeffSet) { mfem_error("coeff already set"); }
GFSet = true;
delete QGF_;
delete QCoef_;
QGF_ = new ParGridFunction(coord_fes_);
*QGF_ = loadGF;
// QGF_->SetFromTrueDofs(loadGF);
QCoef_ = new VectorGridFunctionCoefficient(QGF_);
};
void setLoadCoeff(VectorCoefficient * loadCoeff)
{
if(coeffSet) { mfem_error("coeff already set"); }
coeffSet = true;
QCoef_ =loadCoeff; };
/// Returns the solution
ParGridFunction& GetSolution(){return solgf;}
/// Returns the solution vector.
Vector& GetSolutionVec(){return solgf;}
Vector GetSolutionTVec(){
solgf.SetTrueVector();
return solgf.GetTrueVector();}
/// Returns the adjoint solution vector.
// Vector& GetAdj(){return adj;}
ParLinearForm * GetImplicitDqDx(){ return dQdx_; };
Vector GetImplicitDqDxVec(){ return *dQdx_; };
ParLinearForm * GetImplicitDqDxshape(){ return dQdxshape_; };
ParLinearForm * GetImplicitDqDu(){ return dQdu_; };
private:
ParMesh* pmesh;
Vector X0_;
//solution true vector
// Vector sol;
// Vector adj;
Vector rhs;
ParGridFunction solgf;
// ParGridFunction adjgf;
ParGridFunction bcGridFunc_;
ParLinearForm * dQdx_;
ParLinearForm * dQdxshape_;
ParLinearForm * dQdu_;
FiniteElementCollection *fec;
FiniteElementCollection *pfec;
ParFiniteElementSpace *temp_fes_;
ParFiniteElementSpace *coord_fes_;
ParFiniteElementSpace *temp_fes_scalar_;
//Linear solver parameters
double linear_rtol;
double linear_atol;
int linear_iter;
int print_level = 1;
// holds NBC in coefficient form
std::map<int, Coefficient*> ncc;
Array<int> ess_tdof_list_;
ParGridFunction* QGF_ = nullptr;
VectorCoefficient * QCoef_ = nullptr;
Coefficient * radius_;
ProductCoefficient *pradius_ = nullptr;
bool GFSet = false;
bool coeffSet = false;
};
class DiffusionSolver
{
private:
mfem::Mesh * mesh = nullptr;
int order = 1;
// diffusion coefficient
mfem::Coefficient * diffcf = nullptr;
// mass coefficient
mfem::Coefficient * masscf = nullptr;
mfem::Coefficient * rhscf = nullptr;
mfem::Coefficient * essbdr_cf = nullptr;
mfem::Coefficient * neumann_cf = nullptr;
mfem::VectorCoefficient * gradient_cf = nullptr;
// FEM solver
int dim;
mfem::FiniteElementCollection * fec = nullptr;
mfem::FiniteElementSpace * fes = nullptr;
mfem::Array<int> ess_bdr;
mfem::Array<int> neumann_bdr;
mfem::GridFunction * u = nullptr;
mfem::LinearForm * b = nullptr;
bool parallel;
#ifdef MFEM_USE_MPI
mfem::ParMesh * pmesh = nullptr;
mfem::ParFiniteElementSpace * pfes = nullptr;
#endif
public:
DiffusionSolver() { }
DiffusionSolver(mfem::Mesh * mesh_, int order_, mfem::Coefficient * diffcf_,
mfem::Coefficient * cf_);
void SetMesh(mfem::Mesh * mesh_)
{
mesh = mesh_;
parallel = false;
#ifdef MFEM_USE_MPI
pmesh = dynamic_cast<mfem::ParMesh *>(mesh);
if (pmesh) { parallel = true; }
#endif
}
void SetOrder(int order_) { order = order_ ; }
void SetDiffusionCoefficient(mfem::Coefficient * diffcf_) { diffcf = diffcf_; }
void SetMassCoefficient(mfem::Coefficient * masscf_) { masscf = masscf_; }
void SetRHSCoefficient(mfem::Coefficient * rhscf_) { rhscf = rhscf_; }
void SetEssentialBoundary(const mfem::Array<int> & ess_bdr_) { ess_bdr = ess_bdr_;};
void SetNeumannBoundary(const mfem::Array<int> & neumann_bdr_) { neumann_bdr = neumann_bdr_;};
void SetNeumannData(mfem::Coefficient * neumann_cf_) {neumann_cf = neumann_cf_;}
void SetEssBdrData(mfem::Coefficient * essbdr_cf_) {essbdr_cf = essbdr_cf_;}
void SetGradientData(mfem::VectorCoefficient * gradient_cf_) {gradient_cf = gradient_cf_;}
void ResetFEM();
void SetupFEM();
void Solve();
mfem::GridFunction * GetFEMSolution();
mfem::LinearForm * GetLinearForm() {return b;}
#ifdef MFEM_USE_MPI
mfem::ParGridFunction * GetParFEMSolution();
mfem::ParLinearForm * GetParLinearForm()
{
if (parallel)
{
return dynamic_cast<mfem::ParLinearForm *>(b);
}
else
{
MFEM_ABORT("Wrong code path. Call GetLinearForm");
return nullptr;
}
}
#endif
~DiffusionSolver();
};
}
#endif
+28 -9
View File
@@ -17,7 +17,23 @@ include_directories(BEFORE ${PROJECT_SOURCE_DIR})
include_directories(BEFORE ${PROJECT_BINARY_DIR})
# Include the Google Benchmark include directory
include_directories(BEFORE ${BENCHMARK_INCLUDE_DIRS})
if (MFEM_USE_BENCHMARK)
include_directories(BEFORE ${BENCHMARK_INCLUDE_DIRS})
endif(MFEM_USE_BENCHMARK)
#-------------------------------------------------------------------------------
# Simple timer-based benchmark that intentionally does not use Google Benchmark.
#-------------------------------------------------------------------------------
if (MFEM_USE_MPI)
set(DFEM_LINEARIZED_SIMPLE_BENCH_SRCS bench_dfem_linearized_simple.cpp)
if (MFEM_USE_CUDA)
set_property(SOURCE ${DFEM_LINEARIZED_SIMPLE_BENCH_SRCS} PROPERTY LANGUAGE CUDA)
endif(MFEM_USE_CUDA)
mfem_add_executable(bench_dfem_linearized_simple ${DFEM_LINEARIZED_SIMPLE_BENCH_SRCS})
target_link_libraries(bench_dfem_linearized_simple PRIVATE mfem)
add_dependencies(${MFEM_ALL_BENCHMARKS_TARGET_NAME} bench_dfem_linearized_simple)
endif(MFEM_USE_MPI)
#-------------------------------------------------------------------------------
# Function to add one benchmark from the tests/benchmarks directory.
@@ -32,7 +48,7 @@ function(add_benchmark name)
endif(MFEM_USE_CUDA)
add_executable(bench_${name} ${${NAME}_BENCH_SRCS})
target_link_libraries(bench_${name} mfem pthread)
target_link_libraries(bench_${name} PRIVATE mfem pthread)
add_dependencies(${MFEM_ALL_BENCHMARKS_TARGET_NAME} bench_${name})
add_test(NAME bench_${name}_cpu
@@ -49,10 +65,13 @@ function(add_benchmark name)
endfunction(add_benchmark)
#-------------------------------------------------------------------------------
add_benchmark(assembly_levels)
add_benchmark(ceed)
add_benchmark(dg_amr)
add_benchmark(elasticity)
add_benchmark(tmop)
add_benchmark(vector)
add_benchmark(virtuals)
if (MFEM_USE_BENCHMARK)
add_benchmark(assembly_levels)
add_benchmark(ceed)
add_benchmark(dfem)
add_benchmark(dg_amr)
add_benchmark(elasticity)
add_benchmark(tmop)
add_benchmark(vector)
add_benchmark(virtuals)
endif(MFEM_USE_BENCHMARK)
File diff suppressed because it is too large Load Diff
@@ -0,0 +1,342 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "mfem.hpp"
#ifdef MFEM_USE_MPI
#include "fem/dfem/doperator.hpp"
#include "fem/dfem/backends/global_qf/prelude.hpp"
#include "fem/dfem/backends/local_qf/prelude.hpp"
#include <cmath>
#include <iomanip>
#include <iostream>
#include <string>
using namespace mfem;
using namespace mfem::future;
#ifdef MFEM_USE_ENZYME
using dscalar_t = real_t;
#else
using dscalar_t = dual<real_t, real_t>;
#endif
template <int DIM>
struct DiffusionLocalMode
{
using dvecd_t = tensor<dscalar_t, DIM>;
using matd_t = tensor<real_t, DIM, DIM>;
MFEM_HOST_DEVICE inline auto operator()(const dvecd_t &dudxi,
const matd_t &J,
const real_t &w,
dvecd_t &dvdxi) const
{
const auto invJ = inv(J);
const auto invJt = transpose(invJ);
dvdxi = (dudxi * invJ) * invJt * det(J) * w;
}
};
template <int DIM>
struct DiffusionGlobalMode
{
void operator()(tensor_array<const real_t, DIM> &dudxi,
tensor_array<const real_t, DIM, DIM> &J,
tensor_array<const real_t> &w,
tensor_array<real_t, DIM> &dvdxi) const
{
mfem::forall<UseEnzyme>(J.size(), [=] MFEM_HOST_DEVICE (int q)
{
const auto invJ = inv(J(q));
const auto invJt = transpose(invJ);
dvdxi(q) = (dudxi(q) * invJ) * invJt * det(J(q)) * w(q);
});
}
};
template <int DIM, typename QFBackend> struct DiffusionQF;
template <int DIM> struct DiffusionQF<DIM, LocalQFBackend>
{
using type = DiffusionLocalMode<DIM>;
};
template <int DIM> struct DiffusionQF<DIM, GlobalQFBackend>
{
using type = DiffusionGlobalMode<DIM>;
};
struct Timings
{
double forward = 0.0;
double derivative = 0.0;
real_t error = 0.0;
};
template <typename F>
double TimeIt(const int iterations, MPI_Comm comm, F &&f)
{
MPI_Barrier(comm);
MFEM_DEVICE_SYNC;
StopWatch timer;
timer.Start();
for (int i = 0; i < iterations; i++)
{
f();
}
MFEM_DEVICE_SYNC;
timer.Stop();
const double local_time = timer.RealTime();
double global_time = 0.0;
MPI_Allreduce(&local_time, &global_time, 1, MPI_DOUBLE, MPI_MAX, comm);
return global_time / iterations;
}
template <int DIM>
Mesh MakeSimpleTensorMesh(int n)
{
if constexpr (DIM == 2)
{
return Mesh::MakeCartesian2D(n, n, Element::QUADRILATERAL,
true, 1.0, 1.0);
}
else
{
return Mesh::MakeCartesian3D(n, n, n, Element::HEXAHEDRON,
1.0, 1.0, 1.0);
}
}
template <int DIM>
int MeshSizeFromTargetDofs(const int order, const int target_dofs)
{
const real_t dofs_1d = std::pow(static_cast<real_t>(target_dofs),
1.0 / DIM);
return std::max(1, static_cast<int>(std::ceil((dofs_1d - 1.0) / order)));
}
template <int DIM>
auto GetGlobalTrueVSize(const int order, const int mesh_n)
{
Mesh smesh = MakeSimpleTensorMesh<DIM>(mesh_n);
ParMesh pmesh(MPI_COMM_WORLD, smesh);
smesh.Clear();
pmesh.EnsureNodes();
const int p = std::max(order, pmesh.GetNodalFESpace()->GetMaxElementOrder());
H1_FECollection fec(p, DIM);
ParFiniteElementSpace pfes(&pmesh, &fec);
return pfes.GlobalTrueVSize();
}
template <int DIM, typename QFBackend>
Timings RunBackendCase(const int order, const int mesh_n, const int warmup,
const int iterations)
{
Mesh smesh = MakeSimpleTensorMesh<DIM>(mesh_n);
ParMesh pmesh(MPI_COMM_WORLD, smesh);
smesh.Clear();
pmesh.EnsureNodes();
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
ParFiniteElementSpace *mfes = nodes->ParFESpace();
const int p = std::max(order, pmesh.GetNodalFESpace()->GetMaxElementOrder());
H1_FECollection fec(p, DIM);
ParFiniteElementSpace pfes(&pmesh, &fec);
const IntegrationRule *ir = &IntRules.Get(pmesh.GetTypicalElementGeometry(),
2 * p);
Array<int> all_domain_attr;
if (pmesh.attributes.Size() > 0)
{
all_domain_attr.SetSize(pmesh.attributes.Max());
all_domain_attr = 1;
}
static constexpr int U = 0, Coords = 1;
const auto in_fds = std::vector
{
FieldDescriptor{ U, &pfes },
FieldDescriptor{ Coords, mfes }
};
const auto out_fds = std::vector{ FieldDescriptor{ U, &pfes } };
DifferentiableOperator dop_mf(in_fds, out_fds, pmesh);
typename DiffusionQF<DIM, QFBackend>::type mf_apply_qf;
dop_mf.AddDomainIntegrator<QFBackend>(
mf_apply_qf,
Inputs<Gradient<U>, Gradient<Coords>, Weight> {},
Outputs<Gradient<U>> {},
*ir, all_domain_attr,
Derivatives<U> {});
Vector xtvec(pfes.GetTrueVSize()), ztvec(pfes.GetTrueVSize());
xtvec.Randomize(567);
Vector nodestv;
nodes->GetTrueDofs(nodestv);
// Move the fixed input state to device before warmup/timing so repeated
// applies do not pay host-to-device copies through aliased L-vectors.
xtvec.Read();
nodestv.Read();
MultiVector X{xtvec, nodestv};
MultiVector Z{ztvec};
auto ddop = dop_mf.GetDerivative(U, X, false);
Vector dztvec(ztvec.Size());
MultiVector DZ{dztvec};
for (int i = 0; i < warmup; i++)
{
dop_mf.Mult(X, Z);
ddop->Mult(X[0], DZ);
}
MFEM_DEVICE_SYNC;
// One correctness check: this diffusion action is linear in U, so the
// forward action and derivative action should agree for the same direction.
dop_mf.Mult(X, Z);
ddop->Mult(X[0], DZ);
Vector diff(ztvec);
diff -= dztvec;
const real_t local_error = diff.Normlinf();
real_t global_error = 0.0;
MPI_Allreduce(&local_error, &global_error, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
Timings timings;
timings.error = global_error;
timings.forward = TimeIt(iterations, pmesh.GetComm(), [&]()
{
dop_mf.Mult(X, Z);
});
timings.derivative = TimeIt(iterations, pmesh.GetComm(), [&]()
{
ddop->Mult(X[0], DZ);
});
return timings;
}
template <int DIM>
void RunCase(const int order, const int mesh_n, const int warmup,
const int iterations)
{
const char *mesh_name = DIM == 2 ? "quad" : "hex";
const auto tdofs = GetGlobalTrueVSize<DIM>(order, mesh_n);
if (Mpi::WorldRank() == 0)
{
mfem::out << mesh_name << " #dofs=" << tdofs << std::endl;
}
const Timings global = RunBackendCase<DIM, GlobalQFBackend>(order, mesh_n,
warmup,
iterations);
const Timings local = RunBackendCase<DIM, LocalQFBackend>(order, mesh_n,
warmup,
iterations);
const real_t error = std::max(global.error, local.error);
if (Mpi::WorldRank() == 0)
{
mfem::out << mesh_name << " Scalar Action Linearized timings (seconds):\n"
<< " forward global=" << global.forward
<< ", derivative global=" << global.derivative
<< ", overhead=" << global.derivative / global.forward << "x\n"
<< " forward local =" << local.forward
<< ", derivative local =" << local.derivative
<< ", overhead=" << local.derivative / local.forward << "x\n"
<< " forward local/global=" << local.forward / global.forward
<< "x\n"
<< " derivative local/global="
<< local.derivative / global.derivative << "x\n"
<< " linf_error=" << error << "\n";
}
}
int main(int argc, char *argv[])
{
Mpi::Init(argc, argv);
Hypre::Init();
int order = 3;
int quad_mesh_n = 32;
int hex_mesh_n = 8;
int target_dofs = 0;
int warmup = 3;
int iterations = 25;
const char *device_config = "cpu";
OptionsParser args(argc, argv);
args.AddOption(&order, "-o", "--order", "Finite element order.");
args.AddOption(&quad_mesh_n, "-nq", "--quad-mesh-size",
"Number of quad elements per direction.");
args.AddOption(&hex_mesh_n, "-nh", "--hex-mesh-size",
"Number of hex elements per direction.");
args.AddOption(&target_dofs, "-nd", "--num-dofs",
"Target number of dofs. If positive, overrides -nq/-nh and "
"computes element counts from the order.");
args.AddOption(&warmup, "-w", "--warmup", "Number of warmup iterations.");
args.AddOption(&iterations, "-i", "--iterations",
"Number of timed iterations.");
args.AddOption(&device_config, "-d", "--device",
"MFEM device configuration string.");
args.Parse();
if (!args.Good())
{
if (Mpi::WorldRank() == 0) { args.PrintUsage(mfem::out); }
return 1;
}
Device device(device_config);
if (Mpi::WorldRank() == 0)
{
args.PrintOptions(mfem::out);
device.Print(mfem::out);
mfem::out << std::scientific << std::setprecision(6)
<< "\nForward DifferentiableOperator::Mult vs "
<< "GetDerivative(...)->Mult\n";
}
if (target_dofs > 0)
{
quad_mesh_n = MeshSizeFromTargetDofs<2>(order, target_dofs);
hex_mesh_n = MeshSizeFromTargetDofs<3>(order, target_dofs);
if (Mpi::WorldRank() == 0)
{
mfem::out << "target #dofs=" << target_dofs
<< " -> quad n=" << quad_mesh_n
<< ", hex n=" << hex_mesh_n << std::endl;
}
}
RunCase<2>(order, quad_mesh_n, warmup, iterations);
RunCase<3>(order, hex_mesh_n, warmup, iterations);
return 0;
}
#else
int main(int, char *[])
{
mfem::out << "This benchmark requires MFEM_USE_MPI=YES.\n";
return MFEM_SKIP_RETURN_VALUE;
}
#endif // MFEM_USE_MPI
+2 -2
View File
@@ -20,8 +20,8 @@ CONFIG_MK = $(or $(wildcard $(MFEM_BUILD_DIR)/config/config.mk),\
MFEM_LIB_FILE = mfem_is_not_built
-include $(CONFIG_MK)
SEQ_TESTS = bench_assembly_levels bench_ceed bench_dg_amr bench_elasticity \
bench_tmop bench_vector bench_virtuals
SEQ_TESTS = bench_assembly_levels bench_ceed bench_dfem bench_dg_amr \
bench_elasticity bench_tmop bench_vector bench_virtuals
PAR_TESTS =
ifeq ($(MFEM_USE_MPI),NO)
TESTS = $(SEQ_TESTS)
+181 -168
View File
@@ -37,8 +37,21 @@ include_directories(BEFORE ${CMAKE_CURRENT_SOURCE_DIR})
set(UNIT_TESTS_SRCS
dfem/test_diffusion.cpp
dfem/test_divergence.cpp
dfem/test_functional.cpp
dfem/test_dfem_scratch.cpp
enzyme/test_enzyme_scratch.cpp
enzyme/test_enzyme_scratch_multikernel.cpp
enzyme/test_enzyme_reverse_tape.cpp
dfem/test_hyperelasticity.cpp
dfem/test_functional.cpp
dfem/test_functional_gradient.cpp
dfem/test_jvp_vjp.cpp
dfem/test_lvector_interface.cpp
dfem/test_mass.cpp
dfem/test_multiple_inputs.cpp
dfem/test_multiple_outputs.cpp
dfem/test_second_derivative.cpp
dfem/test_tmop.cpp
general/test_array.cpp
general/test_scan.cpp
general/test_arrays_by_name.cpp
@@ -180,11 +193,11 @@ set(UNIT_TESTS_SRCS
# SERIAL CPU TESTS: unit_tests
#-----------------------------------------------------------
if (MFEM_USE_CUDA)
set_property(SOURCE unit_test_main.cpp ${UNIT_TESTS_SRCS}
set_property(SOURCE unit_test_main.cpp ${UNIT_TESTS_SRCS}
PROPERTY LANGUAGE CUDA)
endif()
if (MFEM_USE_HIP)
set_property(SOURCE unit_test_main.cpp ${UNIT_TESTS_SRCS}
set_property(SOURCE unit_test_main.cpp ${UNIT_TESTS_SRCS}
PROPERTY HIP_SOURCE_PROPERTY_FORMAT TRUE)
endif()
@@ -208,7 +221,7 @@ add_dependencies(unit_tests copy_miniapps_nurbs_data)
# make unit_tests
# ctest -R unit_tests [-V]
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME unit_tests COMMAND unit_tests)
add_test(NAME unit_tests COMMAND unit_tests)
endif()
#-----------------------------------------------------------
@@ -216,15 +229,15 @@ endif()
#-----------------------------------------------------------
# Create CUDA executable and test
if (MFEM_USE_CUDA)
# gpu_unit_tests
set(GPU_UNIT_TESTS_SRCS gpu_unit_test_main.cpp)
set_property(SOURCE ${GPU_UNIT_TESTS_SRCS} PROPERTY LANGUAGE CUDA)
mfem_add_executable(gpu_unit_tests ${GPU_UNIT_TESTS_SRCS})
target_link_libraries(gpu_unit_tests unit_tests_srcs)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} gpu_unit_tests)
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME gpu_unit_tests COMMAND gpu_unit_tests)
endif()
# gpu_unit_tests
set(GPU_UNIT_TESTS_SRCS gpu_unit_test_main.cpp)
set_property(SOURCE ${GPU_UNIT_TESTS_SRCS} PROPERTY LANGUAGE CUDA)
mfem_add_executable(gpu_unit_tests ${GPU_UNIT_TESTS_SRCS})
target_link_libraries(gpu_unit_tests unit_tests_srcs)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} gpu_unit_tests)
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME gpu_unit_tests COMMAND gpu_unit_tests)
endif()
endif()
#-----------------------------------------------------------
@@ -232,14 +245,14 @@ endif()
#-----------------------------------------------------------
# Create HIP 'gpu_unit_tests' executable and test
if (MFEM_USE_HIP)
# gpu_unit_tests
set(GPU_UNIT_TESTS_SRCS gpu_unit_test_main.cpp)
mfem_add_executable(gpu_unit_tests ${GPU_UNIT_TESTS_SRCS})
target_link_libraries(gpu_unit_tests unit_tests_srcs)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} gpu_unit_tests)
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME gpu_unit_tests COMMAND gpu_unit_tests)
endif()
# gpu_unit_tests
set(GPU_UNIT_TESTS_SRCS gpu_unit_test_main.cpp)
mfem_add_executable(gpu_unit_tests ${GPU_UNIT_TESTS_SRCS})
target_link_libraries(gpu_unit_tests unit_tests_srcs)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} gpu_unit_tests)
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME gpu_unit_tests COMMAND gpu_unit_tests)
endif()
endif()
#-----------------------------------------------------------
@@ -251,61 +264,61 @@ endif()
# All device unit tests are built into a separate executable, in order to be
# able to change the device.
function(add_serial_miniapp_test name test_uvm)
string(TOUPPER ${name} NAME)
string(TOUPPER ${name} NAME)
set(${NAME}_TESTS_SRCS miniapps/test_${name}.cpp)
if (MFEM_USE_CUDA)
set_property(SOURCE ${${NAME}_TESTS_SRCS} PROPERTY LANGUAGE CUDA)
endif(MFEM_USE_CUDA)
if (MFEM_USE_HIP)
set_property(SOURCE ${${NAME}_TESTS_SRCS} PROPERTY HIP_SOURCE_PROPERTY_FORMAT TRUE)
endif(MFEM_USE_HIP)
set(${NAME}_TESTS_SRCS miniapps/test_${name}.cpp)
if (MFEM_USE_CUDA)
set_property(SOURCE ${${NAME}_TESTS_SRCS} PROPERTY LANGUAGE CUDA)
endif(MFEM_USE_CUDA)
if (MFEM_USE_HIP)
set_property(SOURCE ${${NAME}_TESTS_SRCS} PROPERTY HIP_SOURCE_PROPERTY_FORMAT TRUE)
endif(MFEM_USE_HIP)
mfem_add_executable(${name}_tests_cpu ${${NAME}_TESTS_SRCS})
add_dependencies(${name}_tests_cpu copy_miniapps_meshing_data)
add_dependencies(${name}_tests_cpu ${MFEM_TEST_EXEC_PREREQUISITES_TARGET_NAME})
target_compile_definitions(${name}_tests_cpu PUBLIC MFEM_${NAME}_DEVICE="cpu")
target_link_libraries(${name}_tests_cpu mfem)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} ${name}_tests_cpu)
mfem_add_executable(${name}_tests_cpu ${${NAME}_TESTS_SRCS})
add_dependencies(${name}_tests_cpu copy_miniapps_meshing_data)
add_dependencies(${name}_tests_cpu ${MFEM_TEST_EXEC_PREREQUISITES_TARGET_NAME})
target_compile_definitions(${name}_tests_cpu PUBLIC MFEM_${NAME}_DEVICE="cpu")
target_link_libraries(${name}_tests_cpu mfem)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} ${name}_tests_cpu)
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME ${name}_tests_cpu COMMAND ${name}_tests_cpu)
endif()
mfem_add_executable(${name}_tests_debug ${${NAME}_TESTS_SRCS})
add_dependencies(${name}_tests_debug copy_miniapps_meshing_data)
add_dependencies(${name}_tests_debug ${MFEM_TEST_EXEC_PREREQUISITES_TARGET_NAME})
target_compile_definitions(${name}_tests_debug PUBLIC MFEM_${NAME}_DEVICE="debug")
target_link_libraries(${name}_tests_debug mfem)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} ${name}_tests_debug)
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME ${name}_tests_debug COMMAND ${name}_tests_debug)
endif()
if (MFEM_USE_CUDA OR MFEM_USE_HIP)
mfem_add_executable(${name}_tests_gpu ${${NAME}_TESTS_SRCS})
add_dependencies(${name}_tests_gpu copy_miniapps_meshing_data)
add_dependencies(${name}_tests_gpu ${MFEM_TEST_EXEC_PREREQUISITES_TARGET_NAME})
target_compile_definitions(${name}_tests_gpu PUBLIC MFEM_${NAME}_DEVICE="gpu")
target_link_libraries(${name}_tests_gpu mfem)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} ${name}_tests_gpu)
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME ${name}_tests_cpu COMMAND ${name}_tests_cpu)
add_test(NAME ${name}_tests_gpu COMMAND ${name}_tests_gpu)
endif()
mfem_add_executable(${name}_tests_debug ${${NAME}_TESTS_SRCS})
add_dependencies(${name}_tests_debug copy_miniapps_meshing_data)
add_dependencies(${name}_tests_debug ${MFEM_TEST_EXEC_PREREQUISITES_TARGET_NAME})
target_compile_definitions(${name}_tests_debug PUBLIC MFEM_${NAME}_DEVICE="debug")
target_link_libraries(${name}_tests_debug mfem)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} ${name}_tests_debug)
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME ${name}_tests_debug COMMAND ${name}_tests_debug)
endif()
if (MFEM_USE_CUDA OR MFEM_USE_HIP)
mfem_add_executable(${name}_tests_gpu ${${NAME}_TESTS_SRCS})
add_dependencies(${name}_tests_gpu copy_miniapps_meshing_data)
add_dependencies(${name}_tests_gpu ${MFEM_TEST_EXEC_PREREQUISITES_TARGET_NAME})
target_compile_definitions(${name}_tests_gpu PUBLIC MFEM_${NAME}_DEVICE="gpu")
target_link_libraries(${name}_tests_gpu mfem)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} ${name}_tests_gpu)
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME ${name}_tests_gpu COMMAND ${name}_tests_gpu)
endif()
if (test_uvm)
mfem_add_executable(${name}_tests_gpu_uvm ${${NAME}_TESTS_SRCS})
add_dependencies(${name}_tests_gpu_uvm copy_miniapps_meshing_data)
add_dependencies(${name}_tests_gpu_uvm ${MFEM_TEST_EXEC_PREREQUISITES_TARGET_NAME})
target_compile_definitions(${name}_tests_gpu_uvm PUBLIC
if (test_uvm)
mfem_add_executable(${name}_tests_gpu_uvm ${${NAME}_TESTS_SRCS})
add_dependencies(${name}_tests_gpu_uvm copy_miniapps_meshing_data)
add_dependencies(${name}_tests_gpu_uvm ${MFEM_TEST_EXEC_PREREQUISITES_TARGET_NAME})
target_compile_definitions(${name}_tests_gpu_uvm PUBLIC
MFEM_${NAME}_DEVICE="gpu:uvm")
target_link_libraries(${name}_tests_gpu_uvm mfem)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME}
target_link_libraries(${name}_tests_gpu_uvm mfem)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME}
${name}_tests_gpu_uvm)
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME ${name}_tests_gpu_uvm COMMAND ${name}_tests_gpu_uvm)
endif()
endif()
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME ${name}_tests_gpu_uvm COMMAND ${name}_tests_gpu_uvm)
endif()
endif()
endif()
endfunction(add_serial_miniapp_test)
add_serial_miniapp_test(sedov ON) # UVM ON
@@ -318,25 +331,25 @@ add_serial_miniapp_test(tmop_pa OFF) # UVM OFF
#-----------------------------------------------------------
# Add 'ceed_tests' executable and test; add extra tests 'ceed_test_*'
if (MFEM_USE_CEED)
set(CEED_TESTS_SRCS
set(CEED_TESTS_SRCS
ceed/test_ceed.cpp
ceed/test_ceed_main.cpp)
if (MFEM_USE_CUDA)
set_property(SOURCE ${CEED_TESTS_SRCS} PROPERTY LANGUAGE CUDA)
endif(MFEM_USE_CUDA)
mfem_add_executable(ceed_tests ${CEED_TESTS_SRCS})
target_link_libraries(ceed_tests mfem)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} ceed_tests)
# Add CEED tests
add_test(NAME ceed_tests COMMAND ceed_tests)
if (MFEM_USE_CUDA)
add_test(NAME ceed_tests_cuda_ref
if (MFEM_USE_CUDA)
set_property(SOURCE ${CEED_TESTS_SRCS} PROPERTY LANGUAGE CUDA)
endif(MFEM_USE_CUDA)
mfem_add_executable(ceed_tests ${CEED_TESTS_SRCS})
target_link_libraries(ceed_tests mfem)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} ceed_tests)
# Add CEED tests
add_test(NAME ceed_tests COMMAND ceed_tests)
if (MFEM_USE_CUDA)
add_test(NAME ceed_tests_cuda_ref
COMMAND ceed_tests --device ceed-cuda:/gpu/cuda/ref)
add_test(NAME ceed_tests_cuda_shared
add_test(NAME ceed_tests_cuda_shared
COMMAND ceed_tests --device ceed-cuda:/gpu/cuda/shared)
add_test(NAME ceed_tests_cuda_gen
add_test(NAME ceed_tests_cuda_gen
COMMAND ceed_tests --device ceed-cuda:/gpu/cuda/gen)
endif()
endif()
endif()
#-----------------------------------------------------------
@@ -344,52 +357,52 @@ endif()
#-----------------------------------------------------------
# Define executables and tests
if (MFEM_USE_MPI)
# punit_tests
if (MFEM_USE_CUDA)
set_property(SOURCE punit_test_main.cpp PROPERTY LANGUAGE CUDA)
endif()
mfem_add_executable(punit_tests punit_test_main.cpp)
target_link_libraries(punit_tests unit_tests_srcs)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} punit_tests)
foreach(np 1 ${MFEM_MPI_NP})
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME punit_tests_np=${np}
# punit_tests
if (MFEM_USE_CUDA)
set_property(SOURCE punit_test_main.cpp PROPERTY LANGUAGE CUDA)
endif()
mfem_add_executable(punit_tests punit_test_main.cpp)
target_link_libraries(punit_tests unit_tests_srcs)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} punit_tests)
foreach(np 1 ${MFEM_MPI_NP})
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME punit_tests_np=${np}
COMMAND ${MPIEXEC} ${MPIEXEC_NUMPROC_FLAG} ${np}
${MPIEXEC_PREFLAGS} $<TARGET_FILE:punit_tests>
${MPIEXEC_POSTFLAGS})
endif()
endif()
endforeach()
if (MFEM_USE_CUDA)
# pgpu_unit_tests
set(PGPU_UNIT_TESTS_SRCS pgpu_unit_test_main.cpp)
set_property(SOURCE ${PGPU_UNIT_TESTS_SRCS} PROPERTY LANGUAGE CUDA)
mfem_add_executable(pgpu_unit_tests ${PGPU_UNIT_TESTS_SRCS})
target_link_libraries(pgpu_unit_tests unit_tests_srcs)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} pgpu_unit_tests)
foreach(np 1 ${MFEM_MPI_NP})
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME pgpu_unit_tests_np=${np}
COMMAND ${MPIEXEC} ${MPIEXEC_NUMPROC_FLAG} ${np}
${MPIEXEC_PREFLAGS} $<TARGET_FILE:pgpu_unit_tests>
${MPIEXEC_POSTFLAGS})
endif()
endforeach()
if (MFEM_USE_CUDA)
# pgpu_unit_tests
set(PGPU_UNIT_TESTS_SRCS pgpu_unit_test_main.cpp)
set_property(SOURCE ${PGPU_UNIT_TESTS_SRCS} PROPERTY LANGUAGE CUDA)
mfem_add_executable(pgpu_unit_tests ${PGPU_UNIT_TESTS_SRCS})
target_link_libraries(pgpu_unit_tests unit_tests_srcs)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} pgpu_unit_tests)
foreach(np 1 ${MFEM_MPI_NP})
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME pgpu_unit_tests_np=${np}
endif()
if (MFEM_USE_HIP)
# pgpu_unit_tests
set(PGPU_UNIT_TESTS_SRCS pgpu_unit_test_main.cpp)
mfem_add_executable(pgpu_unit_tests ${PGPU_UNIT_TESTS_SRCS})
target_link_libraries(pgpu_unit_tests unit_tests_srcs)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} pgpu_unit_tests)
foreach(np 1 ${MFEM_MPI_NP})
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME pgpu_unit_tests_np=${np}
COMMAND ${MPIEXEC} ${MPIEXEC_NUMPROC_FLAG} ${np}
${MPIEXEC_PREFLAGS} $<TARGET_FILE:pgpu_unit_tests>
${MPIEXEC_POSTFLAGS})
endif()
endforeach()
endif()
if (MFEM_USE_HIP)
# pgpu_unit_tests
set(PGPU_UNIT_TESTS_SRCS pgpu_unit_test_main.cpp)
mfem_add_executable(pgpu_unit_tests ${PGPU_UNIT_TESTS_SRCS})
target_link_libraries(pgpu_unit_tests unit_tests_srcs)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} pgpu_unit_tests)
foreach(np 1 ${MFEM_MPI_NP})
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME pgpu_unit_tests_np=${np}
COMMAND ${MPIEXEC} ${MPIEXEC_NUMPROC_FLAG} ${np}
${MPIEXEC_PREFLAGS} $<TARGET_FILE:pgpu_unit_tests>
${MPIEXEC_POSTFLAGS})
endif()
endforeach()
endif()
endif()
endforeach()
endif()
endif(MFEM_USE_MPI)
#-----------------------------------------------------------
@@ -399,72 +412,72 @@ endif(MFEM_USE_MPI)
#-----------------------------------------------------------
# Function to add one MPI executable for a test.
function(add_mpi_executable_test name dev)
string(TOUPPER ${name} NAME)
string(REPLACE "_" ":" DEV ${dev})
mfem_add_executable(p${name}_tests_${dev} ${PAR_${NAME}_TESTS_SRCS})
target_compile_definitions(p${name}_tests_${dev} PUBLIC MFEM_${NAME}_MPI=1)
target_compile_definitions(p${name}_tests_${dev} PUBLIC MFEM_${NAME}_DEVICE="${DEV}")
target_link_libraries(p${name}_tests_${dev} mfem)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} p${name}_tests_${dev})
string(TOUPPER ${name} NAME)
string(REPLACE "_" ":" DEV ${dev})
mfem_add_executable(p${name}_tests_${dev} ${PAR_${NAME}_TESTS_SRCS})
target_compile_definitions(p${name}_tests_${dev} PUBLIC MFEM_${NAME}_MPI=1)
target_compile_definitions(p${name}_tests_${dev} PUBLIC MFEM_${NAME}_DEVICE="${DEV}")
target_link_libraries(p${name}_tests_${dev} mfem)
add_dependencies(${MFEM_ALL_TESTS_TARGET_NAME} p${name}_tests_${dev})
endfunction(add_mpi_executable_test)
# Function to add one test from the tests/unit/miniapp directory.
function(add_parallel_miniapp_test name HYPRE_MM)
string(TOUPPER ${name} NAME)
string(TOUPPER ${name} NAME)
function(add_mpi_unit_test DEV NP)
set(test_name p${name}_tests_${DEV})
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME ${test_name}_np=${NP}
function(add_mpi_unit_test DEV NP)
set(test_name p${name}_tests_${DEV})
if (MFEM_USE_DOUBLE) # otherwise returns MFEM_SKIP_RETURN_VALUE
add_test(NAME ${test_name}_np=${NP}
COMMAND ${MPIEXEC} ${MPIEXEC_NUMPROC_FLAG} ${NP}
${MPIEXEC_PREFLAGS} $<TARGET_FILE:${test_name}>
${MPIEXEC_POSTFLAGS})
endif()
endfunction()
set(PAR_${NAME}_TESTS_SRCS miniapps/test_${name}.cpp)
if (MFEM_USE_CUDA)
set_property(SOURCE ${PAR_${NAME}_TESTS_SRCS} PROPERTY LANGUAGE CUDA)
endif()
endfunction()
set(backends cpu)
if (HYPRE_MM)
# psedov_tests_debug_* will return MFEM_SKIP_RETURN_VALUE when all of
# the following conditions are met:
# * MFEM_SEDOV_MPI is defined (true here)
# * MFEM_DEBUG is defined
# * MFEM_SEDOV_DEVICE is "debug" (the case added here)
# * HypreUsingGPU() is true; this is the same as: HYPRE_USING_GPU is
# defined and MFEM_HYPRE_VERSION < 23100 (if the version is >= 23100,
# the code will switch to HYPRE running on CPU).
# We check these conditions here to skip the "debug" backend and avoid
# the ctest failure.
if (NOT ((${name} STREQUAL "sedov") AND MFEM_DEBUG AND
set(PAR_${NAME}_TESTS_SRCS miniapps/test_${name}.cpp)
if (MFEM_USE_CUDA)
set_property(SOURCE ${PAR_${NAME}_TESTS_SRCS} PROPERTY LANGUAGE CUDA)
endif()
set(backends cpu)
if (HYPRE_MM)
# psedov_tests_debug_* will return MFEM_SKIP_RETURN_VALUE when all of
# the following conditions are met:
# * MFEM_SEDOV_MPI is defined (true here)
# * MFEM_DEBUG is defined
# * MFEM_SEDOV_DEVICE is "debug" (the case added here)
# * HypreUsingGPU() is true; this is the same as: HYPRE_USING_GPU is
# defined and MFEM_HYPRE_VERSION < 23100 (if the version is >= 23100,
# the code will switch to HYPRE running on CPU).
# We check these conditions here to skip the "debug" backend and avoid
# the ctest failure.
if (NOT ((${name} STREQUAL "sedov") AND MFEM_DEBUG AND
(HYPRE_USING_CUDA OR HYPRE_USING_HIP) AND
(${MFEM_HYPRE_VERSION} LESS "23100")))
list(APPEND backends debug)
endif()
list(APPEND backends debug)
endif()
if (MFEM_USE_CUDA OR MFEM_USE_HIP)
list(APPEND backends gpu)
if (HYPRE_MM)
list(APPEND backends gpu_uvm)
endif()
endif()
if (MFEM_USE_CUDA OR MFEM_USE_HIP)
list(APPEND backends gpu)
if (HYPRE_MM)
list(APPEND backends gpu_uvm)
endif()
endif()
set(MPI_NPS 1 ${MFEM_MPI_NP})
foreach(dev ${backends})
add_mpi_executable_test(${name} ${dev})
foreach(np ${MPI_NPS})
add_mpi_unit_test(${dev} ${np})
endforeach()
set(MPI_NPS 1 ${MFEM_MPI_NP})
foreach(dev ${backends})
add_mpi_executable_test(${name} ${dev})
foreach(np ${MPI_NPS})
add_mpi_unit_test(${dev} ${np})
endforeach()
endforeach()
endfunction(add_parallel_miniapp_test)
# Additional MPI unit tests
if (MFEM_USE_MPI)
add_parallel_miniapp_test(sedov TRUE)
add_parallel_miniapp_test(tmop_pa FALSE)
add_parallel_miniapp_test(sedov TRUE)
add_parallel_miniapp_test(tmop_pa FALSE)
endif(MFEM_USE_MPI)
#-----------------------------------------------------------
@@ -473,10 +486,10 @@ endif(MFEM_USE_MPI)
#-----------------------------------------------------------
set(DEBUG_DEVICE_SRCS miniapps/test_debug_device.cpp)
if (MFEM_USE_CUDA)
set_property(SOURCE ${DEBUG_DEVICE_SRCS} PROPERTY LANGUAGE CUDA)
set_property(SOURCE ${DEBUG_DEVICE_SRCS} PROPERTY LANGUAGE CUDA)
endif()
if (MFEM_USE_HIP)
set_property(SOURCE ${DEBUG_DEVICE_SRCS}
set_property(SOURCE ${DEBUG_DEVICE_SRCS}
PROPERTY HIP_SOURCE_PROPERTY_FORMAT TRUE)
endif()
mfem_add_executable(debug_device_tests ${DEBUG_DEVICE_SRCS})
+660
View File
@@ -0,0 +1,660 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
// Multi-kernel scratch regression for the weak residual
//
// F(u)_i = int_Omega phi_i c u^3 dx,
//
// evaluated as the scratch chain s = u, s = s*u, y = c*s*u. The directional
// derivative is
//
// DF(u)[du]_i = int_Omega phi_i 3 c u^2 du dx.
//
// If the tangent stored in the qfunction scratch shadow is lost between the
// split scratch updates, the final product only sees the direct derivative of
// the last factor and produces int_Omega phi_i c u^2 du dx instead. This test
// checks both the direct DerivativeAction path and the cached
// DerivativeSetup+DerivativeApply path against the factor-of-3 result.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
// Test for the dFEM global qfunction with split computation and scratch space.
#include "../unit_tests.hpp"
#include "mfem.hpp"
#ifdef MFEM_USE_MPI
#include "../../../fem/dfem/doperator.hpp"
#include "../../../fem/dfem/backends/global_qf/prelude.hpp"
#include "../../../linalg/tensor_arrays.hpp"
using namespace std;
using namespace mfem;
using namespace mfem::future;
using dscalar_t = real_t;
///<--- Q-functions
constexpr int U = 1;
constexpr int Y = 2;
constexpr int COEF = 3;
constexpr int COORDINATES = 4;
// Global qf with splitting and scratch space.
// The user only writes operator(); the shared base handles scratch setup.
struct CubicQFWithScratch : QFWithScratchType
{
void operator()(tensor_array<const dscalar_t> &x,
tensor_array<const dscalar_t> &coef,
tensor_array<const real_t, 2, 2> &J,
tensor_array<const real_t> &w,
tensor_array<dscalar_t> &y) const
{
const int NQ = nq;
MFEM_ASSERT(NQ == static_cast<int>(x.size()),
"unexpected number of quadrature points");
auto scratch_q = make_tensor_array<>(scratch[0], NQ);
for (int q = 0; q < NQ; ++q)
{
scratch_q(q) = x(q);
}
for (int q = 0; q < NQ; ++q)
{
scratch_q(q) = scratch_q(q) * x(q);
}
for (int q = 0; q < NQ; ++q)
{
y(q) = coef(q) * scratch_q(q) * x(q) * det(J(q)) * w(q);
}
}
};
template <int DIM>
struct CubicQFWithScratchMultipleSizes : QFWithScratchType
{
void operator()(tensor_array<const dscalar_t> &x,
tensor_array<const dscalar_t> &coef,
tensor_array<const real_t, 2, 2> &J,
tensor_array<const real_t> &w,
tensor_array<dscalar_t> &y) const
{
const int NQ = nq;
MFEM_ASSERT(NQ == static_cast<int>(x.size()),
"unexpected number of quadrature points");
auto scratch_scalar = make_tensor_array<>(scratch[0], NQ);
auto scratch_vector = make_tensor_array<DIM>(scratch[1], NQ);
for (int q = 0; q < NQ; ++q)
{
scratch_vector(q)(0) = x(q);
scratch_vector(q)(1) = x(q) * x(q);
}
for (int q = 0; q < NQ; ++q)
{
scratch_scalar(q) = scratch_vector(q)(0) * scratch_vector(q)(1);
}
for (int q = 0; q < NQ; ++q)
{
y(q) = coef(q) * scratch_scalar(q) * det(J(q)) * w(q);
}
}
};
struct CubicQFWithGlobalScratch : QFWithGlobalScratchType
{
void operator()(tensor_array<const dscalar_t> &x,
tensor_array<const dscalar_t> &coef,
tensor_array<const real_t, 2, 2> &J,
tensor_array<const real_t> &w,
tensor_array<dscalar_t> &y) const
{
const int NQ = nq;
MFEM_ASSERT(NQ == static_cast<int>(x.size()),
"unexpected number of quadrature points");
// Unpack the scratch vectors from the scratch bank
auto scratch_q = make_tensor_array<>(GetScratchPointer(0), NQ);
// Unpack global scratch
auto &has_scale = GetGlobalScratch<0>();
const auto scale = GetGlobalScratch<1>();
auto &global_vector = GetGlobalScratch<2>();
has_scale = global_vector.Size() >
0; // If the global vector is non-empty, we will use it to scale the output
if (has_scale)
{
global_vector(0) = 1.0;
}
for (int q = 0; q < NQ; ++q)
{
scratch_q(q) = x(q) * x(q);
}
for (int q = 0; q < NQ; ++q)
{
const real_t global_scale = has_scale ? scale * global_vector(0) : 0.0;
y(q) = global_scale * coef(q) * scratch_q(q) * x(q) * det(J(q)) * w(q);
}
}
};
///<--- Utils
/// @param fes
/// @param x
void FillInput(ParFiniteElementSpace &fes, Coefficient &input_coeff, Vector &x)
{
GridFunction x_gf(&fes);
x_gf.ProjectCoefficient(input_coeff);
x_gf.GetTrueDofs(x);
}
void FillQData(FiniteElementSpace &fes, const IntegrationRule &ir,
Coefficient &coeff_fc, QuadratureFunction &coef)
{
QuadratureSpace qspace(*fes.GetMesh(), ir);
QuadratureFunction coef_qf(qspace);
coeff_fc.Project(coef_qf);
coef = coef_qf;
}
void CheckResults(ParFiniteElementSpace &fes, const IntegrationRule &ir,
Vector &y, Vector &dy)
{
FunctionCoefficient expected_coeff([](const Vector &p)
{
const real_t input = 1.0 + p(0) + 0.25 * (p.Size() > 1 ? p(1) : 0.0);
const real_t coeff = 0.5 + p(0) + 0.125 * (p.Size() > 1 ? p(1) : 0.0);
return coeff * input * input * input;
});
ParLinearForm expected_lf(&fes);
expected_lf.AddDomainIntegrator(new DomainLFIntegrator(expected_coeff, &ir));
expected_lf.Assemble();
Vector expected_y(fes.GetTrueVSize());
fes.GetProlongationMatrix()->MultTranspose(expected_lf, expected_y);
y -= expected_y;
const real_t local_err = y.Normlinf();
real_t global_err = 0.0;
MPI_Allreduce(&local_err, &global_err, 1, MPITypeMap<real_t>::mpi_type,
MPI_MAX, MPI_COMM_WORLD);
FunctionCoefficient expected_deriv_coeff([](const Vector &p)
{
const real_t input = 1.0 + p(0) + 0.25 * (p.Size() > 1 ? p(1) : 0.0);
const real_t coeff = 0.5 + p(0) + 0.125 * (p.Size() > 1 ? p(1) : 0.0);
return 3.0 * coeff * input * input;
});
ParLinearForm expected_deriv_lf(&fes);
expected_deriv_lf.AddDomainIntegrator(new DomainLFIntegrator(
expected_deriv_coeff, &ir));
expected_deriv_lf.Assemble();
Vector expected_dy(fes.GetTrueVSize());
fes.GetProlongationMatrix()->MultTranspose(expected_deriv_lf, expected_dy);
dy -= expected_dy;
const real_t local_deriv_err = dy.Normlinf();
real_t global_deriv_err = 0.0;
MPI_Allreduce(&local_deriv_err, &global_deriv_err, 1,
MPITypeMap<real_t>::mpi_type,
MPI_MAX, MPI_COMM_WORLD);
if (verbose_tests && Mpi::Root())
{
mfem::out << "Primal output max error: " << global_err << endl;
mfem::out << "Derivative output max error: "
<< global_deriv_err << endl;
}
REQUIRE(global_err == MFEM_Approx(0.0));
REQUIRE(global_deriv_err == MFEM_Approx(0.0));
}
void CheckScratchResults(ParMesh &pmesh, const IntegrationRule &ir,
const Vector &scratch, const Vector &scratch_d)
{
REQUIRE(scratch.Size() == scratch_d.Size());
REQUIRE(scratch.Size() == pmesh.GetNE() * ir.GetNPoints());
const real_t *scratch_h = scratch.HostRead();
const real_t *scratch_d_h = scratch_d.HostRead();
real_t local_scratch_err = 0.0;
real_t local_scratch_d_err = 0.0;
for (int e = 0; e < pmesh.GetNE(); e++)
{
ElementTransformation *T = pmesh.GetElementTransformation(e);
for (int q = 0; q < ir.GetNPoints(); q++)
{
const IntegrationPoint &ip = ir.IntPoint(q);
T->SetIntPoint(&ip);
Vector p;
T->Transform(ip, p);
const real_t u_q = 1.0 + p(0) + 0.25 * (p.Size() > 1 ? p(1) : 0.0);
const int idx = q + ir.GetNPoints() * e;
local_scratch_err = std::max(local_scratch_err,
std::abs(scratch_h[idx] - u_q * u_q));
local_scratch_d_err = std::max(local_scratch_d_err,
std::abs(scratch_d_h[idx] - 2.0 * u_q));
}
}
real_t global_scratch_err = 0.0;
real_t global_scratch_d_err = 0.0;
MPI_Allreduce(&local_scratch_err, &global_scratch_err, 1,
MPITypeMap<real_t>::mpi_type, MPI_MAX, MPI_COMM_WORLD);
MPI_Allreduce(&local_scratch_d_err, &global_scratch_d_err, 1,
MPITypeMap<real_t>::mpi_type, MPI_MAX, MPI_COMM_WORLD);
if (verbose_tests && Mpi::Root())
{
mfem::out << "Scratch max error: " << global_scratch_err << endl;
mfem::out << "Scratch derivative max error: "
<< global_scratch_d_err << endl;
}
REQUIRE(global_scratch_err == MFEM_Approx(0.0));
REQUIRE(global_scratch_d_err == MFEM_Approx(0.0));
}
///<--- Test
TEST_CASE("dFEM Scratch scalar", "[Parallel][dFEM][Scratch-Scalar]")
{
int order = 2;
int ref_levels = 1;
///<--- Mesh and finite element space setup
Mesh mesh = Mesh::MakeCartesian2D(2, 2, Element::QUADRILATERAL, true, 1.0,
1.0);
for (int l = 0; l < ref_levels; l++)
{
mesh.UniformRefinement();
}
ParMesh pmesh(MPI_COMM_WORLD, mesh);
pmesh.EnsureNodes();
H1_FECollection fec(order, pmesh.Dimension());
ParFiniteElementSpace fes(&pmesh, &fec);
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
ParFiniteElementSpace *nodes_fes = nodes->ParFESpace();
Vector nodes_tvec;
nodes->GetTrueDofs(nodes_tvec);
///<--- dFEM setup
const IntegrationRule &ir = IntRules.Get(Geometry::SQUARE, 2 * order + 1);
QuadratureSpace qspace(pmesh, ir);
VectorQuadratureSpace coef_qspace(qspace, 1);
QuadratureFunction coef(coef_qspace);
coef.UseDevice(true);
FunctionCoefficient coeff_fc([](const Vector &p)
{ return 0.5 + p(0) + 0.125 * (p.Size() > 1 ? p(1) : 0.0); });
FillQData(fes, ir, coeff_fc, coef);
Array<int> all_domain_attr(pmesh.attributes.Max());
all_domain_attr = 1;
const std::vector<FieldDescriptor> inputs
{
{U, &fes},
{COEF, &coef_qspace},
{COORDINATES, nodes_fes}};
const std::vector<FieldDescriptor> outputs
{
{Y, &fes}};
DifferentiableOperator dop(inputs, outputs, pmesh);
// Define the cubic qfunction with scratch space
// Requesting one scalar scratch vector
// Equivalent to
// cubic_qf.SetScratch(pmesh.GetNE() * ir.GetNPoints(), 1, 1);
CubicQFWithScratch cubic_qf;
cubic_qf.SetScratch(pmesh.GetNE() * ir.GetNPoints(), {1});
dop.AddDomainIntegrator<GlobalQFBackend>(
cubic_qf,
Inputs<Value<U>, Identity<COEF>, Gradient<COORDINATES>, Weight> {},
Outputs<Value<Y>> {},
ir, all_domain_attr,
Derivatives<U> {});
Vector x(fes.GetTrueVSize()), y(fes.GetTrueVSize()), dx(fes.GetTrueVSize()),
dy(fes.GetTrueVSize());
x.UseDevice(true);
y.UseDevice(true);
dx.UseDevice(true);
dy.UseDevice(true);
FunctionCoefficient input_coeff([](const Vector &p)
{ return 1.0 + p(0) + 0.25 * (p.Size() > 1 ? p(1) : 0.0); });
FillInput(fes, input_coeff, x);
ConstantCoefficient direction_coeff(1.0);
FillInput(fes, direction_coeff, dx);
y = 0.0;
dy = 0.0;
///<--- Apply the operator
MultiVector X{x, coef, nodes_tvec};
MultiVector Y{y};
dop.Mult(X, Y);
//<--- Apply derivative operator
auto dop_deriv = dop.GetDerivative(U, X);
MultiVector dY{dy};
dop_deriv->Mult(dx, dY);
///<--- Check the result against the expected output
CheckResults(fes, ir, y, dy);
}
TEST_CASE("dFEM Scratch multiple sizes",
"[Parallel][dFEM][Scratch-Multiple-Sizes]")
{
int order = 2;
int ref_levels = 1;
int DIM = 2;
///<--- Mesh and finite element space setup
Mesh mesh = Mesh::MakeCartesian2D(2, 2, Element::QUADRILATERAL, true, 1.0,
1.0);
for (int l = 0; l < ref_levels; l++)
{
mesh.UniformRefinement();
}
ParMesh pmesh(MPI_COMM_WORLD, mesh);
pmesh.EnsureNodes();
H1_FECollection fec(order, pmesh.Dimension());
ParFiniteElementSpace fes(&pmesh, &fec);
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
ParFiniteElementSpace *nodes_fes = nodes->ParFESpace();
Vector nodes_tvec;
nodes->GetTrueDofs(nodes_tvec);
///<--- dFEM setup
const IntegrationRule &ir = IntRules.Get(Geometry::SQUARE, 2 * order + 1);
QuadratureSpace qspace(pmesh, ir);
VectorQuadratureSpace coef_qspace(qspace, 1);
QuadratureFunction coef(coef_qspace);
coef.UseDevice(true);
FunctionCoefficient coeff_fc([](const Vector &p)
{ return 0.5 + p(0) + 0.125 * (p.Size() > 1 ? p(1) : 0.0); });
FillQData(fes, ir, coeff_fc, coef);
Array<int> all_domain_attr(pmesh.attributes.Max());
all_domain_attr = 1;
const std::vector<FieldDescriptor> inputs
{
{U, &fes},
{COEF, &coef_qspace},
{COORDINATES, nodes_fes}};
const std::vector<FieldDescriptor> outputs
{
{Y, &fes}};
DifferentiableOperator dop(inputs, outputs, pmesh);
// Define the cubic qfunction with scratch space
// Requesting one scalar scratch vector per dimension
CubicQFWithScratch cubic_qf;
cubic_qf.SetScratch(pmesh.GetNE() * ir.GetNPoints(), {1, DIM});
dop.AddDomainIntegrator<GlobalQFBackend>(
cubic_qf,
Inputs<Value<U>, Identity<COEF>, Gradient<COORDINATES>, Weight> {},
Outputs<Value<Y>> {},
ir, all_domain_attr,
Derivatives<U> {});
Vector x(fes.GetTrueVSize()), y(fes.GetTrueVSize()), dx(fes.GetTrueVSize()),
dy(fes.GetTrueVSize());
x.UseDevice(true);
y.UseDevice(true);
dx.UseDevice(true);
dy.UseDevice(true);
FunctionCoefficient input_coeff([](const Vector &p)
{ return 1.0 + p(0) + 0.25 * (p.Size() > 1 ? p(1) : 0.0); });
FillInput(fes, input_coeff, x);
ConstantCoefficient direction_coeff(1.0);
FillInput(fes, direction_coeff, dx);
y = 0.0;
dy = 0.0;
///<--- Apply the operator
MultiVector X{x, coef, nodes_tvec};
MultiVector Y{y};
dop.Mult(X, Y);
//<--- Apply derivative operator
auto dop_deriv = dop.GetDerivative(U, X);
MultiVector dY{dy};
dop_deriv->Mult(dx, dY);
///<--- Check the result against the expected output
CheckResults(fes, ir, y, dy);
}
TEST_CASE("dFEM Global Scratch with tuple objects",
"[Parallel][dFEM][GlobalScratch]")
{
int order = 2;
int ref_levels = 1;
///<--- Mesh and finite element space setup
Mesh mesh = Mesh::MakeCartesian2D(2, 2, Element::QUADRILATERAL, true, 1.0,
1.0);
for (int l = 0; l < ref_levels; l++)
{
mesh.UniformRefinement();
}
ParMesh pmesh(MPI_COMM_WORLD, mesh);
pmesh.EnsureNodes();
H1_FECollection fec(order, pmesh.Dimension());
ParFiniteElementSpace fes(&pmesh, &fec);
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
ParFiniteElementSpace *nodes_fes = nodes->ParFESpace();
Vector nodes_tvec;
nodes->GetTrueDofs(nodes_tvec);
///<--- dFEM setup
const IntegrationRule &ir = IntRules.Get(Geometry::SQUARE, 2 * order + 1);
QuadratureSpace qspace(pmesh, ir);
VectorQuadratureSpace coef_qspace(qspace, 1);
QuadratureFunction coef(coef_qspace);
coef.UseDevice(true);
FunctionCoefficient coeff_fc([](const Vector &p)
{ return 0.5 + p(0) + 0.125 * (p.Size() > 1 ? p(1) : 0.0); });
FillQData(fes, ir, coeff_fc, coef);
Array<int> all_domain_attr(pmesh.attributes.Max());
all_domain_attr = 1;
const std::vector<FieldDescriptor> inputs
{
{U, &fes},
{COEF, &coef_qspace},
{COORDINATES, nodes_fes}};
const std::vector<FieldDescriptor> outputs
{
{Y, &fes}};
DifferentiableOperator dop(inputs, outputs, pmesh);
Vector global_vec(1);
global_vec.UseDevice(true);
global_vec = 0.0;
real_t global_scalar = 1.0;
bool global_flag;
CubicQFWithGlobalScratch cubic_qf;
cubic_qf.SetScratch(pmesh.GetNE() * ir.GetNPoints(), {1});
cubic_qf.SetGlobalScratch(
mfem::future::make_tuple(global_flag, global_scalar, global_vec));
dop.AddDomainIntegrator<GlobalQFBackend>(
cubic_qf,
Inputs<Value<U>, Identity<COEF>, Gradient<COORDINATES>, Weight> {},
Outputs<Value<Y>> {},
ir, all_domain_attr,
Derivatives<U> {});
Vector x(fes.GetTrueVSize()), y(fes.GetTrueVSize()), dx(fes.GetTrueVSize()),
dy(fes.GetTrueVSize());
x.UseDevice(true);
y.UseDevice(true);
dx.UseDevice(true);
dy.UseDevice(true);
FunctionCoefficient input_coeff([](const Vector &p)
{ return 1.0 + p(0) + 0.25 * (p.Size() > 1 ? p(1) : 0.0); });
FillInput(fes, input_coeff, x);
ConstantCoefficient direction_coeff(1.0);
FillInput(fes, direction_coeff, dx);
y = 0.0;
dy = 0.0;
///<--- Apply the operator
MultiVector X{x, coef, nodes_tvec};
MultiVector Y{y};
dop.Mult(X, Y);
//<--- Apply derivative operator
auto dop_deriv = dop.GetDerivative(U, X);
MultiVector dY{dy};
dop_deriv->Mult(dx, dY);
///<--- Check the result against the expected output
CheckResults(fes, ir, y, dy);
}
TEST_CASE("dFEM Scratch multi-kernel persists tangents",
"[Parallel][dFEM][Scratch-MultiKernel]")
{
// This test checks that the tangent stored in the qfunction scratch shadow is preserved between split scratch updates, and persists to the final product.
// With the old implementation, the tangent of the temporary scratch vector was used internally but lost after the derivative action.
int order = 2;
int ref_levels = 1;
Mesh mesh = Mesh::MakeCartesian2D(2, 2, Element::QUADRILATERAL, true, 1.0,
1.0);
for (int l = 0; l < ref_levels; l++)
{
mesh.UniformRefinement();
}
ParMesh pmesh(MPI_COMM_WORLD, mesh);
pmesh.EnsureNodes();
H1_FECollection fec(order, pmesh.Dimension());
ParFiniteElementSpace fes(&pmesh, &fec);
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
ParFiniteElementSpace *nodes_fes = nodes->ParFESpace();
Vector nodes_tvec;
nodes->GetTrueDofs(nodes_tvec);
const IntegrationRule &ir = IntRules.Get(Geometry::SQUARE, 2 * order + 1);
QuadratureSpace qspace(pmesh, ir);
VectorQuadratureSpace coef_qspace(qspace, 1);
QuadratureFunction coef(coef_qspace);
coef.UseDevice(true);
FunctionCoefficient coeff_fc([](const Vector &p)
{ return 0.5 + p(0) + 0.125 * (p.Size() > 1 ? p(1) : 0.0); });
FillQData(fes, ir, coeff_fc, coef);
Array<int> all_domain_attr(pmesh.attributes.Max());
all_domain_attr = 1;
const std::vector<FieldDescriptor> inputs
{
{U, &fes},
{COEF, &coef_qspace},
{COORDINATES, nodes_fes}};
const std::vector<FieldDescriptor> outputs
{
{Y, &fes}};
DifferentiableOperator dop(inputs, outputs, pmesh);
CubicQFWithScratch cubic_qf;
cubic_qf.SetScratch(pmesh.GetNE() * ir.GetNPoints(), {1});
dop.AddDomainIntegrator<GlobalQFBackend>(
cubic_qf,
Inputs<Value<U>, Identity<COEF>, Gradient<COORDINATES>, Weight> {},
Outputs<Value<Y>> {},
ir, all_domain_attr,
Derivatives<U> {});
Vector x(fes.GetTrueVSize()), y(fes.GetTrueVSize()), dx(fes.GetTrueVSize());
Vector dy_action(fes.GetTrueVSize()), dy_cached(fes.GetTrueVSize());
x.UseDevice(true);
y.UseDevice(true);
dx.UseDevice(true);
dy_action.UseDevice(true);
dy_cached.UseDevice(true);
FunctionCoefficient input_coeff([](const Vector &p)
{ return 1.0 + p(0) + 0.25 * (p.Size() > 1 ? p(1) : 0.0); });
FillInput(fes, input_coeff, x);
ConstantCoefficient direction_coeff(1.0);
FillInput(fes, direction_coeff, dx);
y = 0.0;
dy_action = 0.0;
dy_cached = 0.0;
// DifferentiableOperator action
MultiVector X{x, coef, nodes_tvec};
MultiVector Y{y};
dop.Mult(X, Y);
// Derivative action (non-cached)
auto dop_deriv_action = dop.GetDerivative(U, X, false);
MultiVector dY_action{dy_action};
dop_deriv_action->Mult(dx, dY_action);
Vector y_action_check(y);
CheckResults(fes, ir, y_action_check, dy_action);
auto *stored_qf = dop.GetDerivativeActionQFunction<CubicQFWithScratch>(U);
auto *stored_qf_shadow =
dop.GetDerivativeActionShadowQFunction<CubicQFWithScratch>(U);
REQUIRE(stored_qf != nullptr);
REQUIRE(stored_qf_shadow != nullptr);
CheckScratchResults(pmesh, ir, stored_qf->GetScratchVector(0),
stored_qf_shadow->GetScratchVector(0));
// Derivative action (cached)
auto dop_deriv_cached = dop.GetDerivative(U, X, true);
MultiVector dY_cached{dy_cached};
dop_deriv_cached->Mult(dx, dY_cached);
Vector y_cached_check(y);
CheckResults(fes, ir, y_cached_check, dy_cached);
auto *stored_setup_qf = dop.GetDerivativeSetupQFunction<CubicQFWithScratch>(U);
auto *stored_setup_qf_shadow =
dop.GetDerivativeSetupShadowQFunction<CubicQFWithScratch>(U);
REQUIRE(stored_setup_qf != nullptr);
REQUIRE(stored_setup_qf_shadow != nullptr);
CheckScratchResults(pmesh, ir, stored_setup_qf->GetScratchVector(0),
stored_setup_qf_shadow->GetScratchVector(0));
}
#endif // MFEM_USE_MPI
+573 -217
View File
@@ -10,65 +10,117 @@
// CONTRIBUTING.md for details.
#include "../unit_tests.hpp"
#include "../linalg/test_same_matrices.hpp"
#include "mfem.hpp"
#include <utility>
#include "mfem.hpp"
#ifdef MFEM_USE_MPI
#include "../linalg/test_same_matrices.hpp"
#include "../../../fem/dfem/doperator.hpp"
#include "../../../fem/dfem/backends/local_qf/prelude.hpp"
#include "../../../linalg/tensor_arrays.hpp"
using namespace mfem;
using namespace mfem::future;
using mfem::future::tensor;
#ifdef MFEM_USE_ENZYME
using dscalar_t = real_t;
#else
using mfem::future::dual;
using dscalar_t = dual<real_t, real_t>;
#endif
using DOperator = DifferentiableOperator;
template <int DIM> struct Diffusion
// ────────────────────────────────────────────────────────────────────────────
template <int DIM>
struct Diffusion
{
using dvecd_t = tensor<dscalar_t, DIM>;
using matd_t = tensor<real_t, DIM, DIM>;
struct MFApply
{
MFEM_HOST_DEVICE inline auto operator()(const dvecd_t &dudxi,
const real_t &rho,
const matd_t &J,
const real_t &w) const
MFEM_HOST_DEVICE inline auto operator()(
const dvecd_t &dudxi,
const matd_t &J,
const real_t &w,
dvecd_t &dvdxi) const
{
const auto invJ = inv(J), TinJ = transpose(invJ);
return tuple{ (dudxi * invJ) * TinJ * det(J) * w * rho };
const auto invJ = inv(J);
const auto invJt = transpose(invJ);
dvdxi = (dudxi * invJ) * invJt * det(J) * w;
}
};
struct PASetup
{
MFEM_HOST_DEVICE inline auto operator()(const real_t u,
const real_t &rho,
const matd_t &J,
const real_t &w) const
MFEM_HOST_DEVICE inline auto operator()(
const matd_t &J,
const real_t &w,
matd_t &qdata) const
{
return tuple{ inv(J) * transpose(inv(J)) * det(J) * w * rho };
qdata = inv(J) * transpose(inv(J)) * det(J) * w;
}
};
struct PAApply
{
MFEM_HOST_DEVICE inline auto operator()(const dvecd_t &dudxi,
const matd_t &q) const
MFEM_HOST_DEVICE inline auto operator()(
const dvecd_t &dudxi,
const matd_t &qdata,
dvecd_t &dvdxi) const
{
return tuple{ q * dudxi };
dvdxi = qdata * dudxi;
};
};
};
// ────────────────────────────────────────────────────────────────────────────
// Global-QF diffusion. Used to exercise the GlobalQFBackend derivative cache
// with residual_size_on_qp = DIM*DIM > 1; the other GlobalQFBackend tests are
// all scalar Value-in/Value-out, where residual_size_on_qp == 1 and the cache
// index layout is degenerate.
template <int DIM>
struct GlobalDiffusion
{
struct MFApply
{
void operator()(tensor_array<const dscalar_t, DIM> &dudxi,
tensor_array<const real_t, DIM, DIM> &J,
tensor_array<const real_t> &w,
tensor_array<dscalar_t, DIM> &dvdxi) const
{
mfem::forall(w.size(), [=] MFEM_HOST_DEVICE(int q)
{
const auto invJ = inv(J(q));
dvdxi(q) = (dudxi(q) * invJ) * transpose(invJ) * det(J(q)) * w(q);
});
}
};
};
// ────────────────────────────────────────────────────────────────────────────
template <int DIM> struct VectorDiffusion
{
using dmatd_t = tensor<dscalar_t, DIM, DIM>;
using matd_t = tensor<real_t, DIM, DIM>;
struct MFApply
{
MFEM_HOST_DEVICE inline auto operator()(
const dmatd_t &dudxi,
const matd_t &J,
const real_t &w,
dmatd_t &dvdxi) const
{
const auto invJ = inv(J);
const auto invJt = transpose(invJ);
dvdxi = (dudxi * invJ) * invJt * det(J) * w;
}
};
};
// ────────────────────────────────────────────────────────────────────────────
template <int DIM, typename QFBackend = LocalQFBackend>
void diffusion(const char *filename, int p)
{
CAPTURE(filename, DIM, p);
@@ -79,9 +131,10 @@ void diffusion(const char *filename, int p)
pmesh.EnsureNodes();
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
p = std::max(p, pmesh.GetNodalFESpace()->GetMaxElementOrder());
smesh.Clear();
p = std::max(p, pmesh.GetNodalFESpace()->GetMaxElementOrder());
Array<int> all_domain_attr;
if (pmesh.attributes.Size() > 0)
{
@@ -89,248 +142,551 @@ void diffusion(const char *filename, int p)
all_domain_attr = 1;
}
H1_FECollection fec(p, DIM);
ParFiniteElementSpace pfes(&pmesh, &fec);
ParFiniteElementSpace *mfes = nodes->ParFESpace();
const auto *ir = &IntRules.Get(pmesh.GetTypicalElementGeometry(), 2 * p);
const int NE = pfes.GetNE(), d1d(p + 1), q = 2 * p;
const auto *ir = &IntRules.Get(pmesh.GetTypicalElementGeometry(), q);
const int q1d(IntRules.Get(Geometry::SEGMENT, ir->GetOrder()).GetNPoints());
MFEM_VERIFY(d1d <= q1d, "q1d should be >= d1d");
H1_FECollection fec(p, DIM);
ParGridFunction x(&pfes), y(&pfes), z(&pfes);
Vector X(pfes.GetTrueVSize()), Y(pfes.GetTrueVSize()), Z(pfes.GetTrueVSize());
static constexpr int U = 0, Coords = 1;
X.Randomize(1);
x.SetFromTrueDofs(X);
auto rho = [](const Vector &xyz)
SECTION("Scalar")
{
const real_t x = xyz(0), y = xyz(1), z = DIM == 3 ? xyz(2) : 0.0;
real_t r = M_PI * pow(x, 2);
if (DIM >= 2) { r += pow(y, 3); }
if (DIM >= 3) { r += pow(z, 4); }
return r;
};
FunctionCoefficient rho_coeff(rho);
ParFiniteElementSpace pfes(&pmesh, &fec);
ParBilinearForm blf_fa(&pfes);
blf_fa.AddDomainIntegrator(new DiffusionIntegrator(rho_coeff, ir));
blf_fa.SetAssemblyLevel(AssemblyLevel::FULL);
blf_fa.Assemble();
blf_fa.Finalize();
ParGridFunction x(&pfes), y(&pfes), z(&pfes);
Vector xtvec(pfes.GetTrueVSize()), ytvec(pfes.GetTrueVSize()),
ztvec(pfes.GetTrueVSize());
QuadratureSpace qs(pmesh, *ir);
CoefficientVector rho_coeff_cv(rho_coeff, qs);
MFEM_VERIFY(rho_coeff_cv.GetVDim() == 1, "Coefficient should be scalar");
MFEM_VERIFY(rho_coeff_cv.Size() == q1d * q1d * (DIM == 3 ? q1d : 1) * NE, "");
xtvec.Randomize(1);
x.SetFromTrueDofs(xtvec);
UniformParameterSpace rho_ps(pmesh, *ir, 1);
ParBilinearForm blf_fa(&pfes);
blf_fa.AddDomainIntegrator(new DiffusionIntegrator(ir));
blf_fa.SetAssemblyLevel(AssemblyLevel::FULL);
blf_fa.Assemble();
blf_fa.Finalize();
static constexpr int U = 0, Coords = 1, Rho = 3;
const auto sol = std::vector{ FieldDescriptor{ U, &pfes } };
const auto in_fds = std::vector
{
FieldDescriptor{ U, &pfes },
FieldDescriptor{ Coords, mfes }
};
const auto out_fds = std::vector{ FieldDescriptor{ U, &pfes } };
SECTION("action")
{
DOperator dop_mf(sol, {{Rho, &rho_ps}, {Coords, mfes}}, pmesh);
typename Diffusion<DIM>::MFApply mf_apply_qf;
dop_mf.AddDomainIntegrator(mf_apply_qf,
tuple{ Gradient<U>{}, Identity<Rho>{},
Gradient<Coords>{}, Weight{} },
tuple{ Gradient<U>{} }, *ir,
all_domain_attr);
dop_mf.SetParameters({ &rho_coeff_cv, nodes });
SECTION("Scalar Action")
{
DifferentiableOperator dop_mf(in_fds, out_fds, pmesh);
typename Diffusion<DIM>::MFApply mf_apply_qf;
dop_mf.AddDomainIntegrator<QFBackend>(
mf_apply_qf,
Inputs<Gradient<U>, Gradient<Coords>, Weight> {},
Outputs<Gradient<U>> {},
*ir, all_domain_attr);
pfes.GetRestrictionMatrix()->Mult(x, X);
dop_mf.Mult(X, Z);
Vector nodestv;
nodes->GetTrueDofs(nodestv);
blf_fa.Mult(x, y);
pfes.GetProlongationMatrix()->MultTranspose(y, Y);
Y -= Z;
pfes.GetRestrictionMatrix()->Mult(x, xtvec);
real_t norm_global = 0.0;
real_t norm_local = Y.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
MultiVector X{xtvec, nodestv};
MultiVector Z{ztvec};
REQUIRE(norm_global == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
dop_mf.Mult(X, Z);
blf_fa.Mult(x, y);
pfes.GetProlongationMatrix()->MultTranspose(y, ytvec);
ytvec -= ztvec;
real_t norm_global = 0.0;
real_t norm_local = ytvec.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
REQUIRE(norm_global == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
SECTION("Scalar Action Partial Assembly")
{
static constexpr int QData = 2;
QuadratureSpace qspace(pmesh, *ir);
VectorQuadratureSpace qspace_vec(qspace, DIM * DIM);
QuadratureFunction qd(qspace_vec);
DifferentiableOperator setupPAData(
{
{Coords, mfes}
},
{
{QData, &qspace_vec}
}, pmesh);
typename Diffusion<DIM>::PASetup pa_setup_qf;
setupPAData.AddDomainIntegrator<QFBackend>(
pa_setup_qf,
Inputs<Gradient<Coords>, Weight> {},
Outputs<Identity<QData>> {},
*ir, all_domain_attr);
{
Vector nodestv;
nodes->GetTrueDofs(nodestv);
MultiVector X{nodestv};
MultiVector Y{qd};
setupPAData.Mult(X, Y);
}
DifferentiableOperator applyPAData(
{
{U, &pfes}, {QData, &qspace_vec}
},
{
{U, &pfes}
}, pmesh);
typename Diffusion<DIM>::PAApply pa_apply_qf;
applyPAData.AddDomainIntegrator<QFBackend>(
pa_apply_qf,
Inputs<Gradient<U>, Identity<QData>> {},
Outputs<Gradient<U>> {},
*ir, all_domain_attr);
{
pfes.GetRestrictionMatrix()->Mult(x, xtvec);
MultiVector X{xtvec, qd};
MultiVector Z{ztvec};
applyPAData.Mult(X, Z);
}
blf_fa.Mult(x, y);
pfes.GetProlongationMatrix()->MultTranspose(y, ytvec);
ytvec -= ztvec;
real_t norm_global = 0.0;
real_t norm_local = ytvec.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
REQUIRE(norm_global == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
SECTION("Scalar Action Linearized")
{
DifferentiableOperator dop_mf(in_fds, out_fds, pmesh);
typename Diffusion<DIM>::MFApply mf_apply_qf;
dop_mf.AddDomainIntegrator<QFBackend>(
mf_apply_qf,
Inputs<Gradient<U>, Gradient<Coords>, Weight> {},
Outputs<Gradient<U>> {},
*ir, all_domain_attr,
Derivatives<U> {});
pfes.GetRestrictionMatrix()->Mult(x, xtvec);
Vector nodestv;
nodes->GetTrueDofs(nodestv);
MultiVector X{xtvec, nodestv};
MultiVector Z{ztvec};
auto ddop = dop_mf.GetDerivative(U, X);
// Randomize again s.t. the PA setup like cache can't
// trivially succeed by caching one direction only.
xtvec.Randomize(567);
x.SetFromTrueDofs(xtvec);
Vector dztvec(ztvec.Size());
MultiVector DZ{dztvec};
ddop->Mult(X[0], DZ);
blf_fa.Mult(x, y);
pfes.GetProlongationMatrix()->MultTranspose(y, ytvec);
ytvec -= dztvec;
real_t norm_global = 0.0;
real_t norm_local = ytvec.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
REQUIRE(norm_global == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
SECTION("Scalar SparseMatrix")
{
DifferentiableOperator dop_mf(in_fds, out_fds, pmesh);
typename Diffusion<DIM>::MFApply mf_apply_qf;
dop_mf.AddDomainIntegrator<QFBackend>(
mf_apply_qf,
Inputs<Gradient<U>, Gradient<Coords>, Weight> {},
Outputs<Gradient<U>> {},
*ir, all_domain_attr,
Derivatives<U> {});
pfes.GetRestrictionMatrix()->Mult(x, xtvec);
Vector nodestv;
nodes->GetTrueDofs(nodestv);
MultiVector X{xtvec, nodestv};
auto dRdU = dop_mf.GetDerivative(U, X);
SparseMatrix *A = nullptr;
dRdU->Assemble(A);
TestSameMatrices(*A, blf_fa.SpMat());
delete A;
MPI_Barrier(MPI_COMM_WORLD);
}
SECTION("Scalar Assemble Diagonal")
{
DifferentiableOperator dop_mf(in_fds, out_fds, pmesh);
typename Diffusion<DIM>::MFApply mf_apply_qf;
dop_mf.AddDomainIntegrator<QFBackend>(
mf_apply_qf,
Inputs<Gradient<U>, Gradient<Coords>, Weight> {},
Outputs<Gradient<U>> {},
*ir, all_domain_attr,
Derivatives<U> {});
pfes.GetRestrictionMatrix()->Mult(x, xtvec);
Vector nodestv;
nodes->GetTrueDofs(nodestv);
MultiVector X{xtvec, nodestv};
auto dRdU = dop_mf.GetDerivative(U, X);
Vector dfem_diagonal(pfes.GetTrueVSize());
dRdU->AssembleDiagonal(dfem_diagonal);
Vector mfem_diagonal(pfes.GetTrueVSize());
blf_fa.AssembleDiagonal(mfem_diagonal);
dfem_diagonal -= mfem_diagonal;
real_t norm_global = 0.0;
real_t norm_local = dfem_diagonal.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
REQUIRE(norm_global == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
}
SECTION("action partial assembly")
{
static constexpr int QData = 2;
UniformParameterSpace qd_ps(pmesh, *ir, DIM * DIM);
ParameterFunction qdata(qd_ps);
qdata.UseDevice(true);
DOperator dSetup(sol, {{Rho, &rho_ps}, {Coords, mfes}, {QData, &qd_ps}}, pmesh);
typename Diffusion<DIM>::PASetup pa_setup_qf;
dSetup.AddDomainIntegrator(
pa_setup_qf,
tuple{ Value<U>{}, Identity<Rho>{}, Gradient<Coords>{}, Weight{} },
tuple{ Identity<QData>{} }, *ir, all_domain_attr);
dSetup.SetParameters({ &rho_coeff_cv, nodes, &qdata });
pfes.GetRestrictionMatrix()->Mult(x, X);
dSetup.Mult(X, qdata);
DOperator dop_pa(sol, { { QData, &qd_ps } }, pmesh);
typename Diffusion<DIM>::PAApply pa_apply_qf;
dop_pa.AddDomainIntegrator(pa_apply_qf,
tuple{ Gradient<U>{}, Identity<QData>{} },
tuple{ Gradient<U>{} },
*ir, all_domain_attr);
dop_pa.SetParameters({ &qdata });
pfes.GetRestrictionMatrix()->Mult(x, X);
dop_pa.Mult(X, Z);
blf_fa.Mult(x, y);
pfes.GetProlongationMatrix()->MultTranspose(y, Y);
Y -= Z;
real_t norm_global = 0.0;
real_t norm_local = Y.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
REQUIRE(norm_global == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
SECTION("action linearized")
{
DOperator dop_mf(sol, {{Rho, &rho_ps}, {Coords, mfes}}, pmesh);
typename Diffusion<DIM>::MFApply mf_apply_qf;
auto derivatives = std::integer_sequence<size_t, U> {};
dop_mf.AddDomainIntegrator(mf_apply_qf,
tuple{ Gradient<U>{}, Identity<Rho>{},
Gradient<Coords>{}, Weight{} },
tuple{ Gradient<U>{} }, *ir,
all_domain_attr, derivatives);
dop_mf.SetParameters({ &rho_coeff_cv, nodes });
auto dRdU = dop_mf.GetDerivative(U, {&x}, {&rho_coeff_cv, nodes});
pfes.GetRestrictionMatrix()->Mult(x, X);
dRdU->Mult(X, Z);
blf_fa.Mult(x, y);
pfes.GetProlongationMatrix()->MultTranspose(y, Y);
Y -= Z;
real_t norm_global = 0.0;
real_t norm_local = Y.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
REQUIRE(norm_global == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
SECTION("action vector")
SECTION("Vector")
{
ParFiniteElementSpace vpfes(&pmesh, &fec, DIM);
ParGridFunction vx(&vpfes), vy(&vpfes);
Vector vX(vpfes.GetTrueVSize()), vY(vpfes.GetTrueVSize()),
vZ(vpfes.GetTrueVSize());
vX.Randomize(1);
vx.SetFromTrueDofs(vX);
SECTION("Vector Diffusion Action")
{
const auto vsol = std::vector{ FieldDescriptor{ U, &vpfes } };
DOperator dop_mf(vsol, {{Coords, mfes}}, pmesh);
const auto mf_vector_diffusion_qf =
[] MFEM_HOST_DEVICE (const tensor<dscalar_t, DIM, DIM> &dudxi,
const tensor<real_t, DIM, DIM> &J,
const real_t &w)
vX.Randomize(1);
vx.SetFromTrueDofs(vX);
DifferentiableOperator dop_mf(
{
const auto invJ = inv(J), TinJ = transpose(invJ);
return tuple{ (dudxi * invJ) * TinJ * det(J) * w };
};
dop_mf.AddDomainIntegrator(mf_vector_diffusion_qf,
tuple{ Gradient<U>{}, Gradient<Coords>{}, Weight{} },
tuple{ Gradient<U>{} },
*ir, all_domain_attr);
dop_mf.SetParameters({ nodes });
vpfes.GetRestrictionMatrix()->Mult(vx, vX), dop_mf.Mult(vX, vZ);
}
{
ConstantCoefficient one(1.0);
{U, &vpfes},
{Coords, mfes},
},
{
{U, &vpfes}
}, pmesh);
typename VectorDiffusion<DIM>::MFApply mf_vector_diffusion_qf;
dop_mf.AddDomainIntegrator<QFBackend>(
mf_vector_diffusion_qf,
Inputs<Gradient<U>, Gradient<Coords>, Weight> {},
Outputs<Gradient<U>> {},
*ir, all_domain_attr);
Vector nodestv;
nodes->GetTrueDofs(nodestv);
MultiVector X{vX, nodestv};
MultiVector Z{vZ};
dop_mf.Mult(X, Z);
ParBilinearForm vblf_fa(&vpfes);
vblf_fa.AddDomainIntegrator(new VectorDiffusionIntegrator(one, ir));
vblf_fa.AddDomainIntegrator(new VectorDiffusionIntegrator(ir));
vblf_fa.SetAssemblyLevel(AssemblyLevel::LEGACYFULL);
vblf_fa.Assemble();
vblf_fa.Finalize();
vblf_fa.Mult(vx, vy);
vpfes.GetProlongationMatrix()->MultTranspose(vy, vY);
}
vY -= vZ;
real_t norm_global = 0.0, norm_local = vY.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
// Account for ill conditioning of the RT mesh
if (std::string(filename).compare("../../data/rt-2d-q3.mesh") == 0)
{
REQUIRE(norm_global == MFEM_Approx(0.0, 5e-12, 5e-12));
}
else
{
vY -= vZ;
real_t norm_global = 0.0;
real_t norm_local = vY.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
REQUIRE(norm_global == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
MPI_Barrier(MPI_COMM_WORLD);
SECTION("Vector Diffusion Action Linearized")
{
vX.Randomize(1);
vx.SetFromTrueDofs(vX);
DifferentiableOperator dop_mf(
{
{U, &vpfes},
{Coords, mfes},
},
{
{U, &vpfes}
}, pmesh);
typename VectorDiffusion<DIM>::MFApply mf_vector_diffusion_qf;
dop_mf.AddDomainIntegrator<QFBackend>(
mf_vector_diffusion_qf,
Inputs<Gradient<U>, Gradient<Coords>, Weight> {},
Outputs<Gradient<U>> {},
*ir, all_domain_attr,
Derivatives<U> {});
Vector nodestv;
nodes->GetTrueDofs(nodestv);
MultiVector X{vX, nodestv};
const auto ddop = dop_mf.GetDerivative(U, X);
MultiVector Z{vZ};
ddop->Mult(vX, Z);
ParBilinearForm vblf_fa(&vpfes);
vblf_fa.AddDomainIntegrator(new VectorDiffusionIntegrator(ir));
vblf_fa.SetAssemblyLevel(AssemblyLevel::LEGACYFULL);
vblf_fa.Assemble();
vblf_fa.Finalize();
vblf_fa.Mult(vx, vy);
vpfes.GetProlongationMatrix()->MultTranspose(vy, vY);
vY -= vZ;
real_t norm_global = 0.0;
real_t norm_local = vY.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
REQUIRE(norm_global == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
SECTION("Vector SparseMatrix")
{
vX.Randomize(1);
vx.SetFromTrueDofs(vX);
DifferentiableOperator dop_mf(
{
{U, &vpfes},
{Coords, mfes},
},
{
{U, &vpfes}
}, pmesh);
typename VectorDiffusion<DIM>::MFApply mf_vector_diffusion_qf;
dop_mf.AddDomainIntegrator<QFBackend>(
mf_vector_diffusion_qf,
Inputs<Gradient<U>, Gradient<Coords>, Weight> {},
Outputs<Gradient<U>> {},
*ir, all_domain_attr,
Derivatives<U> {});
Vector nodestv;
nodes->GetTrueDofs(nodestv);
MultiVector X{vX, nodestv};
const auto ddop = dop_mf.GetDerivative(U, X);
MultiVector Z{vZ};
ddop->Mult(vX, Z);
ParBilinearForm vblf_fa(&vpfes);
vblf_fa.AddDomainIntegrator(new VectorDiffusionIntegrator(ir));
vblf_fa.SetAssemblyLevel(AssemblyLevel::LEGACYFULL);
vblf_fa.Assemble();
vblf_fa.Finalize();
SparseMatrix *A = nullptr;
ddop->Assemble(A);
TestSameMatrices(*A, vblf_fa.SpMat());
delete A;
MPI_Barrier(MPI_COMM_WORLD);
}
}
}
// ────────────────────────────────────────────────────────────────────────────
TEST_CASE("dFEM Diffusion 2D", "[Parallel][dFEM][GPU]")
{
const auto p = GenAll({1}, {2, 3});
const auto meshs = { "../../data/inline-quad.mesh" };
const auto extra = { "../../data/star.mesh",
"../../data/star-q3.mesh",
"../../data/rt-2d-q3.mesh",
"../../data/periodic-square.mesh"
};
diffusion<2>(GenAll(meshs, extra), p);
}
// ────────────────────────────────────────────────────────────────────────────
// The GlobalQFBackend writes the derivative qp_cache, but Assemble and
// AssembleDiagonal are served by the LocalQF implementations (see
// GlobalQFBackend::MakeDerivativeAssemble*), so writer and readers live in
// different backends and must agree on the cache layout.
template <int DIM>
void diffusion_globalqf(const char *filename, int p)
{
CAPTURE(filename, DIM, p);
Mesh smesh(filename);
ParMesh pmesh(MPI_COMM_WORLD, smesh);
MFEM_VERIFY(pmesh.Dimension() == DIM, "Mesh dimension mismatch");
pmesh.EnsureNodes();
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
smesh.Clear();
p = std::max(p, pmesh.GetNodalFESpace()->GetMaxElementOrder());
Array<int> all_domain_attr;
if (pmesh.attributes.Size() > 0)
{
all_domain_attr.SetSize(pmesh.attributes.Max());
all_domain_attr = 1;
}
SECTION("spmat")
{
DOperator dop_mf(sol, {{Rho, &rho_ps}, {Coords, mfes}}, pmesh);
typename Diffusion<DIM>::MFApply mf_apply_qf;
auto derivatives = std::integer_sequence<size_t, U> {};
dop_mf.AddDomainIntegrator(mf_apply_qf,
tuple{ Gradient<U>{}, Identity<Rho>{},
Gradient<Coords>{}, Weight{} },
tuple{ Gradient<U>{} }, *ir,
all_domain_attr, derivatives);
dop_mf.SetParameters({ &rho_coeff_cv, nodes });
auto dRdU = dop_mf.GetDerivative(U, {&x}, {&rho_coeff_cv, nodes});
ParFiniteElementSpace *mfes = nodes->ParFESpace();
const auto *ir = &IntRules.Get(pmesh.GetTypicalElementGeometry(), 2 * p);
H1_FECollection fec(p, DIM);
ParFiniteElementSpace pfes(&pmesh, &fec);
static constexpr int U = 0, Coords = 1;
ParGridFunction x(&pfes), y(&pfes);
Vector xtvec(pfes.GetTrueVSize()), ytvec(pfes.GetTrueVSize()),
ztvec(pfes.GetTrueVSize());
xtvec.Randomize(1);
x.SetFromTrueDofs(xtvec);
ParBilinearForm blf_fa(&pfes);
blf_fa.AddDomainIntegrator(new DiffusionIntegrator(ir));
blf_fa.SetAssemblyLevel(AssemblyLevel::FULL);
blf_fa.Assemble();
blf_fa.Finalize();
const auto in_fds = std::vector
{
FieldDescriptor{ U, &pfes },
FieldDescriptor{ Coords, mfes }
};
const auto out_fds = std::vector{ FieldDescriptor{ U, &pfes } };
DifferentiableOperator dop(in_fds, out_fds, pmesh);
typename GlobalDiffusion<DIM>::MFApply global_qfn;
dop.AddDomainIntegrator<GlobalQFBackend>(
global_qfn,
Inputs<Gradient<U>, Gradient<Coords>, Weight> {},
Outputs<Gradient<U>> {},
*ir, all_domain_attr,
Derivatives<U> {});
Vector nodestv;
nodes->GetTrueDofs(nodestv);
pfes.GetRestrictionMatrix()->Mult(x, xtvec);
MultiVector X{ xtvec, nodestv };
auto dRdU = dop.GetDerivative(U, X);
const auto max_error = [&](const Vector &v)
{
real_t norm_global = 0.0, norm_local = v.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
return norm_global;
};
// GlobalQF setup writer -> GlobalQF apply reader
{
MultiVector Z{ ztvec };
dRdU->Mult(xtvec, Z);
blf_fa.Mult(x, y);
pfes.GetProlongationMatrix()->MultTranspose(y, ytvec);
ytvec -= ztvec;
REQUIRE(max_error(ytvec) == MFEM_Approx(0.0));
}
// GlobalQF setup writer -> GlobalQF apply-transpose reader
{
Vector wtvec(pfes.GetTrueVSize());
wtvec.Randomize(0x9e3779b9);
MultiVector W{ wtvec }, Z{ ztvec };
dRdU->MultTranspose(W, Z);
ParGridFunction w(&pfes);
w.SetFromTrueDofs(wtvec);
blf_fa.MultTranspose(w, y);
pfes.GetProlongationMatrix()->MultTranspose(y, ytvec);
ytvec -= ztvec;
REQUIRE(max_error(ytvec) == MFEM_Approx(0.0));
}
// GlobalQF setup writer -> LocalQF assemble reader
{
SparseMatrix *A = nullptr;
dRdU->Assemble(A);
TestSameMatrices(*A, blf_fa.SpMat());
delete A;
}
// GlobalQF setup writer -> LocalQF assemble-diagonal reader
{
Vector dfem_diag(pfes.GetTrueVSize()), mfem_diag(pfes.GetTrueVSize());
dRdU->AssembleDiagonal(dfem_diag);
blf_fa.AssembleDiagonal(mfem_diag);
dfem_diag -= mfem_diag;
REQUIRE(max_error(dfem_diag) == MFEM_Approx(0.0));
}
MPI_Barrier(MPI_COMM_WORLD);
}
TEST_CASE("dFEM Diffusion", "[Parallel][dFEM][GPU]")
// ────────────────────────────────────────────────────────────────────────────
TEST_CASE("dFEM Diffusion GlobalQF cache 2D", "[Parallel][dFEM]")
{
const bool all_tests = launch_all_non_regression_tests;
const auto p = !all_tests ? 2 : GENERATE(1, 2, 3);
SECTION("2d")
if constexpr (!mfem_use_gpu)
{
const auto filename2d =
GENERATE(
"../../data/star.mesh",
"../../data/star-q3.mesh",
"../../data/rt-2d-q3.mesh",
"../../data/inline-quad.mesh",
"../../data/periodic-square.mesh"
);
diffusion<2>(filename2d, p);
const auto p = GenAll({1}, {2, 3});
const auto meshs = { "../../data/inline-quad.mesh" };
const auto extra = { "../../data/star.mesh" };
diffusion_globalqf<2>(GenAll(meshs, extra), p);
}
}
SECTION("3d")
// ────────────────────────────────────────────────────────────────────────────
TEST_CASE("dFEM Diffusion GlobalQF cache 3D", "[Parallel][dFEM]")
{
if constexpr (!mfem_use_gpu)
{
const auto filename3d =
GENERATE(
"../../data/fichera.mesh",
"../../data/fichera-q3.mesh",
"../../data/inline-hex.mesh",
"../../data/toroid-hex.mesh",
"../../data/periodic-cube.mesh"
);
diffusion<3>(filename3d, p);
const auto p = GenAll({1}, {2, 3});
const auto meshs = { "../../data/inline-hex.mesh" };
const auto extra = { "../../data/fichera.mesh" };
diffusion_globalqf<3>(GenAll(meshs, extra), p);
}
}
// ────────────────────────────────────────────────────────────────────────────
TEST_CASE("dFEM Diffusion 3D", "[Parallel][dFEM][GPU]")
{
const auto p = GenAll({1}, {2, 3});
const auto meshs = { "../../data/inline-hex.mesh" };
const auto extra = { "../../data/fichera.mesh",
"../../data/fichera-q3.mesh",
"../../data/toroid-hex.mesh",
"../../data/periodic-cube.mesh"
};
diffusion<3>(GenAll(meshs, extra), p);
}
#endif // MFEM_USE_MPI
+122 -67
View File
@@ -10,18 +10,20 @@
// CONTRIBUTING.md for details.
#include "../unit_tests.hpp"
#include "mfem.hpp"
#ifdef MFEM_USE_MPI
#include "../../../fem/dfem/doperator.hpp"
#include "../../../fem/dfem/backends/local_qf/prelude.hpp"
using namespace mfem;
using namespace mfem::future;
using mfem::future::tensor;
#ifdef MFEM_USE_ENZYME
using dscalar_t = real_t;
#else
using mfem::future::dual;
using dscalar_t = dual<real_t, real_t>;
#endif
@@ -50,69 +52,123 @@ void vectordivergence(const char *filename, int p)
ParFiniteElementSpace psfes(&pmesh, &fec);
ParFiniteElementSpace pvfes(&pmesh, &fec, DIM);
const int d1d(p + 1), q = 3 * p + 1;
const int q = 3 * p + 1;
const auto *ir = &IntRules.Get(pmesh.GetTypicalElementGeometry(), q);
const int q1d(IntRules.Get(Geometry::SEGMENT, ir->GetOrder()).GetNPoints());
MFEM_VERIFY(d1d <= q1d, "q1d should be >= d1d");
ParGridFunction vx(&pvfes);
ParGridFunction sy(&psfes), sz(&psfes);
Vector vX(pvfes.GetTrueVSize());
Vector sY(psfes.GetTrueVSize()), sZ(psfes.GetTrueVSize());
ParGridFunction xv(&pvfes);
ParGridFunction ys(&psfes), sz(&psfes);
Vector Xv(pvfes.GetTrueVSize());
Vector Ys(psfes.GetTrueVSize()), Zs(psfes.GetTrueVSize());
vX.Randomize(1), vx.SetFromTrueDofs(vX);
Xv.Randomize(1), xv.SetFromTrueDofs(Xv);
MixedBilinearForm mblf_fa(&pvfes, &psfes);
mblf_fa.AddDomainIntegrator(new VectorDivergenceIntegrator);
mblf_fa.Assemble(), mblf_fa.Finalize();
mblf_fa.Mult(vx, sy);
mblf_fa.Assemble();
mblf_fa.Finalize();
mblf_fa.Mult(xv, ys);
MixedBilinearForm mblf_pa(&pvfes, &psfes);
mblf_pa.AddDomainIntegrator(new VectorDivergenceIntegrator);
mblf_pa.SetAssemblyLevel(AssemblyLevel::PARTIAL);
mblf_pa.Assemble();
mblf_pa.Mult(vx, sz);
sy -= sz;
REQUIRE(sy.Normlinf() == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
static constexpr int P = 0, V = 1, Coords = 2;
ParFiniteElementSpace *mfes = nodes->ParFESpace();
const auto inputs = std::vector
{
static constexpr int P = 0, V = 1, Coords = 2;
ParFiniteElementSpace *mfes = nodes->ParFESpace();
FieldDescriptor{V, &pvfes},
FieldDescriptor{Coords, mfes}
};
const auto outputs = std::vector
{
FieldDescriptor{P, &psfes}
};
const auto solutions = std::vector{ FieldDescriptor{ P, &psfes } };
const auto parameters = std::vector
{
FieldDescriptor{ V, &pvfes },
FieldDescriptor{ Coords, mfes }
};
DifferentiableOperator dop_mf(inputs, outputs, pmesh);
DifferentiableOperator dop_mf(solutions, parameters, pmesh);
const auto mf_vector_divergence_qf =
[] MFEM_HOST_DEVICE(const tensor<dscalar_t, DIM, DIM> &dudxi,
const tensor<real_t, DIM, DIM> &J,
const real_t &w,
dscalar_t &v)
{
const auto invJ = inv(J);
const auto dudx = dudxi * invJ;
v = tr(dudx) * det(J) * w;
};
const auto mf_vector_divergence_qf =
[] MFEM_HOST_DEVICE(const tensor<dscalar_t, DIM, DIM> &dudxi,
const tensor<mfem::real_t, DIM, DIM> &J,
const real_t &w)
{
const auto invJ = inv(J);
const auto dudx = dudxi * invJ;
return tuple{ tr(dudx) * det(J) * w };
};
const auto derivatives = std::integer_sequence<size_t, V> {};
dop_mf.AddDomainIntegrator<LocalQFBackend>(
mf_vector_divergence_qf,
tuple{Gradient<V>{}, Gradient<Coords>{}, Weight{}},
tuple{Value<P>{}},
*ir, all_domain_attr, derivatives);
dop_mf.AddDomainIntegrator(mf_vector_divergence_qf,
tuple{ Gradient<V>{}, Gradient<Coords>{}, Weight{} },
tuple{ Value<P>{} },
*ir, all_domain_attr);
SECTION("Action")
{
Vector nodestv;
nodes->GetTrueDofs(nodestv);
MultiVector X{Xv, nodestv};
MultiVector Z{Zs};
dop_mf.Mult(X, Z);
dop_mf.SetParameters({ &vx, nodes });
Vector unused(pvfes.GetTrueVSize());
dop_mf.Mult(unused, sZ);
mblf_fa.Mult(xv, ys);
psfes.GetProlongationMatrix()->MultTranspose(ys, Ys);
mblf_fa.Mult(vx, sy);
psfes.GetProlongationMatrix()->MultTranspose(sy, sY);
Ys -= Zs;
real_t norm_global = 0.0;
real_t norm_local = Ys.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
REQUIRE(norm_global == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
sY -= sZ;
real_t norm_global = M_PI, norm_local = sY.Normlinf();
SECTION("Derivative Action")
{
Vector nodestv;
nodes->GetTrueDofs(nodestv);
MultiVector X{Xv, nodestv};
MultiVector Z{Zs};
auto dRdV = dop_mf.GetDerivative(V, X);
dRdV->Mult(X[0], Z);
mblf_fa.Mult(xv, ys);
psfes.GetProlongationMatrix()->MultTranspose(ys, Ys);
Ys -= Zs;
real_t norm_global = 0.0;
real_t norm_local = Ys.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
REQUIRE(norm_global == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
SECTION("Derivative Transpose Action")
{
Vector nodestv;
nodes->GetTrueDofs(nodestv);
// Build cache with full primal state
MultiVector state{Xv, nodestv};
auto dRdV = dop_mf.GetDerivative(V, state);
// Direction in output (test) T-space: use Ys computed from mblf_fa.
psfes.GetProlongationMatrix()->MultTranspose(ys, Ys);
MultiVector direction{Ys};
// Result in derivative (trial) T-space.
Vector result_v(pvfes.GetTrueVSize());
result_v = 0.0;
MultiVector result{result_v};
dRdV->MultTranspose(direction, result);
psfes.GetProlongationMatrix()->Mult(Ys, ys);
mblf_fa.MultTranspose(ys, xv);
Vector ref_v(pvfes.GetTrueVSize());
pvfes.GetProlongationMatrix()->MultTranspose(xv, ref_v);
result_v -= ref_v;
real_t norm_global = 0.0;
real_t norm_local = result_v.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
REQUIRE(norm_global == MFEM_Approx(0.0));
@@ -120,32 +176,31 @@ void vectordivergence(const char *filename, int p)
}
}
TEST_CASE("dFEM VectorDivergence", "[Parallel][dFEM]")
// ────────────────────────────────────────────────────────────────────────────
TEST_CASE("dFEM VectorDivergence", "[Parallel][dFEM][GPU]")
{
const bool all_tests = launch_all_non_regression_tests;
const auto p = !all_tests ? 2 : GENERATE(1, 2, 3);
const auto p = GenAll({1}, {2, 3});
SECTION("2D p=" + std::to_string(p))
{
const auto filename =
GENERATE("../../data/star.mesh",
"../../data/star-q3.mesh",
"../../data/rt-2d-q3.mesh",
"../../data/inline-quad.mesh",
"../../data/periodic-square.mesh");
vectordivergence<2>(filename, p);
const auto meshs = { "../../data/inline-quad.mesh" };
const auto extra = { "../../data/star.mesh",
"../../data/star-q3.mesh",
"../../data/rt-2d-q3.mesh",
"../../data/periodic-square.mesh"
};
vectordivergence<2>(GenAll(meshs, extra), p);
}
SECTION("3D p=" + std::to_string(p))
{
const auto filename =
GENERATE("../../data/fichera.mesh",
"../../data/fichera-q3.mesh",
"../../data/inline-hex.mesh",
"../../data/toroid-hex.mesh",
"../../data/periodic-cube.mesh");
vectordivergence<3>(filename, p);
const auto meshs = { "../../data/inline-hex.mesh" };
const auto extra = { "../../data/fichera.mesh",
"../../data/fichera-q3.mesh",
"../../data/toroid-hex.mesh",
"../../data/periodic-cube.mesh"
};
vectordivergence<3>(GenAll(meshs, extra), p);
}
}
+279
View File
@@ -0,0 +1,279 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "../unit_tests.hpp"
#include "mfem.hpp"
#ifdef MFEM_USE_MPI
#include "../../../fem/dfem/doperator.hpp"
#include "../../../fem/dfem/backends/local_qf/prelude.hpp"
using namespace mfem;
using namespace mfem::future;
#ifdef MFEM_USE_ENZYME
using dscalar_t = real_t;
#else
using dscalar_t = dual<real_t, real_t>;
#endif
template <typename dscalar_t, int dim>
struct CubicH1Functional
{
static constexpr real_t alpha = 0.3;
static constexpr real_t beta = 0.7;
MFEM_HOST_DEVICE inline
auto operator()(const dscalar_t &u,
const tensor<dscalar_t, dim> &dudxi,
const tensor<real_t, dim, dim> &J,
const real_t &w,
dscalar_t &f) const
{
const auto invJ = inv(J);
const auto dudx = dudxi * invJ;
const auto dx = det(J) * w;
const auto z =
+ 0.5_r * u * u
+ 0.25_r * alpha * u * u * u * u
+ 0.5_r * beta * dot(dudx, dudx);
f = z * dx;
}
};
template <int dim>
class MyFunctional
{
static constexpr int U = 0, Coords = 1, Q = 2;
public:
MyFunctional(const ParFiniteElementSpace &fes,
const ParFiniteElementSpace &mfes,
const IntegrationRule &ir) :
comm(fes.GetComm()),
qspace(*fes.GetParMesh(), ir),
qspace_vec(qspace, 1),
q(qspace_vec)
{
const auto in_fds = std::vector
{
FieldDescriptor{U, &fes},
FieldDescriptor{Coords, &mfes}
};
const auto out_fds = std::vector
{
FieldDescriptor{Q, &qspace_vec}
};
const auto &mesh = *fes.GetParMesh();
Array<int> all_domain_attr;
if (mesh.attributes.Size() > 0)
{
all_domain_attr.SetSize(mesh.attributes.Max());
all_domain_attr = 1;
}
dop = std::make_unique<DifferentiableOperator>(in_fds, out_fds, mesh);
CubicH1Functional<dscalar_t, dim> apply;
auto derivatives = std::integer_sequence<size_t, U> {};
dop->AddDomainIntegrator<LocalQFBackend>(
apply,
tuple{Value<U>{}, Gradient<U>{}, Gradient<Coords>{}, Weight{}},
tuple{Identity<Q>{}},
ir, all_domain_attr, derivatives);
mesh.GetNodes()->GetTrueDofs(coords);
}
real_t Eval(const Vector &u) const
{
real_t local = EvalLocal(u), global;
MPI_Allreduce(&local, &global, 1, MPITypeMap<real_t>::mpi_type, MPI_SUM, comm);
return global;
}
// Returns the directional derivative dJ/du · du.
real_t dJdu_dir(const Vector &u, const Vector &du) const
{
real_t local = dJdu_dir_local(u, du), global;
MPI_Allreduce(&local, &global, 1, MPITypeMap<real_t>::mpi_type, MPI_SUM, comm);
return global;
}
// Computes the full gradient \nabla J(u) in the trial space via J^T.
// Since Eval sums raw QF values (J = \sum f_q), the adjoint of the
// summation is a QF of ones.
void grad(const Vector &u, Vector &g) const
{
MultiVector X{u, coords};
q = 1.0;
MultiVector ones{q};
dop->GetDerivative(U, X)->MultTranspose(ones, g);
}
// Computes the full gradient via element-wise central differences.
void grad_fd(const Vector &u, Vector &g, real_t eps = 1e-5) const
{
const int local_size = u.Size();
// Global offset for this rank's DOFs and total DOF count.
int offset = 0, global_size = local_size;
MPI_Exscan(&local_size, &offset, 1, MPITypeMap<int>::mpi_type, MPI_SUM, comm);
MPI_Allreduce(MPI_IN_PLACE, &global_size, 1, MPITypeMap<int>::mpi_type, MPI_SUM,
comm);
g.SetSize(local_size);
Vector up(u), um(u);
// Loop over global DOF indices. Each rank perturbs only when gi falls in
// its local range [offset, offset+local_size); all ranks call Eval together.
for (int gi = 0; gi < global_size; ++gi)
{
const int li = gi - offset;
if (li >= 0 && li < local_size) { up(li) += eps; um(li) -= eps; }
const real_t Jp = Eval(up);
const real_t Jm = Eval(um);
if (li >= 0 && li < local_size)
{
g(li) = (Jp - Jm) / (2.0 * eps);
up(li) = u(li);
um(li) = u(li);
}
}
}
private:
real_t EvalLocal(const Vector &u) const
{
MultiVector X{u, coords};
MultiVector Y{q};
dop->Mult(X, Y);
return q.Sum();
}
real_t dJdu_dir_local(const Vector &u, const Vector &du) const
{
MultiVector X{u, coords};
MultiVector dY{q};
dop->GetDerivative(U, X)->Mult(du, dY);
return q.Sum();
}
MPI_Comm comm;
std::unique_ptr<DifferentiableOperator> dop;
QuadratureSpace qspace;
VectorQuadratureSpace qspace_vec;
mutable QuadratureFunction q;
Vector coords;
};
template <int DIM>
void functional(const char *filename, int p)
{
CAPTURE(filename, DIM, p);
Mesh smesh(filename);
ParMesh pmesh(MPI_COMM_WORLD, smesh);
pmesh.EnsureNodes();
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
p = std::max(p, pmesh.GetNodalFESpace()->GetMaxElementOrder());
smesh.Clear();
H1_FECollection fec(p, DIM);
ParFiniteElementSpace fes(&pmesh, &fec);
ParFiniteElementSpace *mfes = nodes->ParFESpace();
const auto ir = IntRules.Get(pmesh.GetTypicalElementGeometry(), 2 * p);
Vector u(fes.GetTrueVSize());
Vector du(fes.GetTrueVSize());
u.Randomize(5532);
du.Randomize(3251);
MyFunctional<DIM> functional(fes, *mfes, ir);
const real_t dJ_ad = functional.dJdu_dir(u, du);
Vector g(fes.GetTrueVSize());
functional.grad(u, g);
const real_t dJ_ad_grad = InnerProduct(pmesh.GetComm(), g, du);
real_t best_error_dir = infinity();
real_t best_error_grad = infinity();
for (real_t eps : {1e-3, 3e-4, 1e-4, 3e-5})
{
Vector up(u), um(u);
up.Add(eps, du);
um.Add(-eps, du);
const real_t Jp = functional.Eval(up);
const real_t Jm = functional.Eval(um);
const real_t dJ_fd = (Jp - Jm) / (2.0 * eps);
const real_t scale = std::max(real_t(1.0), std::abs(dJ_fd));
best_error_dir = std::min(best_error_dir,
std::abs(dJ_ad - dJ_fd) / scale);
best_error_grad = std::min(best_error_grad,
std::abs(dJ_ad_grad - dJ_fd) / scale);
}
REQUIRE(best_error_dir < 1e-7);
REQUIRE(best_error_grad < 1e-7);
// Must match entry-wise FD gradient
Vector g_fd;
functional.grad_fd(u, g_fd);
Vector diff(g);
diff -= g_fd;
const real_t scale = std::max(real_t(1.0), g_fd.Normlinf());
real_t local_norm = diff.Normlinf();
real_t global_norm;
MPI_Allreduce(&local_norm, &global_norm, 1, MPITypeMap<real_t>::mpi_type,
MPI_SUM, pmesh.GetComm());
REQUIRE(diff.Normlinf() / scale < 1e-5);
}
TEST_CASE("dFEM functional derivative action matches finite differences",
"[Parallel][dFEM][GPU]")
{
const auto p = GenAll({1}, {2, 3});
SECTION("2d")
{
const auto meshs = { "../../data/inline-quad.mesh" };
const auto extra = { "../../data/star.mesh",
"../../data/star-q3.mesh",
"../../data/rt-2d-q3.mesh",
"../../data/periodic-square.mesh"
};
functional<2>(GenAll(meshs, extra), p);
}
SECTION("3d")
{
const auto meshs = { "../../data/inline-hex.mesh" };
const auto extra = { "../../data/fichera.mesh",
"../../data/fichera-q3.mesh",
"../../data/toroid-hex.mesh",
"../../data/periodic-cube.mesh"
};
functional<3>(GenAll(meshs, extra), p);
}
}
#endif // MFEM_USE_MPI
@@ -0,0 +1,237 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "../unit_tests.hpp"
#include "mfem.hpp"
#ifdef MFEM_USE_ENZYME
#ifdef MFEM_USE_MPI
#include "../../../fem/dfem/doperator.hpp"
#include "../../../fem/dfem/backends/local_qf/prelude.hpp"
using namespace mfem;
using namespace mfem::future;
using mfem::future::tensor;
namespace functional_gradient_test
{
// Dirichlet-type energy 1/2 \int |grad u|^2 dx. It depends on the solution and
// on the mesh coordinates, so both derivatives are nontrivial. The coordinate
// field enters only through Gradient<Coords>, while the solution enters
// through both Value<U> and Gradient<U>, so the two derivatives have a
// different number of outputs.
template <int dim>
struct EnergyFunctional
{
MFEM_HOST_DEVICE inline __attribute__((always_inline))
auto operator()(const real_t &u,
const tensor<real_t, dim> &dudxi,
const tensor<real_t, dim, dim> &J,
const real_t &w,
real_t &f) const
{
const auto invJ = inv(J);
const auto dudx = dudxi * invJ;
f = (0.5_r * sqnorm(dudx) + 0.25_r * u * u) * det(J) * w;
}
};
/// Energy functional with derivatives w.r.t. both the solution and the mesh
/// coordinates, plus a finite-difference reference for either one.
template <int dim>
class EnergyWithShapeDerivative
{
static constexpr int U = 0, Coords = 1, Q = 2;
public:
EnergyWithShapeDerivative(const ParFiniteElementSpace &fes,
const ParFiniteElementSpace &mfes,
const IntegrationRule &ir) :
comm(fes.GetComm()),
qspace(*fes.GetParMesh(), ir),
qspace_vec(qspace, 1),
q(qspace_vec)
{
const auto &pmesh = *fes.GetParMesh();
Array<int> all_domain_attr;
if (pmesh.attributes.Size() > 0)
{
all_domain_attr.SetSize(pmesh.attributes.Max());
all_domain_attr = 1;
}
const auto in = std::vector
{
FieldDescriptor{U, &fes},
FieldDescriptor{Coords, &mfes}
};
const auto out = std::vector
{
FieldDescriptor{Q, &qspace_vec}
};
dop = std::make_unique<DifferentiableOperator>(in, out, pmesh);
EnergyFunctional<dim> energy;
dop->AddDomainIntegrator<LocalQFBackend>(
energy,
Inputs<Value<U>, Gradient<U>, Gradient<Coords>, Weight> {},
Outputs<FunctionalValue<Q>> {},
ir, all_domain_attr, Derivatives<U, Coords> {});
}
real_t Eval(const Vector &u, const Vector &x) const
{
MultiVector X{u, x};
MultiVector Y{q};
dop->Mult(X, Y);
const real_t local = q.Sum();
real_t global;
MPI_Allreduce(&local, &global, 1, MPITypeMap<real_t>::mpi_type, MPI_SUM,
comm);
return global;
}
/// Gradient w.r.t. @a derivative_id, assembled into a Vector.
void AssembleGradient(size_t derivative_id, const Vector &u,
const Vector &x, Vector &g) const
{
MultiVector X{u, x};
dop->GetDerivative(derivative_id, X)->Assemble(g);
}
/// Central-difference directional derivative of the energy.
real_t DirectionalFD(const Vector &u, const Vector &x,
const Vector &du, const Vector &dx,
real_t eps) const
{
Vector up(u), um(u), xp(x), xm(x);
up.Add(eps, du);
um.Add(-eps, du);
xp.Add(eps, dx);
xm.Add(-eps, dx);
return (Eval(up, xp) - Eval(um, xm)) / (2.0_r * eps);
}
/// Global inner product of two T-vectors (true dofs are uniquely owned).
real_t Dot(const Vector &a, const Vector &b) const
{
const real_t local = a * b;
real_t global;
MPI_Allreduce(&local, &global, 1, MPITypeMap<real_t>::mpi_type, MPI_SUM,
comm);
return global;
}
private:
MPI_Comm comm;
std::unique_ptr<DifferentiableOperator> dop;
QuadratureSpace qspace;
VectorQuadratureSpace qspace_vec;
mutable QuadratureFunction q;
};
template <int DIM>
void functional_gradient(const char *filename, int p)
{
CAPTURE(filename, DIM, p);
static constexpr int U = 0, Coords = 1;
Mesh smesh(filename);
ParMesh pmesh(MPI_COMM_WORLD, smesh);
pmesh.EnsureNodes();
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
ParFiniteElementSpace *mfes = nodes->ParFESpace();
H1_FECollection fec(p, DIM);
ParFiniteElementSpace fes(&pmesh, &fec);
const IntegrationRule &ir =
IntRules.Get(pmesh.GetTypicalElementGeometry(), 2 * p + 2);
EnergyWithShapeDerivative<DIM> energy(fes, *mfes, ir);
ParGridFunction u_gf(&fes), du_gf(&fes);
FunctionCoefficient u_coeff(
[](const auto &x) { return 1.0_r + x[0] + 0.25_r * x[1] * x[1]; });
FunctionCoefficient du_coeff(
[](const auto &x) { return sin(M_PI * x[0]) + 0.5_r * x[0] * x[1]; });
u_gf.ProjectCoefficient(u_coeff);
du_gf.ProjectCoefficient(du_coeff);
ParGridFunction dx_gf(mfes);
VectorFunctionCoefficient dx_coeff(
DIM, [](const Vector &x, Vector &v)
{
v = 0.0;
v(0) = 0.1_r * sin(M_PI * x[0]) * x[1];
v(1) = 0.1_r * cos(M_PI * x[1]) * x[0];
});
dx_gf.ProjectCoefficient(dx_coeff);
Vector u(fes.GetTrueVSize()), du(fes.GetTrueVSize());
Vector x(mfes->GetTrueVSize()), dx(mfes->GetTrueVSize());
u_gf.GetTrueDofs(u);
du_gf.GetTrueDofs(du);
nodes->GetTrueDofs(x);
dx_gf.GetTrueDofs(dx);
Vector zero_u(fes.GetTrueVSize()), zero_x(mfes->GetTrueVSize());
zero_u = 0.0;
zero_x = 0.0;
const real_t eps = 1e-6;
// Derivative w.r.t. the solution.
Vector g_u;
energy.AssembleGradient(U, u, x, g_u);
REQUIRE(g_u.Size() == fes.GetTrueVSize());
const real_t dJdu_fd = energy.DirectionalFD(u, x, du, zero_x, eps);
REQUIRE(energy.Dot(g_u, du) == MFEM_Approx(dJdu_fd, 1e-6, 1e-8));
// Derivative w.r.t. the mesh coordinates. This is the case that used to
// assemble into the solution space instead of the coordinate space.
Vector g_x;
energy.AssembleGradient(Coords, u, x, g_x);
REQUIRE(g_x.Size() == mfes->GetTrueVSize());
const real_t dJdx_fd = energy.DirectionalFD(u, x, zero_u, dx, eps);
REQUIRE(energy.Dot(g_x, dx) == MFEM_Approx(dJdx_fd, 1e-6, 1e-8));
}
} // namespace functional_gradient_test
TEST_CASE("dFEM functional gradient assembles into a Vector",
"[Parallel][dFEM][functional-gradient]")
{
const bool all_tests = launch_all_non_regression_tests;
const auto p = !all_tests ? 1 : GENERATE(1, 2, 3);
SECTION("2d")
{
const auto f = GENERATE("../../data/inline-quad.mesh",
"../../data/star.mesh");
functional_gradient_test::functional_gradient<2>(f, p);
}
SECTION("3d")
{
const auto f = GENERATE("../../data/inline-hex.mesh");
functional_gradient_test::functional_gradient<3>(f, p);
}
}
#endif // MFEM_USE_MPI
#endif // MFEM_USE_ENZYME
+312
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// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "../unit_tests.hpp"
#include "mfem.hpp"
#ifdef MFEM_USE_MPI
#include "../../../fem/dfem/doperator.hpp"
#include "../../../fem/dfem/backends/local_qf/prelude.hpp"
using namespace mfem;
using namespace mfem::future;
using mfem::future::tensor;
#ifdef MFEM_USE_ENZYME
using dscalar_t = real_t;
#else
using mfem::future::dual;
using dscalar_t = dual<real_t, real_t>;
#endif
constexpr int dim = 3;
constexpr int Displacement = 0;
constexpr int Coords = 1;
constexpr int Energy = 2;
template <typename dscalar_t>
struct NeoHookeanEnergy
{
real_t D1 = 100.0;
real_t C1 = 50.0;
MFEM_HOST_DEVICE inline
void operator()(const tensor<dscalar_t, dim, dim> &dudxi,
const tensor<real_t, dim, dim> &J,
const real_t &w,
dscalar_t &energy) const
{
const auto invJ = inv(J);
const auto dudx = dudxi * invJ;
const auto F = IdentityMatrix<dim>() + dudx;
const auto C = transpose(F) * F;
const auto JF = det(F);
const auto I1_bar = pow(JF, -2.0_r / 3.0_r) * tr(C);
const auto psi = D1 * (JF - 1.0_r) * (JF - 1.0_r)
+ C1 * (I1_bar - real_t(dim));
energy = psi * det(J) * w;
}
};
template <typename dscalar_t>
struct NeoHookeanStress
{
real_t D1 = 100.0;
real_t C1 = 50.0;
MFEM_HOST_DEVICE inline
void operator()(const tensor<dscalar_t, dim, dim> &dudxi,
const tensor<real_t, dim, dim> &J,
const real_t &w,
tensor<dscalar_t, dim, dim> &dvdxi) const
{
const auto invJ = inv(J);
const auto dudx = dudxi * invJ;
const auto F = IdentityMatrix<dim>() + dudx;
const auto JF = det(F);
const auto FinvT = inv(transpose(F));
const auto I1 = tr(transpose(F) * F);
const auto P = 2.0_r * D1 * JF * (JF - 1.0_r) * FinvT
+ 2.0_r * C1 * pow(JF, -2.0_r / 3.0_r)
* (F - (I1 / 3.0_r) * FinvT);
dvdxi = P * transpose(invJ) * det(J) * w;
}
};
class HyperelasticityProblem
{
public:
HyperelasticityProblem(ParFiniteElementSpace &fes,
const IntegrationRule &ir,
bool use_energy) :
fes(fes),
use_energy(use_energy),
qspace(*fes.GetParMesh(), ir),
qspace_vec(qspace, 1),
q(qspace_vec)
{
auto &mesh_nodes = *static_cast<ParGridFunction *>
(fes.GetParMesh()->GetNodes());
mesh_nodes_fes = mesh_nodes.ParFESpace();
mesh_nodes.GetTrueDofs(mesh_nodes_tdofs);
const std::vector<FieldDescriptor> inputs =
{
{Displacement, &fes},
{Coords, mesh_nodes_fes}
};
std::vector<FieldDescriptor> outputs;
if (use_energy)
{
outputs = std::vector<FieldDescriptor>
{
{Energy, &qspace_vec}
};
}
else
{
outputs = std::vector<FieldDescriptor>
{
{Displacement, &fes}
};
}
dop = std::make_shared<DifferentiableOperator>(inputs, outputs,
*fes.GetParMesh());
Array<int> all_domain_attr;
if (fes.GetMesh()->attributes.Size() > 0)
{
all_domain_attr.SetSize(fes.GetMesh()->attributes.Max());
all_domain_attr = 1;
}
auto derivatives = std::integer_sequence<size_t, Displacement> {};
if (use_energy)
{
NeoHookeanEnergy<dscalar_t> energy;
dop->AddDomainIntegrator<LocalQFBackend>(
energy,
Inputs<Gradient<Displacement>, Gradient<Coords>, Weight> {},
Outputs<FunctionalValue<Energy>> {},
ir, all_domain_attr, derivatives);
}
else
{
NeoHookeanStress<dscalar_t> stress;
dop->AddDomainIntegrator<LocalQFBackend>(
stress,
Inputs<Gradient<Displacement>, Gradient<Coords>, Weight> {},
Outputs<Gradient<Displacement>> {},
ir, all_domain_attr, derivatives);
}
}
void SetEssentialAttributes(const Array<int> &ess_bdr)
{
fes.GetEssentialTrueDofs(ess_bdr, ess_tdofs);
}
void SetPrescribedDisplacementAttributes(const Array<int> &disp_bdr)
{
fes.GetEssentialTrueDofs(disp_bdr, prescribed_tdofs);
}
const Array<int>& GetPrescribedDisplacementTDofs() const
{
return prescribed_tdofs;
}
const Array<int>& GetEssentialTDofs() const
{
return ess_tdofs;
}
void Residual(const Vector &x, Vector &r) const
{
MultiVector X{x, mesh_nodes_tdofs};
MultiVector R{r};
if (use_energy)
{
dop->GetDerivative(Displacement)->Mult(X, R);
}
else
{
dop->Mult(X, R);
}
r.SetSubVector(ess_tdofs, 0.0);
}
void GradientAction(const Vector &x, const Vector &dx, Vector &y) const
{
MultiVector X{x, mesh_nodes_tdofs};
std::shared_ptr<DerivativeOperator> derivative;
if (use_energy)
{
derivative = dop->GetSecondDerivative(Displacement, X);
}
else
{
derivative = dop->GetDerivative(Displacement, X);
}
Vector local_dx(dx);
local_dx.SetSubVector(ess_tdofs, 0.0);
MultiVector Y{y};
derivative->Mult(local_dx, Y);
y.SetSubVector(ess_tdofs, 0.0);
}
private:
ParFiniteElementSpace &fes;
bool use_energy = false;
ParFiniteElementSpace *mesh_nodes_fes = nullptr;
QuadratureSpace qspace;
VectorQuadratureSpace qspace_vec;
QuadratureFunction q;
Vector mesh_nodes_tdofs;
Array<int> ess_tdofs;
Array<int> prescribed_tdofs;
std::shared_ptr<DifferentiableOperator> dop;
};
struct HyperelasticityTestContext
{
HyperelasticityTestContext(bool use_energy)
{
Mesh mesh = Mesh::MakeCartesian3D(8, 2, 2, Element::HEXAHEDRON, 8.0, 1.0, 1.0);
mesh.EnsureNodes();
pmesh = std::make_unique<ParMesh>(MPI_COMM_WORLD, mesh);
mesh.Clear();
pmesh->EnsureNodes();
fec = std::make_unique<H1_FECollection>(1, dim);
fes = std::make_unique<ParFiniteElementSpace>(pmesh.get(), fec.get(), dim,
Ordering::byNODES);
const IntegrationRule &ir = IntRules.Get(pmesh->GetTypicalElementGeometry(), 3);
problem = std::make_unique<HyperelasticityProblem>(*fes, ir, use_energy);
Array<int> ess_attr(pmesh->bdr_attributes.Max());
ess_attr = 0;
ess_attr[4] = 1;
ess_attr[2] = 1;
problem->SetEssentialAttributes(ess_attr);
Array<int> disp_attr(pmesh->bdr_attributes.Max());
disp_attr = 0;
disp_attr[2] = 1;
problem->SetPrescribedDisplacementAttributes(disp_attr);
state.SetSize(fes->GetTrueVSize());
state.Randomize(11);
state -= 0.5;
state *= 1.0e-3;
state.SetSubVector(problem->GetEssentialTDofs(), 0.0);
state.SetSubVector(problem->GetPrescribedDisplacementTDofs(), 1.0e-2);
direction.SetSize(fes->GetTrueVSize());
direction.Randomize(17);
direction -= 0.5;
}
std::unique_ptr<ParMesh> pmesh;
std::unique_ptr<H1_FECollection> fec;
std::unique_ptr<ParFiniteElementSpace> fes;
std::unique_ptr<HyperelasticityProblem> problem;
Vector state;
Vector direction;
};
TEST_CASE("dfem neo-hookean energy and stress agree",
"[Parallel][dFEM][GPU][Hyperelasticity]")
{
HyperelasticityTestContext energy(true);
HyperelasticityTestContext stress(false);
REQUIRE(energy.state.Size() == stress.state.Size());
// Check residuals from energy and stress formulations should match.
Vector energy_residual(energy.state.Size());
Vector stress_residual(stress.state.Size());
energy.problem->Residual(energy.state, energy_residual);
stress.problem->Residual(stress.state, stress_residual);
Vector residual_diff(energy_residual);
residual_diff -= stress_residual;
REQUIRE(residual_diff.Norml2() < 1e-12);
// Check the energy Hessian action should match the stress Jacobian action.
Vector energy_action(energy.state.Size());
Vector stress_action(stress.state.Size());
energy.problem->GradientAction(energy.state, energy.direction, energy_action);
stress.problem->GradientAction(stress.state, stress.direction, stress_action);
Vector action_diff(energy_action);
action_diff -= stress_action;
if (verbose_tests)
{
mfem::out << "Energy Hessian action norm: " << energy_action.Norml2() <<
std::endl;
mfem::out << "Stress Jacobian action norm: " << stress_action.Norml2() <<
std::endl;
}
REQUIRE(action_diff.Norml2() < 1e-10);
REQUIRE(energy_action.Norml2() > 0.0);
REQUIRE(stress_action.Norml2() > 0.0);
}
#endif
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// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "../unit_tests.hpp"
#include "mfem.hpp"
#ifdef MFEM_USE_MPI
#ifndef _WIN32
#include "../../../fem/dfem/doperator.hpp"
#include "../../../linalg/tensor_arrays.hpp"
using namespace mfem;
using namespace mfem::future;
#ifdef MFEM_USE_ENZYME
using dreal_t = real_t;
#else
using dreal_t = dual<real_t, real_t>;
#endif
static constexpr int U = 0, V = 1, X = 2;
// ────────────────────────────────────────────────────────────────────────────
template<int DIM>
struct global_qf
{
void operator()(tensor_array<const dreal_t> &x,
tensor_array<const dreal_t> &y,
tensor_array<const real_t, DIM, DIM> &J,
tensor_array<const real_t> &w,
tensor_array<dreal_t> &z) const
{
mfem::forall(x.size(),
[=] MFEM_HOST_DEVICE(int q)
{
const dreal_t xq = x(q), yq = y(q);
z(q) = sin(xq) * cos(yq) * (xq + yq) * w(q) * det(J(q));
});
}
};
// ────────────────────────────────────────────────────────────────────────────
template<int DIM>
struct local_qf
{
inline MFEM_HOST_DEVICE void operator()(const dreal_t &x,
const dreal_t &y,
const tensor<real_t, DIM, DIM> &J,
const real_t &w,
dreal_t &z) const
{ z = sin(x) * cos(y) * (x + y) * w * det(J); }
};
// ────────────────────────────────────────────────────────────────────────────
template<int DIM>
static void VerifyJvpVjp(DifferentiableOperator &F,
ParFiniteElementSpace &fes,
ParGridFunction &nodes)
{
const auto nfes = nodes.ParFESpace();
const auto tvsize = fes.GetTrueVSize();
const auto ntvsize = nfes->GetTrueVSize();
const auto comm = fes.GetParMesh()->GetComm();
Vector X_bar(tvsize), Y_bar(tvsize), N_bar(ntvsize);
X_bar.Randomize(0x9e3779b9);
Y_bar.Randomize(0x9e3779b1);
nodes.GetTrueDofs(N_bar);
MultiVector state{ X_bar, Y_bar, N_bar };
Vector dX(tvsize), dY(tvsize), dZ(tvsize);
dX.Randomize(0x01000193);
dY.Randomize(0x1b873593);
Vector dU(tvsize), dV(tvsize);
MultiVector mdU{ dU }, mdV{ dV };
const auto dFu = F.GetDerivative(U, state);
const auto dFv = F.GetDerivative(V, state);
dFu->Mult(dX, mdU); // dU = (∂F/∂u) dX
dFv->Mult(dY, mdV); // dV = (∂F/∂v) dY
add(dU, dV, dZ);
Vector dX_star(tvsize), dY_star(tvsize), dZ_star(tvsize);
dZ_star.Randomize(0x7ed55d16);
MultiVector mdZ_star{ dZ_star }, mdX_star{ dX_star }, mdY_star{ dY_star };
dFu->MultTranspose(mdZ_star, mdX_star); // dX* = (∂F/∂u)^T dZ*
dFv->MultTranspose(mdZ_star, mdY_star); // dY* = (∂F/∂v)^T dZ*
// Tangent/cotangent consistency test:
// <dZ*, dZ> = <dX*, dX> + <dY*, dY>
REQUIRE(InnerProduct(comm, dZ_star, dZ) ==
MFEM_Approx(InnerProduct(comm, dX_star, dX) +
InnerProduct(comm, dY_star, dY)));
REQUIRE(InnerProduct(comm, dZ_star, dU) ==
MFEM_Approx(InnerProduct(comm, dX_star, dX)));
REQUIRE(InnerProduct(comm, dZ_star, dV) ==
MFEM_Approx(InnerProduct(comm, dY_star, dY)));
}
// ────────────────────────────────────────────────────────────────────────────
template<int DIM>
void TestJvpVjp(const char *filename, int p)
{
CAPTURE(filename, DIM, p);
Mesh smesh(filename);
ParMesh pmesh(MPI_COMM_WORLD, smesh);
MFEM_VERIFY(pmesh.Dimension() == DIM, "Mesh dimension mismatch");
pmesh.EnsureNodes();
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
smesh.Clear();
p = std::max(p, pmesh.GetNodalFESpace()->GetMaxElementOrder());
Array<int> all_domain_attr;
if (pmesh.attributes.Size() > 0)
{
all_domain_attr.SetSize(pmesh.attributes.Max());
all_domain_attr = 1;
}
H1_FECollection fec(p, DIM);
ParFiniteElementSpace fes(&pmesh, &fec);
const auto *nfes = nodes->ParFESpace();
const auto geom = pmesh.GetTypicalElementGeometry();
const auto ir = &IntRules.Get(geom, 2 * p + 1);
using vfds_t = std::vector<FieldDescriptor>;
const vfds_t in_fds = { { U, &fes }, { V, &fes }, { X, nfes } };
const vfds_t out_fds = { { U, &fes } };
DifferentiableOperator F(in_fds, out_fds, pmesh);
using IT = Inputs<Value<U>, Value<V>, Gradient<X>, Weight>;
using OT = Outputs<Value<U>>;
using DT = Derivatives<U, V>;
if constexpr (!mfem_use_gpu)
{
global_qf<DIM> q_gfn{};
F.AddDomainIntegrator<GlobalQFBackend>(
q_gfn, IT{}, OT{}, *ir, all_domain_attr, DT{});
}
using LQT = local_qf<DIM>;
local_qf<DIM> q_lfn{};
F.AddDomainIntegrator<LocalQFBackend>(
q_lfn, IT{}, OT{}, *ir, all_domain_attr, DT{});
AddLocalSpecializations<DIM, 3, LQT, IT, OT, DT>();
VerifyJvpVjp<DIM>(F, fes, *nodes);
}
// ────────────────────────────────────────────────────────────────────────────
TEST_CASE("dFEM JVP-VJP 2D", "[Parallel][dFEM][GPU]")
{
const auto p = GenAll({ 1 }, { 2, 3 });
const auto meshs = { "../../data/inline-quad.mesh" };
const auto extra = { "../../data/star.mesh",
"../../data/star-q3.mesh",
"../../data/rt-2d-q3.mesh",
"../../data/periodic-square.mesh"
};
TestJvpVjp<2>(GenAll(meshs, extra), p);
}
// ────────────────────────────────────────────────────────────────────────────
TEST_CASE("dFEM JVP-VJP 3D", "[Parallel][dFEM][GPU]")
{
const auto p = GenAll({ 1 }, { 2, 3 });
const auto meshs = { "../../data/inline-hex.mesh" };
const auto extra = { "../../data/fichera.mesh",
"../../data/fichera-q3.mesh",
"../../data/toroid-hex.mesh",
"../../data/periodic-cube.mesh"
};
TestJvpVjp<3>(GenAll(meshs, extra), p);
}
#endif // _WIN32
#endif // MFEM_USE_MPI
+61 -24
View File
@@ -10,37 +10,37 @@
// CONTRIBUTING.md for details.
#include "../unit_tests.hpp"
#include "mfem.hpp"
#ifdef MFEM_USE_MPI
#include "../../../fem/dfem/doperator.hpp"
#include "../../../fem/dfem/backends/local_qf/prelude.hpp"
using namespace mfem;
using namespace mfem::future;
using mfem::future::tensor;
constexpr int DIM = 3;
namespace kernels
{
template <int DIM>
struct MFApply
{
MFEM_HOST_DEVICE inline auto operator()(const tensor<real_t, DIM> &dudxi,
const tensor<real_t, DIM, DIM> &J,
const real_t &w) const
MFEM_HOST_DEVICE inline auto operator()(
const tensor<real_t, DIM> &dudxi,
const tensor<real_t, DIM, DIM> &J,
const real_t &w,
tensor<real_t, DIM> &dvdxi) const
{
const auto invJ = inv(J);
return tuple{ (dudxi * invJ) * transpose(invJ) * det(J) * w };
const auto invJt = transpose(invJ);
dvdxi = (dudxi * invJ) * invJt * det(J) * w;
}
};
}
TEST_CASE("DFEM L-Vector interface", "[Parallel][dFEM][GPU]")
template <int DIM, typename QFBackend = LocalQFBackend>
void l_vector_interface(const char *filename, int p)
{
constexpr int p = 2; // Polynomial order
constexpr int r = 1;
constexpr int q = 2 * p + r;
CAPTURE(filename, DIM, p);
const auto filename = GENERATE("../../data/fichera.mesh");
Mesh smesh(filename);
ParMesh pmesh(MPI_COMM_WORLD, smesh);
MFEM_VERIFY(pmesh.Dimension() == DIM, "Mesh dimension mismatch");
@@ -49,6 +49,9 @@ TEST_CASE("DFEM L-Vector interface", "[Parallel][dFEM][GPU]")
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
smesh.Clear();
p = std::max(p, pmesh.GetNodalFESpace()->GetMaxElementOrder());
const int q = 2 * p + 1;
Array<int> all_domain_attr;
if (pmesh.attributes.Size() > 0)
{
@@ -75,18 +78,28 @@ TEST_CASE("DFEM L-Vector interface", "[Parallel][dFEM][GPU]")
static constexpr int U = 0, Coords = 1;
const auto solution = std::vector{FieldDescriptor{U, &pfes}};
DifferentiableOperator dop(solution, {{Coords, mfes}}, pmesh);
const auto in_fds = std::vector
{
FieldDescriptor{ U, &pfes },
FieldDescriptor{ Coords, mfes }
};
const auto out_fds = std::vector{ FieldDescriptor{ U, &pfes } };
kernels::MFApply mf_apply_qf;
dop.AddDomainIntegrator(mf_apply_qf,
tuple{Gradient<U>{}, Gradient<Coords>{}, Weight{}},
tuple{Gradient<U>{}}, *ir, all_domain_attr);
DifferentiableOperator dop(in_fds, out_fds, pmesh);
MFApply<DIM> mf_apply;
dop.AddDomainIntegrator<LocalQFBackend>(
mf_apply,
tuple{Gradient<U>{}, Gradient<Coords>{}, Weight{}},
tuple{Gradient<U>{}},
*ir, all_domain_attr);
// Use the L-vector interface to multiply
dop.SetMultLevel(DifferentiableOperator::MultLevel::LVECTOR);
dop.SetParameters({nodes});
dop.Mult(x, z);
MultiVector mx{x, *nodes};
MultiVector mz{z};
dop.Mult(mx, mz);
blf_fa.Mult(x, y);
@@ -94,4 +107,28 @@ TEST_CASE("DFEM L-Vector interface", "[Parallel][dFEM][GPU]")
REQUIRE(z.Normlinf() == MFEM_Approx(0.0));
}
#endif
TEST_CASE("dFEM L-Vector 2D", "[Parallel][dFEM][GPU]")
{
const auto p = GenAll({1}, {2, 3});
const auto meshs = { "../../data/inline-quad.mesh" };
const auto extra = { "../../data/star.mesh",
"../../data/star-q3.mesh",
"../../data/rt-2d-q3.mesh",
"../../data/periodic-square.mesh"
};
l_vector_interface<2>(GenAll(meshs, extra), p);
}
TEST_CASE("dFEM L-Vector 3D", "[Parallel][dFEM][GPU]")
{
const auto p = GenAll({1}, {2, 3});
const auto meshs = { "../../data/inline-hex.mesh" };
const auto extra = { "../../data/fichera.mesh",
"../../data/fichera-q3.mesh",
"../../data/toroid-hex.mesh",
"../../data/periodic-cube.mesh"
};
l_vector_interface<3>(GenAll(meshs, extra), p);
}
#endif // MFEM_USE_MPI
+461 -182
View File
@@ -10,160 +10,82 @@
// CONTRIBUTING.md for details.
#include "../unit_tests.hpp"
#include "../linalg/test_same_matrices.hpp"
#include "mfem.hpp"
#ifdef MFEM_USE_MPI
#include "../linalg/test_same_matrices.hpp"
#include "../../../fem/dfem/doperator.hpp"
#include "../../../fem/dfem/backends/local_qf/prelude.hpp"
using namespace mfem;
using namespace mfem::future;
using mfem::future::tensor;
#ifdef MFEM_USE_ENZYME
using dscalar_t = real_t;
#else
using mfem::future::dual;
using dscalar_t = dual<real_t, real_t>;
#endif
// ────────────────────────────────────────────────────────────────────────────
template <int DIM> struct global_mf_mass_qf
{
void operator()(tensor_array<const dscalar_t> &u,
tensor_array<const real_t, DIM, DIM> &J,
tensor_array<const real_t> &w,
tensor_array<dscalar_t> &v) const
{
// Enzyme requires extra support to handle:
// mfem::forall(u.size(), [=] MFEM_HOST_DEVICE (int q)
for (size_t q = 0; q < u.size(); ++q)
{
v(q) = (dscalar_t)(u(q)) * w(q) * det(J(q));
}
}
};
template <int DIM> struct local_mf_mass_qf
{
inline MFEM_HOST_DEVICE
void operator()(const dscalar_t &u,
const tensor<real_t, DIM, DIM> &J,
const real_t &w,
dscalar_t &v) const
{
v = u * w * det(J);
}
};
// ────────────────────────────────────────────────────────────────────────────
template <int DIM> struct local_mf_vector_mass_qf
{
MFEM_HOST_DEVICE inline auto operator()(
const tensor<dscalar_t, DIM> &vu,
const tensor<real_t, DIM, DIM> &J,
const real_t &w,
tensor<dscalar_t, DIM> &vv) const
{
vv = vu * w * det(J);
}
};
// ────────────────────────────────────────────────────────────────────────────
template <int DIM>
void mass_action(const char *filename, int p)
{
constexpr int BDIM = DIM - 1;
CAPTURE(filename, DIM, p);
Mesh smesh(filename);
ParMesh pmesh(MPI_COMM_WORLD, smesh);
MFEM_VERIFY(pmesh.Dimension() == DIM, "Mesh dimension mismatch");
pmesh.EnsureNodes();
auto* nodes = static_cast<ParGridFunction*>(pmesh.GetNodes());
p = std::max(p, pmesh.GetNodalFESpace()->GetMaxElementOrder());
smesh.Clear();
H1_FECollection fec(p, DIM);
ParFiniteElementSpace fes(&pmesh, &fec);
ParGridFunction x(&fes), y(&fes), z(&fes);
Vector X(fes.GetTrueVSize()), Y(fes.GetTrueVSize()), Z(fes.GetTrueVSize());
X.Randomize(1);
x.SetFromTrueDofs(X);
ConstantCoefficient one(1.0);
SECTION("domain")
{
const auto *ir = &IntRules.Get(pmesh.GetTypicalElementGeometry(), 2 * p);
Array<int> all_domain_attr;
if (pmesh.attributes.Size() > 0)
{
all_domain_attr.SetSize(pmesh.attributes.Max());
all_domain_attr = 1;
}
ParBilinearForm blf(&fes);
blf.AddDomainIntegrator(new MassIntegrator(one, ir));
blf.SetAssemblyLevel(AssemblyLevel::PARTIAL);
blf.Assemble();
blf.Mult(x, y);
fes.GetProlongationMatrix()->MultTranspose(y, Y);
static constexpr int U = 0, Coords = 1;
const auto sol = std::vector{ FieldDescriptor{ U, &fes } };
DifferentiableOperator dop(sol, {{Coords, nodes->ParFESpace()}}, pmesh);
const auto mf_mass_qf =
[] MFEM_HOST_DEVICE(const real_t &u,
const tensor<real_t, DIM, DIM> &J, const real_t &w)
{ return tuple{u * w * det(J)}; };
dop.AddDomainIntegrator(mf_mass_qf,
tuple{ Value<U>{}, Gradient<Coords>{}, Weight{} },
tuple{ Value<U>{} },
*ir, all_domain_attr);
dop.SetParameters({ nodes });
fes.GetRestrictionMatrix()->Mult(x, X);
dop.Mult(X, Z);
Y -= Z;
real_t norm_g, norm_l = Y.Normlinf();
MPI_Allreduce(&norm_l, &norm_g, 1, MPI_DOUBLE, MPI_MAX, pmesh.GetComm());
REQUIRE(norm_g == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
// Test boundary
// This ensures that we're not trying to test on fully periodic meshes
if (!((std::string("../../data/periodic-square.mesh").compare(filename) == 0) ||
(std::string("../../data/periodic-cube.mesh").compare(filename) == 0)))
{
SECTION("boundary")
{
const auto *ir = &IntRules.Get(pmesh.GetTypicalFaceGeometry(), 2 * p);
Array<int> all_bdr_attr;
if (pmesh.bdr_attributes.Size() > 0)
{
all_bdr_attr.SetSize(pmesh.bdr_attributes.Max());
all_bdr_attr = 1;
}
ParBilinearForm blf(&fes);
blf.AddBoundaryIntegrator(new MassIntegrator(one, ir));
blf.SetAssemblyLevel(AssemblyLevel::PARTIAL);
blf.Assemble();
blf.Mult(x, y);
fes.GetProlongationMatrix()->MultTranspose(y, Y);
static constexpr int U = 0, Coords = 1;
const auto sol = std::vector{FieldDescriptor{U, &fes}};
DifferentiableOperator dop(sol, {{Coords, nodes->ParFESpace()}}, pmesh);
const auto mf_mass_qf =
[] MFEM_HOST_DEVICE(const dscalar_t &u,
const tensor<real_t, DIM, BDIM> &J,
const real_t &w)
{
return tuple{u * weight(J) * w};
};
auto derivatives = std::integer_sequence<size_t, U> {};
dop.AddBoundaryIntegrator(mf_mass_qf,
tuple{ Value<U>{}, Gradient<Coords>{}, Weight{} },
tuple{ Value<U>{} },
*ir, all_bdr_attr, derivatives);
dop.SetParameters({nodes});
fes.GetRestrictionMatrix()->Mult(x, X);
dop.Mult(X, Z);
Y -= Z;
real_t norm_g, norm_l = Y.Normlinf();
MPI_Allreduce(&norm_l, &norm_g, 1, MPI_DOUBLE, MPI_MAX, pmesh.GetComm());
REQUIRE(norm_g == MFEM_Approx(0.0));
auto dRdU = dop.GetDerivative(U, {&x}, {nodes});
dRdU->Mult(X, Z);
fes.GetProlongationMatrix()->MultTranspose(y, Y);
Y -= Z;
norm_l = Y.Normlinf();
MPI_Allreduce(&norm_l, &norm_g, 1, MPI_DOUBLE, MPI_MAX, pmesh.GetComm());
REQUIRE(norm_g == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
}
}
template <int DIM> void mass_mat_mixed(const char* filename, int p)
{
CAPTURE(filename, DIM, p);
Mesh smesh(filename);
ParMesh pmesh(MPI_COMM_WORLD, smesh);
pmesh.EnsureNodes();
auto* nodes = static_cast<ParGridFunction*>(pmesh.GetNodes());
p = std::max(p, pmesh.GetNodalFESpace()->GetMaxElementOrder());
smesh.Clear();
Array<int> all_domain_attr;
if (pmesh.attributes.Size() > 0)
@@ -172,51 +94,394 @@ template <int DIM> void mass_mat_mixed(const char* filename, int p)
all_domain_attr = 1;
}
ParFiniteElementSpace *mfes = nodes->ParFESpace();
const auto *ir = &IntRules.Get(pmesh.GetTypicalElementGeometry(), 2 * p);
H1_FECollection fec(p, DIM);
ParFiniteElementSpace pfes(&pmesh, &fec);
const int tvsize = pfes.GetTrueVSize();
ParGridFunction x(&pfes), y(&pfes), z(&pfes);
Vector X(tvsize), Y(tvsize), Z(tvsize), dZ(tvsize);
X.Randomize(1);
x.SetFromTrueDofs(X);
ConstantCoefficient one(1.0), zero(0.0);
ParBilinearForm blf(&pfes);
// Add two mass integrators as we use both local and global QF backends
// If GPU is enabled, we only add the local QF backend
blf.AddDomainIntegrator(new MassIntegrator(one, ir));
if constexpr(!mfem_use_gpu)
{
blf.AddDomainIntegrator(new MassIntegrator(one, ir));
}
blf.SetAssemblyLevel(AssemblyLevel::PARTIAL);
blf.Assemble();
static constexpr int U = 0, Coords = 1;
const auto in_fds = std::vector
{
FieldDescriptor{ U, &pfes },
FieldDescriptor{ Coords, mfes }
};
const auto out_fds = std::vector{ FieldDescriptor{ U, &pfes } };
Vector N;
nodes->GetTrueDofs(N);
using IT = Inputs<Value<U>, Gradient<Coords>, Weight>;
using OT = Outputs<Value<U>>;
using DT = Derivatives<U>;
SECTION("Action")
{
blf.Mult(x, y);
pfes.GetProlongationMatrix()->MultTranspose(y, Y);
DifferentiableOperator dop(in_fds, out_fds, pmesh);
local_mf_mass_qf<DIM> local_qfn;
dop.AddDomainIntegrator<LocalQFBackend>(
local_qfn, IT {}, OT {}, *ir, all_domain_attr);
if constexpr(!mfem_use_gpu)
{
global_mf_mass_qf<DIM> global_qfn;
dop.AddDomainIntegrator<GlobalQFBackend>(
global_qfn, IT {}, OT {}, *ir, all_domain_attr);
}
MultiVector MX{X, N}, MZ{Z};
dop.Mult(MX, MZ);
Y -= Z;
y.SetFromTrueDofs(Y);
REQUIRE(y.ComputeMaxError(zero) == MFEM_Approx(0.0));
}
SECTION("Action Linearized")
{
// Randomize again s.t. the setup cache cannot
// trivially succeed by caching one direction only.
X.Randomize(0x9e3779b9);
x.SetFromTrueDofs(X);
DifferentiableOperator dop(in_fds, out_fds, pmesh);
local_mf_mass_qf<DIM> local_qfn;
dop.AddDomainIntegrator<LocalQFBackend>(
local_qfn, IT {}, OT {}, *ir, all_domain_attr, DT {});
if constexpr(!mfem_use_gpu)
{
global_mf_mass_qf<DIM> global_qfn;
dop.AddDomainIntegrator<GlobalQFBackend>(
global_qfn, IT {}, OT {}, *ir, all_domain_attr, DT {});
}
MultiVector MX{X, N}, MZ{Z}, MdZ{dZ};
// without cache
{
blf.Mult(x, y);
pfes.GetProlongationMatrix()->MultTranspose(y, Y);
const bool no_cache = false;
auto ddop_nc = dop.GetDerivative(U, MX, no_cache);
ddop_nc->Mult(MX[0], MdZ);
Y -= dZ;
y.SetFromTrueDofs(Y);
REQUIRE(y.ComputeMaxError(zero) == MFEM_Approx(0.0));
}
// allow using the setup cache
{
blf.Mult(x, y);
pfes.GetProlongationMatrix()->MultTranspose(y, Y);
const bool use_cache = true;
auto ddop_wc = dop.GetDerivative(U, MX, use_cache);
ddop_wc->Mult(MX[0], MdZ);
Y -= dZ;
y.SetFromTrueDofs(Y);
REQUIRE(y.ComputeMaxError(zero) == MFEM_Approx(0.0));
}
}
SECTION("Assemble Diagonal")
{
DifferentiableOperator dop(in_fds, out_fds, pmesh);
local_mf_mass_qf<DIM> local_qfn;
dop.AddDomainIntegrator<LocalQFBackend>(
local_qfn, IT {}, OT {}, *ir, all_domain_attr, DT {});
if constexpr(!mfem_use_gpu)
{
global_mf_mass_qf<DIM> global_qfn;
dop.AddDomainIntegrator<GlobalQFBackend>(
global_qfn, IT {}, OT {}, *ir, all_domain_attr, DT {});
}
pfes.GetRestrictionMatrix()->Mult(x, X);
MultiVector MX{X, N};
auto dRdU = dop.GetDerivative(U, MX);
Vector dfem_D(tvsize), mfem_D(tvsize);
dRdU->AssembleDiagonal(dfem_D);
blf.AssembleDiagonal(mfem_D);
Y = mfem_D;
Y -= dfem_D;
y.SetFromTrueDofs(Y);
REQUIRE(y.ComputeMaxError(zero) == MFEM_Approx(0.0));
}
// Test boundary
#if 0 // TODO: Boundary tests
// This ensures that we're not trying to test on fully periodic meshes
if (!((std::string("../../data/periodic-square.mesh").compare(filename) == 0) ||
(std::string("../../data/periodic-cube.mesh").compare(filename) == 0)))
{
constexpr int BDIM = DIM - 1;
SECTION("boundary")
{
Array<int> all_bdr_attr;
if (pmesh.bdr_attributes.Size() > 0)
{
all_bdr_attr.SetSize(pmesh.bdr_attributes.Max());
all_bdr_attr = 1;
}
ParBilinearForm blf(&pfes);
blf.AddBoundaryIntegrator(new MassIntegrator(one, ir));
blf.SetAssemblyLevel(AssemblyLevel::PARTIAL);
blf.Assemble();
blf.Mult(x, y);
pfes.GetProlongationMatrix()->MultTranspose(y, Y);
static constexpr int U = 0, Coords = 1;
const auto in_fds = std::vector<FieldDescriptor> {{ U, &pfes }, { Coords, mfes }};
const auto out_fds = std::vector<FieldDescriptor> {{ U, &pfes }};
DifferentiableOperator dop(in_fds, out_fds, pmesh);
const auto mf_mass_qf =
[] MFEM_HOST_DEVICE(const dscalar_t &u,
const tensor<real_t, DIM, BDIM> &J,
const real_t &w,
dscalar_t& v)
{
v = u * weight(J) * w;
};
auto derivatives = std::integer_sequence<size_t, U> {};
dop.AddBoundaryIntegrator<QFBackend>(mf_mass_qf,
tuple{ Value<U>{}, Gradient<Coords>{}, Weight{} },
tuple{ Value<U>{} },
*ir, all_bdr_attr, derivatives);
pfes.GetRestrictionMatrix()->Mult(x, X);
Vector N;
nodes->GetTrueDofs(N);
MultiVector MX{X, N}, MZ{Z};
dop.Mult(MX, MZ);
Y -= MZ[0];
real_t norm_g, norm_l = Y.Normlinf();
MPI_Allreduce(&norm_l, &norm_g, 1, MPI_DOUBLE, MPI_MAX, pmesh.GetComm());
REQUIRE(norm_g == MFEM_Approx(0.0));
nodes->GetTrueDofs(N);
auto dRdU = dop.GetDerivative(U, MX);
dRdU->Mult(MX[0], MZ);
pfes.GetProlongationMatrix()->MultTranspose(y, Y);
Y -= Z;
norm_l = Y.Normlinf();
MPI_Allreduce(&norm_l, &norm_g, 1, MPI_DOUBLE, MPI_MAX, pmesh.GetComm());
REQUIRE(norm_g == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
}
#endif // TODO: Boundary tests
}
// ────────────────────────────────────────────────────────────────────────────
template <int DIM>
void vector_mass_action(const char *filename, int p)
{
CAPTURE(filename, DIM, p);
Mesh smesh(filename);
ParMesh pmesh(MPI_COMM_WORLD, smesh);
MFEM_VERIFY(pmesh.Dimension() == DIM, "Mesh dimension mismatch");
pmesh.EnsureNodes();
auto* nodes = static_cast<ParGridFunction*>(pmesh.GetNodes());
smesh.Clear();
p = std::max(p, pmesh.GetNodalFESpace()->GetMaxElementOrder());
Array<int> all_domain_attr;
if (pmesh.attributes.Size() > 0)
{
all_domain_attr.SetSize(pmesh.attributes.Max());
all_domain_attr = 1;
}
ParFiniteElementSpace *mfes = nodes->ParFESpace();
const auto *ir = &IntRules.Get(pmesh.GetTypicalElementGeometry(), 2 * p);
H1_FECollection fec(p, DIM);
ParFiniteElementSpace vpfes(&pmesh, &fec, DIM);
const int tvsize = vpfes.GetTrueVSize();
ParGridFunction x(&vpfes), y(&vpfes), z(&vpfes);
Vector X(tvsize), Y(tvsize), Z(tvsize), dZ(tvsize);
X.Randomize(1);
x.SetFromTrueDofs(X);
ConstantCoefficient one(1.0), zero(0.0);
ParBilinearForm blf(&vpfes);
blf.AddDomainIntegrator(new VectorMassIntegrator(one, ir));
blf.SetAssemblyLevel(AssemblyLevel::PARTIAL);
blf.Assemble();
static constexpr int U = 0, Coords = 1;
const auto in_fds = std::vector
{
FieldDescriptor{ U, &vpfes },
FieldDescriptor{ Coords, mfes }
};
const auto out_fds = std::vector{ FieldDescriptor{ U, &vpfes } };
Vector N;
nodes->GetTrueDofs(N);
using IT = Inputs<Value<U>, Gradient<Coords>, Weight>;
using OT = Outputs<Value<U>>;
SECTION("Vector Mass Action")
{
blf.Mult(x, y);
vpfes.GetProlongationMatrix()->MultTranspose(y, Y);
DifferentiableOperator dop(in_fds, out_fds, pmesh);
local_mf_vector_mass_qf<DIM> local_qfn;
dop.AddDomainIntegrator<LocalQFBackend>(
local_qfn, IT {}, OT {}, *ir, all_domain_attr);
MultiVector MX{X, N}, MZ{Z};
dop.Mult(MX, MZ);
Y -= Z;
y.SetFromTrueDofs(Y);
REQUIRE(y.ComputeMaxError(zero) == MFEM_Approx(0.0));
}
}
// ────────────────────────────────────────────────────────────────────────────
template <int DIM>
void mass_mat_mixed(const char* filename, int p)
{
CAPTURE(filename, DIM, p);
Mesh smesh(filename);
ParMesh pmesh(MPI_COMM_WORLD, smesh);
MFEM_VERIFY(pmesh.Dimension() == DIM, "Mesh dimension mismatch");
pmesh.EnsureNodes();
auto* nodes = static_cast<ParGridFunction*>(pmesh.GetNodes());
smesh.Clear();
p = std::max(p, pmesh.GetNodalFESpace()->GetMaxElementOrder());
Array<int> all_domain_attr;
if (pmesh.attributes.Size() > 0)
{
all_domain_attr.SetSize(pmesh.attributes.Max());
all_domain_attr = 1;
}
ParFiniteElementSpace *mfes = nodes->ParFESpace();
const auto* ir = &IntRules.Get(pmesh.GetTypicalElementGeometry(), 2 * p);
H1_FECollection fec0(p, DIM);
H1_FECollection fec1(p + 1, DIM);
ParFiniteElementSpace fes0(&pmesh, &fec0);
ParFiniteElementSpace fes1(&pmesh, &fec1);
const auto* ir = &IntRules.Get(pmesh.GetTypicalElementGeometry(), 2 * p);
ConstantCoefficient one(1.0);
ParMixedBilinearForm blf(&fes1, &fes0);
blf.AddDomainIntegrator(new MassIntegrator(one, ir));
blf.SetAssemblyLevel(AssemblyLevel::FULL);
blf.Assemble();
blf.Finalize();
blf.SpMat().Finalize();
static constexpr int U = 0, P = 1, Coords = 2;
const auto sol = std::vector{FieldDescriptor{U, &fes1}};
DifferentiableOperator dop(sol, {{P, &fes0}, {Coords, nodes->ParFESpace()}},
pmesh);
const auto mf_mass_qf = [] MFEM_HOST_DEVICE(
const dscalar_t& u,
const tensor<real_t, DIM, DIM>& J,
const real_t& w)
DifferentiableOperator dop(
{ { U, &fes1 }, { Coords, mfes } },
{ { P, &fes0 } }, pmesh);
local_mf_mass_qf<DIM> local_qfn;
dop.AddDomainIntegrator<LocalQFBackend>(
local_qfn,
Inputs<Value<U>, Gradient<Coords>, Weight> {},
Outputs<Value<P>> {},
*ir, all_domain_attr,
Derivatives<U> {});
ParGridFunction ugf(&fes1), pgf(&fes0);
ugf = 0.0, pgf = 0.0;
Vector xtvec(fes1.GetTrueVSize()), ytvec(fes0.GetTrueVSize());
Vector nodestv;
xtvec.Randomize(1);
ugf.SetFromTrueDofs(xtvec);
nodes->GetTrueDofs(nodestv);
fes1.GetRestrictionMatrix()->Mult(ugf, xtvec);
MultiVector X{xtvec, nodestv};
auto ddopdu = dop.GetDerivative(U, X, false);
SECTION("Action Linearized")
{
return tuple{u * w * det(J)};
};
xtvec.Randomize(567);
ugf.SetFromTrueDofs(xtvec);
auto derivatives = std::integer_sequence<size_t, U> {};
dop.AddDomainIntegrator(mf_mass_qf,
tuple{Value<U>{}, Gradient<Coords>{}, Weight{}},
tuple{Value<P>{}},
*ir, all_domain_attr, derivatives);
Vector dztvec(fes0.GetTrueVSize());
MultiVector DZ{dztvec};
ddopdu->Mult(X[0], DZ);
ParGridFunction ugf(&fes1);
ugf = 0.0;
blf.Mult(ugf, pgf);
fes0.GetProlongationMatrix()->MultTranspose(pgf, ytvec);
ParGridFunction pgf(&fes0);
pgf = 0.0;
ytvec -= dztvec;
dop.SetParameters({&pgf, nodes});
real_t norm_global = 0.0;
real_t norm_local = ytvec.Normlinf();
MPI_Allreduce(&norm_local, &norm_global, 1, MPI_DOUBLE, MPI_MAX,
pmesh.GetComm());
auto ddopdu = dop.GetDerivative(U, {&ugf}, {&pgf, nodes});
REQUIRE(norm_global == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
SECTION("spmat")
SECTION("MFEM SparseMatrix")
{
SparseMatrix *A;
ddopdu->Assemble(A);
@@ -224,7 +489,8 @@ template <int DIM> void mass_mat_mixed(const char* filename, int p)
delete A;
}
SECTION("hypre parallel mat")
// TODO Hypre parallel matrix
if constexpr(false && !mfem_use_gpu)
{
HypreParMatrix *Amfem = blf.ParallelAssemble();
@@ -236,39 +502,52 @@ template <int DIM> void mass_mat_mixed(const char* filename, int p)
}
}
// no GPU tag to avoid failing 'hypre parallel mat' section
TEST_CASE("dFEM Mass", "[Parallel][dFEM]")
// ────────────────────────────────────────────────────────────────────────────
TEST_CASE("dFEM Mass 2D", "[Parallel][dFEM][GPU]")
{
const bool all_tests = launch_all_non_regression_tests;
const auto p = GenAll({1}, {2, 3});
const auto meshs = { "../../data/inline-quad.mesh" };
const auto extra = { "../../data/star.mesh",
"../../data/star-q3.mesh",
"../../data/rt-2d-q3.mesh",
"../../data/periodic-square.mesh"
};
const auto p = !all_tests ? 2 : GENERATE(1, 2, 3);
SECTION("2d")
SECTION("Scalar Mass")
{
const auto filename2d =
GENERATE(
"../../data/star.mesh",
"../../data/star-q3.mesh",
"../../data/rt-2d-q3.mesh",
"../../data/inline-quad.mesh",
"../../data/periodic-square.mesh"
);
mass_action<2>(filename2d, p);
mass_mat_mixed<2>(filename2d, p);
mass_action<2>(GenAll(meshs, extra), p);
}
SECTION("3d")
SECTION("Scalar Mass Mixed")
{
const auto filename3d =
GENERATE(
"../../data/fichera.mesh",
"../../data/fichera-q3.mesh",
"../../data/inline-hex.mesh",
"../../data/toroid-hex.mesh",
"../../data/periodic-cube.mesh"
);
mass_action<3>(filename3d, p);
mass_mat_mixed<3>(filename3d, p);
mass_mat_mixed<2>(GenAll(meshs, extra), p);
}
SECTION("Vector Mass")
{
vector_mass_action<2>(GenAll(meshs, extra), p);
}
}
// ────────────────────────────────────────────────────────────────────────────
TEST_CASE("dFEM Mass 3D", "[Parallel][dFEM][GPU]")
{
const auto p = GenAll({1}, {2, 3});
const auto meshs = { "../../data/inline-hex.mesh" };
const auto extra = { "../../data/fichera.mesh",
"../../data/fichera-q3.mesh",
"../../data/toroid-hex.mesh",
"../../data/periodic-cube.mesh"
};
SECTION("Scalar Mass")
{
mass_action<3>(GenAll(meshs, extra), p);
}
SECTION("Scalar Mass Mixed")
{
mass_mat_mixed<3>(GenAll(meshs, extra), p);
}
SECTION("Vector Mass")
{
vector_mass_action<3>(GenAll(meshs, extra), p);
}
}
+213
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@@ -0,0 +1,213 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "../unit_tests.hpp"
#include "mfem.hpp"
#ifdef MFEM_USE_MPI
#include "../../../fem/dfem/doperator.hpp"
#include "../../../fem/dfem/backends/local_qf/prelude.hpp"
using namespace mfem;
using namespace mfem::future;
#ifdef MFEM_USE_ENZYME
using dscalar_t = real_t;
#else
using dscalar_t = dual<real_t, real_t>;
#endif
// ────────────────────────────────────────────────────────────────────────────
template<int DIM, typename ValSeq, typename GradSeq>
struct multiply_inputs_qf;
template<int DIM, std::size_t... Vs, std::size_t... Gs>
struct multiply_inputs_qf<DIM, std::index_sequence<Vs...>,
std::index_sequence<Gs...>>
{
template<std::size_t>
using value_t = const dscalar_t &;
template<std::size_t>
using gradient_t = const tensor<dscalar_t, DIM> &;
inline MFEM_HOST_DEVICE void operator()(
const tensor<real_t, DIM, DIM> &J,
value_t<Vs>... vs,
gradient_t<Gs>... gs,
const real_t &w,
dscalar_t &v) const
{
v = (vs * ...) * (real_t{1} + (w - w) * (gs(0) + ...)) * w * det(J);
}
};
template<int DIM, std::size_t Nv, std::size_t Ng>
using multiply_inputs_qf_t =
multiply_inputs_qf<DIM,
std::make_index_sequence<Nv>,
std::make_index_sequence<Ng>>;
// ────────────────────────────────────────────────────────────────────────────
template<int I>
using Values = Value<I>;
template<int I>
using Gradients = Gradient<I>;
template<int... Vs, int... Gs>
constexpr auto make_inputs(std::integer_sequence<int, Vs...>,
std::integer_sequence<int, Gs...>)
{
return Inputs<Gradient<0>, Values<1 + Vs>...,
Gradients<1 + sizeof...(Vs) + Gs>..., Weight> {};
}
// ────────────────────────────────────────────────────────────────────────────
struct InputsTestContext
{
ParMesh &pmesh;
ParFiniteElementSpace &pfes;
ParFiniteElementSpace *mfes;
const IntegrationRule &ir;
Array<int> &all_domain_attr;
const Vector &Y_ref;
Vector &N_vec;
Vector &input;
int tvsize;
};
// ────────────────────────────────────────────────────────────────────────────
template<int DIM, std::size_t Nv, std::size_t Ng>
void test_nv_ng_inputs(const InputsTestContext &ctx)
{
constexpr std::size_t Ni = Nv + Ng;
// inputs & output
std::vector<FieldDescriptor> in_fds;
in_fds.reserve(Ni + 1);
in_fds.emplace_back(0, ctx.mfes); // Coords
for (std::size_t i = 1; i <= Ni; ++i)
{
in_fds.emplace_back(i, &ctx.pfes);
}
const auto out_fds = std::vector{ FieldDescriptor{ 1, &ctx.pfes } };
// Prepare the MultiVector inputs
Array<int> mx_sizes(Ni + 1);
mx_sizes[0] = ctx.N_vec.Size(); // Coords
for (std::size_t i = 1; i <= Ni; ++i) { mx_sizes[i] = ctx.tvsize; }
MultiVector MX;
MX.SetSizes(mx_sizes);
MX.MakeRef(0, ctx.N_vec);
for (std::size_t i = 1; i <= Ni; ++i)
{
MX.MakeRef(static_cast<int>(i), ctx.input);
}
using IT = decltype(make_inputs(
std::make_integer_sequence<int, Nv> {},
std::make_integer_sequence<int, Ng> {}));
using OT = Outputs<Value<1>>;
multiply_inputs_qf_t<DIM, Nv, Ng> qfn;
DifferentiableOperator dop(in_fds, out_fds, ctx.pmesh);
dop.AddDomainIntegrator<LocalQFBackend>(
qfn, IT{}, OT{}, ctx.ir, ctx.all_domain_attr);
Vector Z(ctx.tvsize);
MultiVector MZ{ Z };
dop.Mult(MX, MZ);
Vector Y_diff(ctx.Y_ref);
Y_diff -= Z;
ParGridFunction y(&ctx.pfes);
ConstantCoefficient zero(0.0);
y.SetFromTrueDofs(Y_diff);
REQUIRE(y.ComputeMaxError(zero) == MFEM_Approx(0.0));
}
// ────────────────────────────────────────────────────────────────────────────
void test_multiple_inputs(int p)
{
static constexpr int DIM = 2;
CAPTURE(DIM, p);
Mesh smesh("../../data/inline-quad.mesh");
ParMesh pmesh(MPI_COMM_WORLD, smesh);
MFEM_VERIFY(pmesh.Dimension() == DIM, "Mesh dimension mismatch");
pmesh.EnsureNodes();
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
smesh.Clear();
Array<int> all_domain_attr;
if (pmesh.attributes.Size() > 0)
{
all_domain_attr.SetSize(pmesh.attributes.Max());
all_domain_attr = 1;
}
ParFiniteElementSpace *mfes = nodes->ParFESpace();
const auto &ir = IntRules.Get(pmesh.GetTypicalElementGeometry(), 2 * p);
H1_FECollection fec(p, DIM);
ParFiniteElementSpace pfes(&pmesh, &fec);
const int tvsize = pfes.GetTrueVSize();
ParGridFunction x(&pfes), y(&pfes);
Vector X_ref(tvsize), Y_ref(tvsize);
X_ref = 1.0;
x.SetFromTrueDofs(X_ref);
ConstantCoefficient one(1.0);
ParBilinearForm blf(&pfes);
blf.AddDomainIntegrator(new MassIntegrator(one, &ir));
blf.SetAssemblyLevel(AssemblyLevel::PARTIAL);
blf.Assemble();
blf.Mult(x, y);
pfes.GetProlongationMatrix()->MultTranspose(y, Y_ref);
Vector N_vec;
nodes->GetTrueDofs(N_vec);
Vector input(tvsize);
input = 1.0;
const InputsTestContext ctx
{
pmesh, pfes, mfes, ir, all_domain_attr, Y_ref, N_vec, input, tvsize
};
// with current dFEM tuple: max 9 = J + 3 + 3 + weights + output
#ifndef _WIN32
test_nv_ng_inputs<DIM, 3, 3>(ctx);
#else
// avoiding 'number of sections exceeded object file format limit' error
test_nv_ng_inputs<DIM, 2, 2>(ctx);
#endif // _WIN32
}
// ────────────────────────────────────────────────────────────────────────────
TEST_CASE("dFEM Inputs", "[Parallel][dFEM][GPU]")
{
const auto p = GenAll({1}, {2, 3, 8});
test_multiple_inputs(p);
}
#endif // MFEM_USE_MPI
+495
View File
@@ -0,0 +1,495 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include <memory>
#include "../unit_tests.hpp"
#include "mfem.hpp"
#ifdef MFEM_USE_MPI
#include "../../../fem/dfem/doperator.hpp"
#include "../../../fem/dfem/backends/local_qf/prelude.hpp"
#include "../../../linalg/tensor_arrays.hpp"
using namespace mfem;
using namespace mfem::future;
#ifdef MFEM_USE_ENZYME
using dscalar_t = real_t;
#else
using dscalar_t = dual<real_t, real_t>;
#endif
constexpr int DIM = 2;
class DummyParameterSpace : public ParameterSpace
{
public:
class Bimpl : public Operator
{
void Mult(const Vector &x, Vector &y) const override
{
const bool use_dev = x.UseDevice() || y.UseDevice();
const auto xr = x.Read(use_dev);
auto yw = y.Write(use_dev);
mfem::forall_switch(use_dev, y.Size(), [=] MFEM_HOST_DEVICE (int i)
{
yw[i] = xr[0];
});
}
};
class Btimpl : public Operator
{
void Mult(const Vector &x, Vector &y) const override
{
const bool use_dev = x.UseDevice() || y.UseDevice();
const auto xr = x.Read(use_dev);
auto yw = y.Write(use_dev);
mfem::forall_switch(use_dev, 1, [=] MFEM_HOST_DEVICE (int)
{
yw[0] = xr[0];
});
}
};
DummyParameterSpace() : ParameterSpace(1) {}
int GetTrueVSize() const override
{
return 1;
}
int GetVSize() const override
{
return 1;
}
const Operator* GetB() const override
{
if (!B)
{
B = std::make_unique<Bimpl>();
}
return B.get();
}
const Operator* GetBt() const override
{
if (!Bt)
{
Bt = std::make_unique<Btimpl>();
}
return Bt.get();
}
};
/*struct mass_global_qf
{
void operator()(
tensor_array<const dscalar_t> &u,
tensor_array<const real_t, DIM, DIM> &J,
tensor_array<const real_t> &w,
tensor_array<dscalar_t> &out1,
tensor_array<dscalar_t> &out2) const
{
mfem::forall(u.size(), [=] MFEM_HOST_DEVICE (int q)
{
const auto v = u(q) * det(J(q)) * w(q);
out1(q) = v;
out2(q) = v;
});
}
};*/
// __enzyme_fwddiff(.....
struct mass_diffusion_global_qf
{
void operator()(
tensor_array<const dscalar_t> &u,
tensor_array<const dscalar_t, DIM> &dudxi,
tensor_array<const real_t, DIM, DIM> &J,
[[maybe_unused]] tensor_array<const real_t, DIM, DIM> &qdata,
tensor_array<const real_t> &w,
[[maybe_unused]] tensor_array<const real_t> &dummy_parameter,
tensor_array<dscalar_t> &out1,
tensor_array<dscalar_t, DIM> &out2,
tensor_array<real_t, DIM, DIM> &out3) const
{
mfem::forall<UseEnzyme>(u.size(), [=] MFEM_HOST_DEVICE (int q)
{
const auto invJq = inv(J(q));
const auto detJq = det(J(q));
const real_t weight = detJq * w(q);
out1(q) = u(q) * weight;
out2(q) = (dudxi(q) * invJq) * transpose(invJq) * (detJq * w(q));
out3(q) = J(q);
});
}
};
// ..... );
struct mass_local_qf
{
inline MFEM_HOST_DEVICE
void operator()(
const dscalar_t &u,
const tensor<real_t, DIM, DIM> &J,
const real_t &w,
dscalar_t &out1,
dscalar_t &out2) const
{
const auto v = u * det(J) * w;
out1 = v;
out2 = v;
}
};
struct mass_diffusion_local_qf
{
inline MFEM_HOST_DEVICE
void operator()(
const real_t &u,
const tensor<real_t, DIM> &dudxi,
const tensor<real_t, DIM, DIM> &J,
const real_t &w,
real_t &out1,
tensor<real_t, DIM> &out2) const
{
const auto invJ = inv(J);
const auto detJ = det(J);
out1 = u * detJ * w;
out2 = (dudxi * invJ) * transpose(invJ) * (detJ * w);
}
};
TEST_CASE("dFEM Multiple Outputs", "[Parallel][dFEM][GPU]")
{
const bool all_tests = launch_all_non_regression_tests;
const auto p = !all_tests ? 2 : GENERATE(1, 2, 3);
const char *filename = "../../data/inline-quad.mesh";
CAPTURE(filename, DIM, p);
Mesh smesh(filename);
MFEM_ASSERT(smesh.Dimension() == DIM, "DIM and mesh dimension have to match");
ParMesh pmesh(MPI_COMM_WORLD, smesh);
pmesh.EnsureNodes();
auto* nodes = static_cast<ParGridFunction*>(pmesh.GetNodes());
smesh.Clear();
H1_FECollection fec(p, DIM);
ParFiniteElementSpace fes(&pmesh, &fec);
const auto *ir = &IntRules.Get(pmesh.GetTypicalElementGeometry(), 2 * p);
ParGridFunction x(&fes), y(&fes), z(&fes);
ConstantCoefficient one(1.0);
Array<int> all_domain_attr;
if (pmesh.attributes.Size() > 0)
{
all_domain_attr.SetSize(pmesh.attributes.Max());
all_domain_attr = 1;
}
// {
// Array<int> inoffsets(3);
// inoffsets[0] = 0;
// inoffsets[1] = fes.GetTrueVSize();
// inoffsets[2] = nodes->ParFESpace()->GetTrueVSize();
// inoffsets.PartialSum();
// BlockVector X(inoffsets);
// X.GetBlock(0).Randomize(1);
// X.GetBlock(1) = *nodes;
// x.SetFromTrueDofs(X.GetBlock(0));
// Array<int> outoffsets(2);
// outoffsets[0] = 0;
// outoffsets[1] = fes.GetTrueVSize();
// outoffsets.PartialSum();
// BlockVector Z(outoffsets);
// ParBilinearForm blf(&fes);
// blf.AddDomainIntegrator(new MassIntegrator(one, ir));
// blf.SetAssemblyLevel(AssemblyLevel::PARTIAL);
// blf.Assemble();
// blf.Mult(x, y);
// Vector Y(fes.GetTrueVSize());
// fes.GetProlongationMatrix()->MultTranspose(y, Y);
// static constexpr int U = 0, COORDINATES = 1, V = 2;
// const std::vector<FieldDescriptor> in
// {
// {U, &fes},
// {COORDINATES, nodes->ParFESpace()}
// };
// const std::vector<FieldDescriptor> out // test spaces?
// {
// {V, &fes},
// };
// DifferentiableOperator dop(in, out, pmesh);
// auto derivatives = std::integer_sequence<size_t, U> {};
// auto mass_qfunc = massqf{};
// dop.AddDomainIntegrator(mass_qfunc,
// tuple{ Value<U>{}, Gradient<COORDINATES>{}, Weight{} },
// tuple{ Value<V>{}, Value<V>{} },
// *ir, all_domain_attr, derivatives);
// fes.GetRestrictionMatrix()->Mult(x, X.GetBlock(0));
// dop.Mult(X, Z);
// Vector Y0(Y);
// Y0 *= 2.0;
// Y0 -= Z.GetBlock(0);
// real_t norm_g, norm_l = Y0.Normlinf();
// MPI_Allreduce(&norm_l, &norm_g, 1, MPI_DOUBLE, MPI_MAX, pmesh.GetComm());
// REQUIRE(norm_g == MFEM_Approx(0.0));
// MPI_Barrier(MPI_COMM_WORLD);
// auto ddop = dop.GetDerivative(U, X);
// ddop->Mult(X.GetBlock(0), Z);
// Y0 = Y;
// Y0 *= 2.0;
// Y0 -= Z.GetBlock(0);
// norm_l = Y0.Normlinf();
// MPI_Allreduce(&norm_l, &norm_g, 1, MPI_DOUBLE, MPI_MAX, pmesh.GetComm());
// REQUIRE(norm_g == MFEM_Approx(0.0));
// MPI_Barrier(MPI_COMM_WORLD);
// }
{
QuadratureSpace qs(pmesh, *ir);
VectorQuadratureSpace vqs(qs, DIM * DIM);
QuadratureFunction qdata(vqs);
DummyParameterSpace dps;
ParameterFunction dpf(dps);
dpf = 9.12345;
auto coef_func = [](const Vector &coords)
{
return coords[0] * coords[1] * (DIM == 3 ? coords[2] : 1.0);
};
FunctionCoefficient coef(coef_func);
x.ProjectCoefficient(coef);
Vector xtvec, ytvec, ytvecmfem;
x.GetTrueDofs(xtvec);
ytvec.SetSize(xtvec.Size());
ytvecmfem.SetSize(xtvec.Size());
Vector nodestvec;
nodes->GetTrueDofs(nodestvec);
qdata = 123.0;
Vector yqdata(qdata.Size());
static constexpr int U = 0, COORDINATES = 1, V = 2, S = 3, L = 4;
#if !defined(MFEM_USE_HIP)
{
xtvec.UseDevice(true);
nodestvec.UseDevice(true);
qdata.UseDevice(true);
dpf.UseDevice(true);
ytvec.UseDevice(true);
yqdata.UseDevice(true);
MultiVector X{xtvec, nodestvec, qdata, dpf};
MultiVector Z{ytvec, yqdata};
ParBilinearForm blf(&fes);
blf.AddDomainIntegrator(new MassIntegrator(ir));
blf.AddDomainIntegrator(new DiffusionIntegrator(ir));
blf.SetAssemblyLevel(AssemblyLevel::PARTIAL);
blf.Assemble();
blf.Mult(x, y);
fes.GetProlongationMatrix()->MultTranspose(y, ytvecmfem);
const std::vector<FieldDescriptor> in_fds
{
{U, &fes},
{COORDINATES, nodes->ParFESpace()},
{S, &vqs},
{L, &dps}
};
const std::vector<FieldDescriptor> out_fds
{
{V, &fes},
{S, &vqs}
};
DifferentiableOperator dop(in_fds, out_fds, pmesh);
dop.SetQLayouts({{Value<U>{}, {1, 0}}}, {});
auto derivatives = Derivatives<U> {};
auto mass_diffusion_qfunc = mass_diffusion_global_qf{};
dop.AddDomainIntegrator(
mass_diffusion_qfunc,
Inputs<Value<U>, Gradient<U>, Gradient<COORDINATES>, Identity<S>, Weight, Value<L>> {},
Outputs<Value<V>, Gradient<V>, Identity<S>> {},
*ir, all_domain_attr, derivatives);
fes.GetRestrictionMatrix()->Mult(x, xtvec);
dop.Mult(X, Z);
Vector Y0(ytvecmfem);
Y0.UseDevice(true);
Y0 -= Z[0];
real_t norm_l = Y0.Normlinf();
real_t norm_g = norm_l;
MPI_Allreduce(&norm_l, &norm_g, 1, MPI_DOUBLE, MPI_MAX, pmesh.GetComm());
REQUIRE(norm_g == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
auto ddop = dop.GetDerivative(U, X);
ddop->Mult(X[0], Z);
Z[0].HostRead();
Y0 = ytvecmfem;
Y0.HostRead();
Y0 -= Z[0];
norm_l = Y0.Normlinf();
norm_g = norm_l;
MPI_Allreduce(&norm_l, &norm_g, 1, MPI_DOUBLE, MPI_MAX, pmesh.GetComm());
REQUIRE(norm_g == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
#endif
{
static constexpr int W = 0;
ParBilinearForm blf(&fes);
blf.AddDomainIntegrator(new MassIntegrator(ir));
blf.SetAssemblyLevel(AssemblyLevel::PARTIAL);
blf.Assemble();
blf.Mult(x, y);
fes.GetProlongationMatrix()->MultTranspose(y, ytvecmfem);
const std::vector<FieldDescriptor> in_fds
{
{U, &fes},
{COORDINATES, nodes->ParFESpace()},
};
const std::vector<FieldDescriptor> out_fds
{
{V, &fes},
{W, &fes},
};
DifferentiableOperator dop(in_fds, out_fds, pmesh);
auto mass_qfunclocal = mass_local_qf{};
dop.AddDomainIntegrator<LocalQFBackend>(
mass_qfunclocal,
tuple{Value<U>{}, Gradient<COORDINATES>{}, Weight{}},
tuple{Value<V>{}, Value<W>{}},
*ir, all_domain_attr);
Vector nodestv;
nodes->GetTrueDofs(nodestv);
fes.GetRestrictionMatrix()->Mult(x, xtvec);
Vector ztvec(xtvec.Size());
Vector zztvec(xtvec.Size());
MultiVector X{xtvec, nodestv};
MultiVector Z{ztvec, zztvec};
dop.Mult(X, Z);
Vector Y0(ytvecmfem);
Y0 -= Z[0];
real_t norm_l = Y0.Normlinf();
real_t norm_g = norm_l;
MPI_Allreduce(&norm_l, &norm_g, 1, MPI_DOUBLE, MPI_MAX, pmesh.GetComm());
REQUIRE(norm_g == MFEM_Approx(0.0));
Vector Y1(ytvecmfem);
Y1 -= Z[1];
norm_l = Y1.Normlinf();
norm_g = norm_l;
MPI_Allreduce(&norm_l, &norm_g, 1, MPI_DOUBLE, MPI_MAX, pmesh.GetComm());
REQUIRE(norm_g == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
{
ParBilinearForm blf(&fes);
blf.AddDomainIntegrator(new MassIntegrator(ir));
blf.AddDomainIntegrator(new DiffusionIntegrator(ir));
blf.SetAssemblyLevel(AssemblyLevel::PARTIAL);
blf.Assemble();
blf.Mult(x, y);
fes.GetProlongationMatrix()->MultTranspose(y, ytvecmfem);
const std::vector<FieldDescriptor> in_fds
{
{U, &fes},
{COORDINATES, nodes->ParFESpace()},
};
const std::vector<FieldDescriptor> out_fds
{
{V, &fes},
};
DifferentiableOperator dop(in_fds, out_fds, pmesh);
auto mass_diffusion_qfunclocal = mass_diffusion_local_qf{};
dop.AddDomainIntegrator<LocalQFBackend>(
mass_diffusion_qfunclocal,
tuple{Value<U>{}, Gradient<U>{}, Gradient<COORDINATES>{}, Weight{}},
tuple{Value<V>{}, Gradient<V>{}},
*ir, all_domain_attr);
Vector nodestv;
nodes->GetTrueDofs(nodestv);
fes.GetRestrictionMatrix()->Mult(x, xtvec);
Vector ztvec(xtvec.Size());
MultiVector X{xtvec, nodestv};
MultiVector Z{ztvec};
dop.Mult(X, Z);
Vector Y0(ytvecmfem);
Y0 -= Z[0];
real_t norm_l = Y0.Normlinf();
real_t norm_g = norm_l;
MPI_Allreduce(&norm_l, &norm_g, 1, MPI_DOUBLE, MPI_MAX, pmesh.GetComm());
REQUIRE(norm_g == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
}
}
#endif // MFEM_USE_MPI
+680
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// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "../unit_tests.hpp"
#include "mfem.hpp"
#ifdef MFEM_USE_ENZYME
#include "../../../fem/dfem/doperator.hpp"
#include "../../../fem/dfem/backends/local_qf/prelude.hpp"
#include "../../../fem/dfem/backends/local_qf/revdiff_transformer.hpp"
#ifdef MFEM_USE_MPI
using namespace mfem;
using namespace mfem::future;
using mfem::future::tensor;
#ifdef MFEM_USE_ENZYME
using dscalar_t = real_t;
#else
using mfem::future::dual;
using dscalar_t = dual<real_t, real_t>;
#endif
namespace second_derivative_test
{
template <typename dscalar_t, int dim>
struct MinimalSurfaceEnergyFunctional
{
MFEM_HOST_DEVICE inline __attribute__((always_inline))
auto operator()(const dscalar_t &u,
const tensor<dscalar_t, dim> &dudxi,
const tensor<real_t, dim, dim> &J,
const real_t &w,
real_t &f /* dfdu, dfddudxi */
) const
{
const auto invJ = inv(J);
const auto dudx = dudxi * invJ;
const auto dx = det(J) * w;
const auto E = sqrt(1.0_r + sqnorm(dudx));
f = E * dx;
}
};
template <typename dscalar_t, int dim>
struct MinimalSurfaceEnergy
{
MFEM_HOST_DEVICE inline __attribute__((always_inline))
auto operator()(const tensor<dscalar_t, dim> &dudxi,
const tensor<real_t, dim, dim> &J,
const real_t &w,
real_t &f) const
{
const auto invJ = inv(J);
const auto dudx = dudxi * invJ;
const auto dx = det(J) * w;
const auto E = sqrt(1.0_r + sqnorm(dudx));
f = E * dx;
}
};
template <typename dscalar_t, int dim>
struct MinimalSurfaceResidual
{
MFEM_HOST_DEVICE inline __attribute__((always_inline))
auto operator()(const tensor<dscalar_t, dim> &dudxi,
const tensor<real_t, dim, dim> &J,
const real_t &w,
tensor<real_t, dim> &dvdx) const
{
const auto invJ = inv(J);
const auto dudx = dudxi * invJ;
const auto dx = det(J) * w;
dvdx = dudx / (sqrt(1.0_r + sqnorm(dudx))) * transpose(invJ) * dx;
}
};
// Hand-coded action of the second derivative of the minimal surface energy,
// i.e. the Hessian-vector product integrand d^2 J(u)[delta_u, v].
template <typename dscalar_t, int dim>
struct MinimalSurfaceHessianAction
{
MFEM_HOST_DEVICE inline __attribute__((always_inline))
auto operator()(const tensor<real_t, dim> &ddelta_udxi,
const tensor<dscalar_t, dim> &dudxi,
const tensor<real_t, dim, dim> &J,
const real_t &w,
tensor<real_t, dim> &dvdx) const
{
const auto invJ = inv(J);
const auto dudx = dudxi * invJ;
const auto ddelta_udx = ddelta_udxi * invJ;
const auto dx = det(J) * w;
const auto c = 1.0_r / sqrt(1.0_r + sqnorm(dudx));
const auto term1 = c * ddelta_udx;
const auto term2 = c * c * c * dot(dudx, ddelta_udx) * dudx;
dvdx = (term1 - term2) * transpose(invJ) * dx;
}
};
// Functional for the mixed problem with two fields u and rho, with the energy functional:
// J(u, rho) = int (rho u^2 + 0.5 rho^2) dx
template <typename dscalar_t, int dim>
struct MixedFunctional
{
MFEM_HOST_DEVICE inline __attribute__((always_inline))
auto operator()(const dscalar_t &u,
const dscalar_t &rho,
const tensor<real_t, dim, dim> &J,
const real_t &w,
real_t &f) const
{
f = (rho * u * u + 0.5_r * rho * rho) * det(J) * w;
}
};
template <typename dscalar_t, int dim>
struct MixedFunctionalUUAction
{
MFEM_HOST_DEVICE inline __attribute__((always_inline))
auto operator()(const real_t &du,
const dscalar_t &rho,
const tensor<real_t, dim, dim> &J,
const real_t &w,
real_t &v) const
{
v = 2.0_r * rho * du * det(J) * w;
}
};
template <typename dscalar_t, int dim>
struct MixedFunctionalURhoAction
{
MFEM_HOST_DEVICE inline __attribute__((always_inline))
auto operator()(const real_t &drho,
const dscalar_t &u,
const tensor<real_t, dim, dim> &J,
const real_t &w,
real_t &v) const
{
v = 2.0_r * u * drho * det(J) * w;
}
};
template <typename dscalar_t, int dim>
struct MixedFunctionalRhoUAction
{
MFEM_HOST_DEVICE inline __attribute__((always_inline))
auto operator()(const real_t &du,
const dscalar_t &u,
const tensor<real_t, dim, dim> &J,
const real_t &w,
real_t &v) const
{
v = 2.0_r * u * du * det(J) * w;
}
};
template <typename dscalar_t, int dim>
struct MixedFunctionalRhoRhoAction
{
MFEM_HOST_DEVICE inline __attribute__((always_inline))
auto operator()(const real_t &drho,
const tensor<real_t, dim, dim> &J,
const real_t &w,
real_t &v) const
{
v = drho * det(J) * w;
}
};
template <int dim>
class MyFunctional
{
static constexpr int U = 0, Coords = 1, Q = 2, DirU = 3;
public:
MyFunctional(const ParFiniteElementSpace &fes,
const ParFiniteElementSpace &mfes,
const IntegrationRule &ir) :
comm(fes.GetComm()),
mesh(*mfes.GetParMesh()),
qspace(*fes.GetParMesh(), ir),
qspace_vec(qspace, 1),
q(qspace_vec)
{
const auto &pmesh = *fes.GetParMesh();
Array<int> all_domain_attr;
if (pmesh.attributes.Size() > 0)
{
all_domain_attr.SetSize(pmesh.attributes.Max());
all_domain_attr = 1;
}
// Energy
{
const auto in = std::vector
{
FieldDescriptor{U, &fes},
FieldDescriptor{Coords, &mfes}
};
const auto out = std::vector
{
FieldDescriptor{Q, &qspace_vec}
};
functional_dop = std::make_unique<DifferentiableOperator>(in, out, mesh);
MinimalSurfaceEnergyFunctional<real_t, dim> energy;
auto derivatives = std::integer_sequence<size_t, U> {};
auto second_derivatives = std::integer_sequence<size_t, U> {};
functional_dop->AddDomainIntegrator<LocalQFBackend>(
energy,
Inputs<Value<U>, Gradient<U>, Gradient<Coords>, Weight> {},
Outputs<FunctionalValue<Q>> {}, /* Value<U>, Gradient<U> */
ir, all_domain_attr, derivatives /* , second_derivatives */);
}
// Manually computed residual
{
const auto in = std::vector
{
FieldDescriptor{U, &fes},
FieldDescriptor{Coords, &mfes}
};
const auto out = std::vector
{
FieldDescriptor{U, &fes}
};
residual_dop = std::make_unique<DifferentiableOperator>(in, out, pmesh);
MinimalSurfaceResidual<real_t, dim> residual;
auto derivatives = std::integer_sequence<size_t, U> {};
residual_dop->AddDomainIntegrator<LocalQFBackend>(
residual,
tuple{Gradient<U>{}, Gradient<Coords>{}, Weight{}},
tuple{Gradient<U>{}},
ir, all_domain_attr, derivatives);
}
// Differentiated energy representing the residual
{
const auto in = std::vector
{
FieldDescriptor{U, &fes},
FieldDescriptor{Coords, &mfes}
};
const auto out = std::vector
{
FieldDescriptor{U, &fes}
};
dfunctional_dop = std::make_unique<DifferentiableOperator>(in, out, mesh);
// Differentiate output f (argument 3) with respect to dudxi
// (argument 0).
RevDiff<MinimalSurfaceEnergy<real_t, dim>, tuple<Active, Const, Const>, tuple<Active>>
fd;
auto derivatives = std::integer_sequence<size_t, U> {};
dfunctional_dop->AddDomainIntegrator<LocalQFBackend>(
fd,
tuple{Gradient<U>{}, Gradient<Coords>{}, Weight{}},
tuple{Gradient<U>{}},
ir, all_domain_attr, derivatives);
}
// Hand-coded Hessian action with the direction as an explicit field
{
const auto in = std::vector
{
FieldDescriptor{DirU, &fes},
FieldDescriptor{U, &fes},
FieldDescriptor{Coords, &mfes}
};
const auto out = std::vector
{
FieldDescriptor{U, &fes}
};
hessian_dop = std::make_unique<DifferentiableOperator>(in, out, mesh);
MinimalSurfaceHessianAction<real_t, dim> hessian_action;
hessian_dop->AddDomainIntegrator<LocalQFBackend>(
hessian_action,
tuple{Gradient<DirU>{}, Gradient<U>{}, Gradient<Coords>{}, Weight{}},
tuple{Gradient<U>{}},
ir, all_domain_attr);
}
mesh.GetNodes()->GetTrueDofs(coords);
}
void gradient_exact(const Vector &u, Vector &g) const
{
MultiVector X{u, coords};
MultiVector Y{g};
residual_dop->Mult(X, Y);
}
void gradient(const Vector &u, Vector &g) const
{
MultiVector X{u, coords};
MultiVector Y{g};
functional_dop->GetDerivative(U)->Mult(X, Y);
}
// Gradient assembled into a Vector from the state captured by
// GetDerivative, the functional counterpart of Assemble(SparseMatrix *&).
void gradient_assembled(const Vector &u, Vector &g) const
{
MultiVector X{u, coords};
functional_dop->GetDerivative(U, X)->Assemble(g);
}
// Hessian-vector product H(u) v with the hand-coded second derivative.
void hvp_exact(const Vector &u, const Vector &v, Vector &Hv) const
{
MultiVector X{v, u, coords};
MultiVector Y{Hv};
hessian_dop->Mult(X, Y);
}
// H(u) v as the derivative of the hand-coded residual (single AD).
void hvp_dresidual(const Vector &u, const Vector &v, Vector &Hv) const
{
MultiVector X{u, coords};
MultiVector Y{Hv};
residual_dop->GetDerivative(U, X)->Mult(v, Y);
}
// H(u) v as the derivative of the differentiated energy
// (forward-over-reverse AD).
void hvp(const Vector &u, const Vector &v, Vector &Hv) const
{
MultiVector X{u, coords};
MultiVector Y{Hv};
dfunctional_dop->GetDerivative(U, X)->Mult(v, Y);
}
// H(u) v from the functional's second-derivative interface.
void hvp_functional(const Vector &u, const Vector &v, Vector &Hv) const
{
MultiVector X{u, coords};
MultiVector Y{Hv};
functional_dop->GetSecondDerivative(U, X)->Mult(v, Y);
}
private:
MPI_Comm comm;
ParMesh &mesh;
std::unique_ptr<DifferentiableOperator> functional_dop;
std::unique_ptr<DifferentiableOperator> dfunctional_dop;
std::unique_ptr<DifferentiableOperator> residual_dop;
std::unique_ptr<DifferentiableOperator> hessian_dop;
QuadratureSpace qspace;
VectorQuadratureSpace qspace_vec;
mutable QuadratureFunction q;
Vector coords;
};
template <int DIM>
void second_derivative(const char *filename, int p)
{
CAPTURE(filename, DIM, p);
Mesh smesh(filename);
ParMesh pmesh(MPI_COMM_WORLD, smesh);
pmesh.EnsureNodes();
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
ParFiniteElementSpace *mfes = nodes->ParFESpace();
H1_FECollection fec(p, DIM);
ParFiniteElementSpace fes(&pmesh, &fec);
const IntegrationRule &ir =
IntRules.Get(pmesh.GetTypicalElementGeometry(), 2 * p);
ParGridFunction u_gf(&fes);
FunctionCoefficient u_coeff(
[](const auto &x)
{
return 2_r * M_PI * x[0] * x[0] * 2_r * M_PI * x[1] * x[1];
});
u_gf.ProjectCoefficient(u_coeff);
Vector u(fes.GetTrueVSize());
u_gf.GetTrueDofs(u);
MyFunctional<DIM> functional(fes, *mfes, ir);
Vector exact_g(fes.GetTrueVSize());
functional.gradient_exact(u, exact_g);
Vector g(fes.GetTrueVSize());
functional.gradient(u, g);
Vector diff(g);
diff -= exact_g;
REQUIRE(diff.Norml2() < 1e-12);
// The functional derivative assembled into a Vector.
Vector assembled_g;
functional.gradient_assembled(u, assembled_g);
REQUIRE(assembled_g.Size() == fes.GetTrueVSize());
diff = assembled_g;
diff -= exact_g;
REQUIRE(diff.Norml2() < 1e-12);
// Direction for the Hessian-vector product
ParGridFunction v_gf(&fes);
FunctionCoefficient v_coeff(
[](const auto &x)
{
return sin(M_PI * x[0]) * cos(M_PI * x[1]) + 0.5_r * x[0] * x[1];
});
v_gf.ProjectCoefficient(v_coeff);
Vector v(fes.GetTrueVSize());
v_gf.GetTrueDofs(v);
Vector exact_Hv(fes.GetTrueVSize());
functional.hvp_exact(u, v, exact_Hv);
Vector Hv_dres(fes.GetTrueVSize());
functional.hvp_dresidual(u, v, Hv_dres);
diff = Hv_dres;
diff -= exact_Hv;
REQUIRE(MFEM_Approx(diff.Norml2()) == 0.0);
Vector Hv(fes.GetTrueVSize());
functional.hvp(u, v, Hv);
diff = Hv;
diff -= exact_Hv;
REQUIRE(MFEM_Approx(diff.Norml2()) == 0.0);
Vector Hv_functional(fes.GetTrueVSize());
functional.hvp_functional(u, v, Hv_functional);
diff = Hv_functional;
diff -= exact_Hv;
REQUIRE(MFEM_Approx(diff.Norml2()) == 0.0);
// std::cout << "Gradient using FwdDiff<f>:\n";
// pretty_print(g);
// std::cout << "Handcoded gradient of f(u):\n";
// pretty_print(exact_g);
// std::cout << "Handcoded H(u) v:\n";
// pretty_print(exact_Hv);
// std::cout << "H(u) v using the derivative of the handcoded residual:\n";
// pretty_print(Hv_dres);
// std::cout << "H(u) v using the derivative of FwdDiff<f>:\n";
// pretty_print(Hv);
}
template <int DIM>
void mixed_second_derivative(const char *filename, int p)
{
static constexpr int U = 0, Rho = 1, Coords = 2, Q = 3;
static constexpr int DU = 4, DRho = 5;
CAPTURE(filename, DIM, p);
Mesh smesh(filename);
ParMesh pmesh(MPI_COMM_WORLD, smesh);
pmesh.EnsureNodes();
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
ParFiniteElementSpace *mfes = nodes->ParFESpace();
H1_FECollection fec(p, DIM);
ParFiniteElementSpace fes(&pmesh, &fec);
const int tvsize = fes.GetTrueVSize();
const IntegrationRule &ir =
IntRules.Get(pmesh.GetTypicalElementGeometry(), 2 * p);
Array<int> all_domain_attr;
if (pmesh.attributes.Size() > 0)
{
all_domain_attr.SetSize(pmesh.attributes.Max());
all_domain_attr = 1;
}
// Use smooth, non-constant fields so all four second-derivative blocks are
// nontrivial while keeping the exact expressions simple.
ParGridFunction u_gf(&fes), rho_gf(&fes), du_gf(&fes), drho_gf(&fes);
FunctionCoefficient u_coeff(
[](const auto &x)
{
return 1.0_r + x[0] + 0.25_r * x[1];
});
FunctionCoefficient rho_coeff(
[](const auto &x)
{
return 0.5_r + 0.2_r * x[0] * x[0] + 0.1_r * x[1];
});
FunctionCoefficient du_coeff(
[](const auto &x)
{
return cos(M_PI * x[0]) + 0.25_r * x[0] * x[1];
});
FunctionCoefficient drho_coeff(
[](const auto &x)
{
return sin(M_PI * x[0]) + 0.5_r * x[1];
});
u_gf.ProjectCoefficient(u_coeff);
rho_gf.ProjectCoefficient(rho_coeff);
du_gf.ProjectCoefficient(du_coeff);
drho_gf.ProjectCoefficient(drho_coeff);
Vector u(tvsize), rho(tvsize), du(tvsize), drho(tvsize), coords;
u_gf.GetTrueDofs(u);
rho_gf.GetTrueDofs(rho);
du_gf.GetTrueDofs(du);
drho_gf.GetTrueDofs(drho);
pmesh.GetNodes()->GetTrueDofs(coords);
const auto functional_in = std::vector
{
FieldDescriptor{U, &fes},
FieldDescriptor{Rho, &fes},
FieldDescriptor{Coords, mfes}
};
QuadratureSpace qspace(pmesh, ir);
VectorQuadratureSpace qspace_vec(qspace, 1);
const auto functional_out = std::vector
{
FieldDescriptor{Q, &qspace_vec}
};
DifferentiableOperator functional_dop(functional_in, functional_out, pmesh);
MixedFunctional<real_t, DIM> functional;
functional_dop.AddDomainIntegrator<LocalQFBackend>(
functional,
Inputs<Value<U>, Value<Rho>, Gradient<Coords>, Weight> {},
Outputs<FunctionalValue<Q>> {},
ir, all_domain_attr,
Derivatives<U, Rho> {});
MultiVector X{u, rho, coords};
auto check_block = [&](auto gradient_id,
auto direction_id,
const Vector &direction,
auto exact_qfunc,
auto exact_inputs,
auto exact_outputs,
const std::vector<FieldDescriptor> &exact_in,
const std::vector<FieldDescriptor> &exact_out,
MultiVector exact_x)
{
Vector actual(tvsize);
MultiVector Actual{actual};
functional_dop.GetSecondDerivative(gradient_id, direction_id, X)->Mult(
direction, Actual);
Vector expected(tvsize);
MultiVector Expected{expected};
DifferentiableOperator exact_dop(exact_in, exact_out, pmesh);
exact_dop.AddDomainIntegrator<LocalQFBackend>(
exact_qfunc, exact_inputs, exact_outputs, ir, all_domain_attr);
exact_dop.Mult(exact_x, Expected);
Vector diff(actual);
diff -= expected;
REQUIRE(MFEM_Approx(diff.Norml2()) == 0.0);
};
check_block(U, U, du,
MixedFunctionalUUAction<real_t, DIM> {},
Inputs<Value<DU>, Value<Rho>, Gradient<Coords>, Weight> {},
Outputs<Value<U>> {},
std::vector{FieldDescriptor{DU, &fes},
FieldDescriptor{Rho, &fes},
FieldDescriptor{Coords, mfes}},
std::vector{FieldDescriptor{U, &fes}},
MultiVector{du, rho, coords});
check_block(U, Rho, drho,
MixedFunctionalURhoAction<real_t, DIM> {},
Inputs<Value<DRho>, Value<U>, Gradient<Coords>, Weight> {},
Outputs<Value<U>> {},
std::vector{FieldDescriptor{DRho, &fes},
FieldDescriptor{U, &fes},
FieldDescriptor{Coords, mfes}},
std::vector{FieldDescriptor{U, &fes}},
MultiVector{drho, u, coords});
check_block(Rho, U, du,
MixedFunctionalRhoUAction<real_t, DIM> {},
Inputs<Value<DU>, Value<U>, Gradient<Coords>, Weight> {},
Outputs<Value<Rho>> {},
std::vector{FieldDescriptor{DU, &fes},
FieldDescriptor{U, &fes},
FieldDescriptor{Coords, mfes}},
std::vector{FieldDescriptor{Rho, &fes}},
MultiVector{du, u, coords});
check_block(Rho, Rho, drho,
MixedFunctionalRhoRhoAction<real_t, DIM> {},
Inputs<Value<DRho>, Gradient<Coords>, Weight> {},
Outputs<Value<Rho>> {},
std::vector{FieldDescriptor{DRho, &fes},
FieldDescriptor{Coords, mfes}},
std::vector{FieldDescriptor{Rho, &fes}},
MultiVector{drho, coords});
}
} // namespace second_derivative_test
TEST_CASE("dFEM functional second derivative action matches mfem",
"[Parallel][dFEM][second-derivative]")
{
const bool all_tests = launch_all_non_regression_tests;
const auto p = !all_tests ? 1 : GENERATE(1, 2, 3);
SECTION("2d")
{
const auto f =
GENERATE(
// "../../data/star.mesh",
// "../../data/star-q3.mesh",
// "../../data/rt-2d-q3.mesh",
"../../data/inline-quad.mesh"
// "../../data/periodic-square.mesh"
);
second_derivative_test::second_derivative<2>(f, p);
}
// SECTION("3d")
// {
// const auto f =
// GENERATE(
// "../../data/fichera-q3.mesh",
// "../../data/inline-hex.mesh",
// "../../data/toroid-hex.mesh",
// "../../data/periodic-cube.mesh"
// );
// second_derivative_test::second_derivative<3>(f, p);
// }
}
TEST_CASE("dFEM functional mixed second derivative action matches exact action",
"[Parallel][dFEM][second-derivative]")
{
const bool all_tests = launch_all_non_regression_tests;
const auto p = !all_tests ? 1 : GENERATE(1, 2, 3);
SECTION("2d")
{
const auto f = GENERATE("../../data/inline-quad.mesh");
second_derivative_test::mixed_second_derivative<2>(f, p);
}
}
#endif // MFEM_USE_MPI
#endif // MFEM_USE_ENZYME
+173
View File
@@ -0,0 +1,173 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "../unit_tests.hpp"
#include "mfem.hpp"
#ifdef MFEM_USE_MPI
#include "../../../fem/dfem/doperator.hpp"
#include "../../../fem/dfem/backends/local_qf/prelude.hpp"
using namespace mfem;
using namespace mfem::future;
#ifdef MFEM_USE_ENZYME
using dscalar_t = real_t;
#else
using dscalar_t = dual<real_t, real_t>;
#endif
// ────────────────────────────────────────────────────────────────────────────
namespace
{
static constexpr int DIM = 2;
struct VectorValueCopy
{
MFEM_HOST_DEVICE inline
void operator()(const tensor<real_t, DIM> &x,
tensor<real_t, DIM> &y) const
{
y(0) = x(0);
y(1) = x(1);
}
};
struct VectorMassCopy
{
MFEM_HOST_DEVICE inline
void operator()(const tensor<real_t, DIM> &x,
const tensor<real_t, DIM, DIM> &J,
const real_t &w,
tensor<real_t, DIM> &y) const
{
y = x * w * det(J);
}
};
}
// ────────────────────────────────────────────────────────────────────────────
void test_vqspace_identity_copy(int order)
{
Mesh serial_mesh =
Mesh::MakeCartesian2D(1, 1, Element::QUADRILATERAL, true, 1.0, 1.0);
ParMesh pmesh(MPI_COMM_WORLD, serial_mesh);
const IntegrationRule &ir = IntRules.Get(Geometry::SQUARE, 2 * order + 1);
QuadratureSpace qspace(pmesh, ir);
VectorQuadratureSpace vqspace(qspace, DIM);
const auto qvsize = vqspace.GetVSize();
Array<int> domain_attr(pmesh.attributes.Max());
domain_attr = 1;
static constexpr int U = 0, V = 1;
const std::vector fdi { FieldDescriptor{U, &vqspace} };
const std::vector fdo { FieldDescriptor{V, &vqspace} };
DifferentiableOperator dop(fdi, fdo, pmesh);
VectorValueCopy qfunc;
dop.AddDomainIntegrator<LocalQFBackend>(
qfunc,
Inputs<Identity<U>> {},
Outputs<Identity<V>> {},
ir, domain_attr);
Vector vX(qvsize), vY(qvsize);
vX.Randomize(0x9e3779b9);
vY = 0.0;
MultiVector Xmv{vX}, Ymv{vY};
dop.Mult(Xmv, Ymv);
Vector diff(vY);
diff -= vX;
REQUIRE(diff.Normlinf() == MFEM_Approx(0.0));
}
// ────────────────────────────────────────────────────────────────────────────
void test_value_vector_mass(int order)
{
Mesh serial_mesh =
Mesh::MakeCartesian2D(1, 1, Element::QUADRILATERAL, true, 1.0, 1.0);
ParMesh pmesh(MPI_COMM_WORLD, serial_mesh);
pmesh.EnsureNodes();
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
const auto *nfes = nodes->ParFESpace();
H1_FECollection fec(order, DIM);
ParFiniteElementSpace fes(&pmesh, &fec, DIM, Ordering::byVDIM);
const auto tvsize = fes.GetTrueVSize();
Array<int> domain_attr(pmesh.attributes.Max());
domain_attr = 1;
const IntegrationRule &ir = IntRules.Get(Geometry::SQUARE, 2 * order + 1);
ConstantCoefficient one(1.0), zero(0.0);
ParGridFunction input_gf(&fes);
ParGridFunction reference_gf(&fes);
ParGridFunction error_gf(&fes);
Vector vX(tvsize), vY_ref(tvsize), vY(tvsize), N(nfes->GetTrueVSize());
vX.Randomize(0x9e3779b9);
input_gf.SetFromTrueDofs(vX);
nodes->GetTrueDofs(N);
vY = 0.0;
ParBilinearForm blf(&fes);
blf.AddDomainIntegrator(new VectorMassIntegrator(one, &ir));
blf.SetAssemblyLevel(AssemblyLevel::PARTIAL);
blf.Assemble();
blf.Mult(input_gf, reference_gf);
fes.GetProlongationMatrix()->MultTranspose(reference_gf, vY_ref);
static constexpr int U = 0, V = 1, Coords = 2;
const std::vector fdi { FieldDescriptor{U, &fes}, FieldDescriptor{Coords, nfes} };
const std::vector fdo { FieldDescriptor{V, &fes} };
DifferentiableOperator dop(fdi, fdo, pmesh);
VectorMassCopy qfunc;
dop.AddDomainIntegrator<LocalQFBackend>(
qfunc,
Inputs<Value<U>, Gradient<Coords>, Weight> {},
Outputs<Value<V>> {},
ir, domain_attr);
MultiVector Xmv{vX, N}, Ymv{vY};
dop.Mult(Xmv, Ymv);
vY_ref -= vY;
error_gf.SetFromTrueDofs(vY_ref);
REQUIRE(error_gf.ComputeMaxError(zero) == MFEM_Approx(0.0));
}
// ────────────────────────────────────────────────────────────────────────────
TEST_CASE("dFEM TMOP", "[Parallel][dFEM][GPU]")
{
const auto p = GenAll({1}, {2, 3});
SECTION("VectorQuadratureSpace identity copy")
{
test_vqspace_identity_copy(p);
}
SECTION("Value vector mass matches PA MFEM")
{
test_value_vector_mass(p);
}
}
#endif // MFEM_USE_MPI
+62
View File
@@ -59,4 +59,66 @@ TEST_CASE("AD Vector implementation", "[Enzyme]")
run_test<std::vector<double>>();
}
namespace enzyme_test
{
template <int N>
void f(const double *x, double *y, double *a)
{
mfem::forall<mfem::UseEnzyme>(N, [=] MFEM_HOST_DEVICE(int q)
{
y[q] = a[q] * x[q] * x[q];
});
}
} // namespace enzyme_test
TEST_CASE("AD Global qfunction with GPU", "[Enzyme][GPU]")
{
constexpr int N = 10;
mfem::Vector x(N), xd(N), y(N), yd(N), a(N), ad(N);
auto x_w = x.HostWrite();
auto xd_w = xd.HostWrite();
auto y_w = y.HostWrite();
auto yd_w = yd.HostWrite();
auto a_w = a.HostWrite();
auto ad_w = ad.HostWrite();
for (int i = 0; i < N; i++)
{
x_w[i] = i;
xd_w[i] = 1.0;
y_w[i] = 0.0;
yd_w[i] = 0.0;
a_w[i] = 2.0;
ad_w[i] = 0.0;
}
auto x_d = x.Read();
auto xd_d = xd.ReadWrite();
auto y_d = y.ReadWrite();
auto yd_d = yd.ReadWrite();
auto a_d = a.Read();
__enzyme_fwddiff<void>((void *)enzyme_test::f<N>, enzyme_dup, x_d, xd_d,
enzyme_dup, y_d,
yd_d, enzyme_const, a_d, enzyme_runtime_activity);
const mfem::real_t *yd_h = yd.HostRead();
const mfem::real_t *x_h = x.HostRead();
const mfem::real_t *a_h = a.HostRead();
bool ok = true;
for (int q = 0; q < N; q++)
{
mfem::real_t exact = 2.0 * a_h[q] * x_h[q];
if (yd_h[q] != exact)
{
ok = false;
break;
}
}
REQUIRE(ok);
}
#endif
@@ -0,0 +1,122 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "mfem.hpp"
#include "unit_tests.hpp"
#include "../../../linalg/tensor_arrays.hpp"
#ifdef MFEM_USE_ENZYME
namespace enzyme_test_reversetape
{
using namespace mfem;
using namespace mfem::future;
void myQF(real_t x[2])
{
const real_t u = x[0];
const real_t v = x[1];
x[0] = sin(u) * cos(v) * (u + v);
}
struct WrappedQF
{
void operator()(tensor_array<real_t> &x) const
{
const real_t u = x(0);
const real_t v = x(1);
x(0) = sin(u) * cos(v) * (u + v);
}
};
template <int N>
void qfunction_wrapper(real_t *x)
{
auto x_t = make_tensor_array(x, N);
WrappedQF qf;
qf(x_t);
}
template <typename return_type, typename... Args>
return_type __enzyme_augmentfwd(Args...);
template <typename return_type, typename... Args>
return_type __enzyme_reverse(Args...);
} // namespace enzyme_test_reversetape
TEST_CASE("Enzyme split reverse mode point qfunction VJP",
"[Enzyme][SplitReverse]")
{
using namespace enzyme_test_reversetape;
real_t x[2] = {0.7, 0.2};
real_t x_bar[2] = {1.5, 0.0};
real_t y[2] = {x[0], x[1]};
real_t y_bar[2] = {x_bar[0], x_bar[1]};
void *tape = __enzyme_augmentfwd<void *>((void *)myQF, x, x_bar);
__enzyme_reverse<void>((void *)myQF, x, x_bar, tape);
__enzyme_autodiff<void>((void *)myQF, y, y_bar);
const real_t u = 0.7;
const real_t v = 0.2;
const real_t residual = sin(u) * cos(v) * (u + v);
REQUIRE(x[0] == MFEM_Approx(residual));
REQUIRE(y[0] == MFEM_Approx(residual));
REQUIRE(x[1] == MFEM_Approx(v));
REQUIRE(y[1] == MFEM_Approx(v));
const real_t exact_u_bar = 1.5 * (cos(u) * cos(v) * (u + v) + sin(u) * cos(v));
const real_t exact_v_bar = 1.5 * (-sin(u) * sin(v) * (u + v) + sin(u) * cos(v));
REQUIRE(x_bar[0] == MFEM_Approx(exact_u_bar));
REQUIRE(x_bar[1] == MFEM_Approx(exact_v_bar));
REQUIRE(y_bar[0] == MFEM_Approx(x_bar[0]));
REQUIRE(y_bar[1] == MFEM_Approx(x_bar[1]));
}
TEST_CASE("Enzyme split reverse mode wrapped point qfunction VJP",
"[Enzyme][SplitReverse][QFunctionWrapper]")
{
using namespace enzyme_test_reversetape;
real_t x[2] = {0.7, 0.2};
real_t x_bar[2] = {1.5, 0.0};
real_t y[2] = {x[0], x[1]};
real_t y_bar[2] = {x_bar[0], x_bar[1]};
void *tape = __enzyme_augmentfwd<void *>((void *)qfunction_wrapper<2>, x,
x_bar);
__enzyme_reverse<void>((void *)qfunction_wrapper<2>, x, x_bar, tape);
__enzyme_autodiff<void>((void *)qfunction_wrapper<2>, y, y_bar);
const real_t u = 0.7;
const real_t v = 0.2;
const real_t residual = sin(u) * cos(v) * (u + v);
REQUIRE(x[0] == MFEM_Approx(residual));
REQUIRE(y[0] == MFEM_Approx(residual));
REQUIRE(x[1] == MFEM_Approx(v));
REQUIRE(y[1] == MFEM_Approx(v));
const real_t exact_u_bar = 1.5 * (cos(u) * cos(v) * (u + v) + sin(u) * cos(v));
const real_t exact_v_bar = 1.5 * (-sin(u) * sin(v) * (u + v) + sin(u) * cos(v));
REQUIRE(x_bar[0] == MFEM_Approx(exact_u_bar));
REQUIRE(x_bar[1] == MFEM_Approx(exact_v_bar));
REQUIRE(y_bar[0] == MFEM_Approx(x_bar[0]));
REQUIRE(y_bar[1] == MFEM_Approx(x_bar[1]));
}
#endif

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