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88 Commits
Author SHA1 Message Date
Andrew Ho 15e85586b1 Merge branch 'gpu_em' into gpu-maxwell 2026-07-02 18:55:08 -07:00
Andrew Ho bab4314cf3 Merge branch 'gpu-qinterp-integ' into gpu_em 2026-07-02 18:10:10 -07:00
Andrew Ho 70b5d7c501 Merge branch 'gpu_em' into gpu-maxwell 2026-07-02 08:43:50 -07:00
Andrew Ho e59d1835c3 compiler warnings 2026-07-02 08:41:58 -07:00
Andrew Ho b4e7cf1a1a specializations to work with quadratic meshes 2026-07-01 18:31:20 -07:00
Andrew Ho 83747810f3 Merge branch 'gpu_em' into gpu-maxwell 2026-07-01 16:11:29 -07:00
Andrew Ho 3cdaebdcaa formatting 2026-06-30 14:55:23 -07:00
Andrew Ho 9e8a7c456f Added Kris's mixed dot product integrator PA 2026-06-30 14:41:32 -07:00
Andrew Ho b39719984a Merge branch 'curl_interp_pa' into gpu_em 2026-06-30 14:21:26 -07:00
Andrew Ho a95278fe72 Merge branch 'bugfix-project' into gpu_em 2026-06-30 14:20:49 -07:00
Andrew Ho f2f366efa2 Merge branch 'gpu-qinterp-integ' into gpu_em 2026-06-30 14:20:34 -07:00
Andrew Ho e3ee3868e8 Merge remote-tracking branch 'base/gpu-maxwell' into gpu-maxwell 2026-06-29 17:01:43 -07:00
Andrew Ho 93c3db3c2c Merge branch 'curl_interp_pa' into gpu-maxwell 2026-06-29 14:54:33 -07:00
Andrew Ho f4ad8b8f92 formatting 2026-06-29 14:50:31 -07:00
Andrew Ho e04c90b678 thread assignment error 2026-06-29 14:46:08 -07:00
Andrew Ho abbfe7cf71 Merge branch 'hcurl_mass_pa' into curl_interp_pa 2026-06-29 14:09:12 -07:00
Andrew Ho f0f15cac86 Merge branch 'curl_interp_pa' into gpu-maxwell 2026-06-29 12:23:51 -07:00
Andrew Ho 6c2a78d5bd extract curl interpolator and a few other misc fixes 2026-06-29 11:49:07 -07:00
Andrew Ho 5bce913668 old comment 2026-06-29 11:46:07 -07:00
Andrew Ho 6ec7186f5d Merge branch 'hcurl_mass_pa' into gpu-maxwell 2026-06-29 11:31:19 -07:00
Andrew Ho ac3062abab matrix coefficient version not implemented yet 2026-06-17 22:40:11 -07:00
Andrew Ho f11c649b20 Merge branch 'hcurl_mass_pa' into gpu-maxwell 2026-06-17 22:01:29 -07:00
Andrew Ho e87398b84b minor changes 2026-06-17 22:00:16 -07:00
Andrew Ho 902bb43e8d Merge branch 'hcurl_mass_pa' into gpu-maxwell 2026-06-17 21:54:34 -07:00
Andrew Ho 87d3488424 missing forwarding addmult/addmulttranspose to bilinearform extensions 2026-06-17 20:09:01 -07:00
Andrew Ho 4c1abe4a87 Remove full assembly option
Just use the regular Maxwell miniapp for full assembly.
2026-06-17 19:09:56 -07:00
Andrew Ho 2969dabdf9 need an operator which operates on tdofs 2026-06-16 23:18:11 -07:00
Andrew Ho b5b2749946 fixed dt calculation partially applying bcs 2026-06-16 22:44:37 -07:00
Andrew Ho d97d93a3ac implemented partial assembly dt calculation 2026-06-15 22:50:43 -07:00
Andrew Ho 7783ee88a5 wrong variable name 2026-06-14 23:09:14 -07:00
Andrew Ho 3233fe5ef5 windows compiler is trying to capture constexpr local variables 2026-06-14 22:55:14 -07:00
Andrew Ho 7869614b2d can use fewer max threads 2026-06-14 18:45:31 -07:00
Andrew Ho eb0c90e7b7 Merge branch 'hcurl_mass_pa' into gpu-maxwell 2026-06-14 18:44:30 -07:00
Andrew Ho d2220abf93 implemented addmult transpose
fixed a few bugs in assemblepa
2026-06-13 23:40:21 -07:00
Andrew Ho acfda7a20e offsetting is beneficial on matrix 2026-06-13 08:42:22 -07:00
Andrew Ho dc2c5b0acb added launch bounds, testing if thread offsetting is beneficial or not 2026-06-13 08:15:46 -07:00
Andrew Ho 813fccdcb2 implemented batching 2026-06-13 08:04:39 -07:00
Andrew Ho a8d70d8947 fixed kernel execution bug and added unit test 2026-06-12 16:53:06 -07:00
Andrew Ho 7bab30392e Merge branch 'hcurl_mass_pa' into gpu-maxwell 2026-06-12 12:53:36 -07:00
Andrew Ho 56ba38a0aa switched to 3d offset wrappers to simplify code 2026-06-12 10:07:55 -07:00
Andrew Ho 5c1fa29ff0 Merge branch 'hcurl_mass_pa' into gpu-maxwell 2026-06-12 09:12:46 -07:00
Andrew Ho 6766332897 have smem curl interpolator apply implemented 2026-06-12 03:11:28 -07:00
Andrew Ho 56305bb57b fixed typo 2026-06-10 15:52:29 -07:00
Andrew Ho 37a2ec2230 Merge branch 'hcurl_mass_pa' into gpu-maxwell 2026-06-10 15:34:51 -07:00
Andrew Ho 1704a02128 use kernel specializations for curl interpolator 2026-06-10 11:15:50 -07:00
Andrew Ho ba98d630bf Merge remote-tracking branch 'base/gpu-maxwell' into gpu-maxwell 2026-06-09 11:28:04 -07:00
Andrew Ho 584b933a7f stub for "partial-assembly" CurlInterpolator 2026-06-09 11:27:43 -07:00
Andrew Ho 5f04cf5e6f Merge branch 'master' into gpu-maxwell 2026-06-09 11:27:00 -07:00
Andrew Ho e7e9c4707d Merge branch 'hcurl_mass_pa' into gpu-maxwell 2026-05-18 11:35:24 -07:00
Andrew Ho f96fe0358d Merge branch 'hcurl_domain_lf' into gpu-maxwell 2026-05-18 11:11:30 -07:00
Andrew Ho 2cafc41e9d change contiguous order to have dim1 last 2026-05-18 11:09:38 -07:00
Andrew Ho 38c2f7a6ea Merge branch 'hcurl_domain_lf' into gpu-maxwell 2026-05-15 01:20:57 -07:00
Andrew Ho afe84565d8 Merge branch 'hcurl_domain_lf' into gpu-maxwell 2026-05-15 01:17:28 -07:00
Andrew Ho f072fde956 Implemented adaptive dt calculation
also have another hcurl mass kernel which performs really well on AMD GPUs,
but is not great at high order on NVidia GPUs.
2026-05-14 15:02:35 -07:00
Andrew Ho 65ed4e1188 msvc incorrectly captures vdim instead of treating it as constexpr 2026-05-08 23:37:58 -07:00
Andrew Ho f432e7fef3 even more msvc warnings 2026-05-08 22:57:17 -07:00
Andrew Ho 03145336b6 more mvsc warnings 2026-05-08 22:44:27 -07:00
Andrew Ho f077a45cce fix another msvc warning 2026-05-08 22:23:37 -07:00
Andrew Ho 4e568ae2e1 Merge remote-tracking branch 'base/gpu-maxwell' into gpu-maxwell 2026-05-08 21:59:21 -07:00
Andrew Ho dc53c87f63 compiler complaining about indexing with bool 2026-05-08 21:58:55 -07:00
Andrew Ho 0919b965f7 Merge branch 'master' into gpu-maxwell 2026-05-08 21:28:48 -07:00
Andrew Ho 9c687e3e83 bug fixes 2026-05-08 13:02:36 -07:00
Andrew Ho 5e244e1512 fixed bug reading markers 2026-05-08 12:12:16 -07:00
Andrew Ho f0d5a8a406 implemented hcurl domain lininteg device assembly 2026-05-08 12:06:19 -07:00
Andrew Ho 67e5ea9e74 switch VectorFEDomainLFIntegrator to use kernel dispatcher 2026-05-08 11:49:00 -07:00
Andrew Ho 9ff10d4c24 test windows build failure fix 2026-05-08 09:30:25 -07:00
Andrew Ho 2f42e93943 more CI warnings 2026-05-07 17:35:32 -07:00
Andrew Ho d0984442da CI compiler warnings 2026-05-06 19:13:30 -07:00
Andrew Ho b7188b08ab initialization order warning 2026-05-06 17:53:48 -07:00
Andrew Ho e61a0d629b missing doxygen escapes
added specializations for P=Q
2026-05-06 17:43:02 -07:00
Andrew Ho ca4ffc731b allow passing a specific integration rule to VectorFELFIntegrator 2026-05-05 11:55:01 -07:00
Andrew Ho f64e6a714b improved HCurl mass 3d apply performance 2026-05-05 09:25:27 -07:00
Andrew Ho b764432dae Merge branch 'batchmass3d' into gpu-maxwell 2026-04-27 23:58:23 -07:00
Andrew Ho 29b796be29 working on re-working parallelization of hcurl mass pa apply 2026-04-27 23:57:37 -07:00
Andrew Ho e2d73eb5de change vectorfemass to use the kernel specialization infrastructure 2026-04-27 19:14:24 -07:00
Andrew Ho baab626655 Have the correct RHS now 2026-04-26 23:51:12 -07:00
Andrew Ho f4c43542fe implemented current source 2026-04-26 02:27:40 -07:00
Andrew Ho f4442f229a wrong number of dofs in 3D h(div) linear form assembly 2026-04-26 00:57:57 -07:00
Andrew Ho 20424db300 Have a normalized plane wave example working on GPU 2026-04-25 11:14:55 -07:00
Andrew Ho dc427a4b04 have visualization, but seems to have some sort of bug still? 2026-04-25 01:00:36 -07:00
Andrew Ho b34f43359e Fixed missing RAP setup for MPI 2026-04-24 23:45:47 -07:00
Andrew Ho fc42855ce4 need pmesh coordinate information for current integrator 2026-04-23 10:51:14 -07:00
Andrew Ho 5abcb25851 have basic GPU solve with partial assembly working 2026-04-22 15:58:05 -07:00
Andrew Ho 7a02c5d256 setup coefficients and some terms in ampere's equation 2026-04-19 08:44:59 -07:00
Andrew Ho ba9ba59a08 getting global true vsize is a collective operation 2026-04-19 01:45:35 -07:00
Andrew Ho 06a8223fa6 implemented faraday's equation 2026-04-19 01:31:45 -07:00
Andrew Ho ffeef80ed4 stub for GPU maxwell implementation 2026-04-14 12:36:18 -07:00
Andrew Ho 34278b85fd added an enumeration list option to optparser 2026-04-08 12:41:10 -07:00
257 changed files with 14005 additions and 43120 deletions
+6 -2
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@@ -29,12 +29,16 @@ Runs a number of static repository-level sanity checks.
- `branch-history` guards against accidental commits of large files using the `--history` option of the `config/githooks/pre-push` script.
## `mfem-analysis.yml` (`build-analysis`)
Checks if the code builds and satisfies minimal requirements.
- `gitignore` builds hypre, METIS, and MFEM using `mfem/github-actions/build-hypre`, `mfem/github-actions/build-metis`, and `mfem/github-actions/build-mfem` and checks for correct `.gitignore` settings by running the `tests/scripts/gitignore` script.
## `builds-and-tests.yml`
Runs a matrix of builds and tests runs with different compilers, OS, mfem/hypre settings, etc. Also processes and upload Codecov reports.
One matrix job runs `tests/scripts/gitignore` after `make test-noclean` to check generated artifacts against `.gitignore`.
Uses the following GitHub Actions from <https://github.com/mfem/github-actions>:
- `mfem/github-actions/build-hypre`
+2 -70
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@@ -111,7 +111,6 @@ jobs:
build-system: make
hypre-target: int64
precision: fp64
gitignore-check: YES
- os: ubuntu-latest
target: opt
codecov: NO
@@ -142,10 +141,6 @@ jobs:
continue-on-error: ${{ matrix.enzyme && true || false }}
# Enable ccache for all jobs except Windows (would need sccache).
env:
USE_CCACHE: ${{ matrix.os != 'windows-latest' }}
steps:
# Fix 'No space left on device' errors for Ubuntu builds.
- name: Run Actions Cleaner
@@ -294,52 +289,6 @@ jobs:
echo "OMPI_CC=$LLVM_PREFIX/bin/clang" >> $GITHUB_ENV
echo "OMPI_CXX=$LLVM_PREFIX/bin/clang++" >> $GITHUB_ENV
# Restore the compiler cache (ccache). The key embeds the run id, so new
# runs save a fresh snapshot; the restore-keys prefix warm-starts from the
# most recent prior run (incl. the base branch for PRs).
- name: cache ccache
if: ${{ env.USE_CCACHE == 'true' }}
uses: actions/cache@v5
with:
path: .ccache
key: ccache-${{ matrix.os }}-${{ matrix.build-system }}-${{ matrix.target }}-${{ matrix.mpi }}-${{ matrix.hypre-target }}-${{ matrix.precision }}${{ matrix.enzyme && '-enzyme' || '' }}-${{ github.run_id }}
restore-keys: |
ccache-${{ matrix.os }}-${{ matrix.build-system }}-${{ matrix.target }}-${{ matrix.mpi }}-${{ matrix.hypre-target }}-${{ matrix.precision }}${{ matrix.enzyme && '-enzyme' || '' }}-
# Configure ccache and select how it is injected into the MFEM build:
# - make: set CXX="ccache g++"; for MPI, OMPI_CXX="ccache g++" so mpicxx
# runs ccache around g++ (not ccache around the mpicxx wrapper).
# - cmake: set CMAKE_<LANG>_COMPILER_LAUNCHER=ccache.
# - enzyme: wrap the brew clang++ via OMPI_CXX.
# The chosen options are passed through build-mfem's 'config-options'
# input (see the build step below).
- name: configure ccache
if: ${{ env.USE_CCACHE == 'true' }}
run: |
command -v ccache >/dev/null 2>&1 || {
if [[ "${{ runner.os }}" == "Linux" ]]; then
sudo apt-get update && sudo apt-get install -y ccache
else
brew install ccache
fi
}
echo "CCACHE_DIR=${{ github.workspace }}/.ccache" >> $GITHUB_ENV
echo "CCACHE_MAXSIZE=1G" >> $GITHUB_ENV
echo "CCACHE_COMPILERCHECK=content" >> $GITHUB_ENV
# Ignore header timestamps (restamped by each checkout) so direct mode hits.
echo "CCACHE_SLOPPINESS=include_file_mtime,include_file_ctime,time_macros" >> $GITHUB_ENV
# Hash absolute paths relative to the workspace.
echo "CCACHE_BASEDIR=${{ github.workspace }}" >> $GITHUB_ENV
if [[ "${{ matrix.enzyme }}" == "true" ]]; then
echo "OMPI_CXX=ccache $LLVM_PREFIX/bin/clang++" >> $GITHUB_ENV
elif [[ "${{ matrix.build-system }}" == "cmake" ]]; then
echo 'CCACHE_CONFIG_OPTS=-DCMAKE_CXX_COMPILER_LAUNCHER=ccache -DCMAKE_C_COMPILER_LAUNCHER=ccache' >> $GITHUB_ENV
else
echo "OMPI_CXX=ccache g++" >> $GITHUB_ENV
echo 'CCACHE_CONFIG_OPTS=CXX="ccache g++" MPICXX="mpicxx"' >> $GITHUB_ENV
fi
shell: bash
# MFEM build and test
- name: build
uses: mfem/github-actions/build-mfem@v2.7
@@ -355,14 +304,9 @@ jobs:
metis-dir: ${{ env.METIS_TOP_DIR }}
mfem-dir: ${{ env.MFEM_TOP_DIR }}
precision: ${{ matrix.precision }}
config-options: ${{ matrix.config-opts }} ${{ env.CCACHE_CONFIG_OPTS }}
config-options: ${{ matrix.config-opts }}
library-only: ${{ matrix.target == 'dbg' && matrix.os != 'ubuntu-latest' }}
- name: ccache stats
if: ${{ env.USE_CCACHE == 'true' }}
run: ccache -s
shell: bash
# Run checks (and only checks) on debug targets
- name: checks
if: matrix.build-system == 'make' && matrix.target == 'dbg'
@@ -373,13 +317,7 @@ jobs:
- name: tests
if: matrix.build-system == 'make' && (matrix.target == 'opt' || matrix.os == 'ubuntu-latest')
run: |
cd ${{ env.MFEM_TOP_DIR }}
if [[ "${{ matrix.gitignore-check }}" == "YES" ]]; then
make test-noclean
else
make test
fi
shell: bash
cd ${{ env.MFEM_TOP_DIR }} && make test
- name: cmake checks
if: matrix.build-system == 'cmake' && matrix.target == 'dbg'
@@ -431,9 +369,3 @@ jobs:
directories: "fem general linalg mesh"
env:
CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
- name: gitignore
if: matrix.gitignore-check == 'YES'
run: |
cd ${{ env.MFEM_TOP_DIR }}/tests/scripts
./runtest gitignore
-42
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@@ -1,42 +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.
---
# A closed PR's caches can never be restored again, so delete them to free
# space against the 10 GB per-repo cache limit.
name: Cleanup PR caches
on:
pull_request:
types: [closed]
permissions:
actions: write
jobs:
cleanup:
runs-on: ubuntu-latest
steps:
- name: Delete caches for the closed PR
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
GH_REPO: ${{ github.repository }}
PR_REF: refs/pull/${{ github.event.pull_request.number }}/merge
run: |
echo "Deleting caches for $PR_REF"
while :; do
ids=$(gh cache list --ref "$PR_REF" --limit 100 --json id --jq '.[].id')
[ -n "$ids" ] || break
echo "$ids" | while read -r id; do
[ -n "$id" ] || continue
echo "Deleting cache $id"
gh cache delete "$id" || echo " (already gone)"
done
done
-10
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@@ -14,19 +14,9 @@ name: "Static Analysis"
on:
push:
branches: ["master", "next"]
paths-ignore: &docs-only-paths
- "**/*.md"
- "doc/**"
- ".binder/**"
- "CITATION.cff"
- "LICENSE"
- "NOTICE"
- "CHANGELOG"
- "INSTALL"
pull_request:
# The branches below must be a subset of the branches above
branches: ["master"]
paths-ignore: *docs-only-paths
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
+102
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@@ -0,0 +1,102 @@
# 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.
name: "Build Analysis"
permissions:
actions: write
on:
push:
branches:
- master
- next
pull_request:
workflow_dispatch:
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
env:
HYPRE_ARCHIVE: v2.19.0.tar.gz
HYPRE_TOP_DIR: hypre-2.19.0
METIS_ARCHIVE: metis-4.0.3.tar.gz
METIS_TOP_DIR: metis-4.0.3
COVERAGE_ENV: mfem-coverage
MFEM_ACTIONS_VERSION: v2.7
jobs:
gitignore:
runs-on: ubuntu-latest
steps:
- name: checkout MFEM
uses: actions/checkout@v6
with:
path: mfem
- name: Get MPI (Linux)
run: |
sudo apt-get install openmpi-bin libopenmpi-dev
export OMPI_MCA_rmaps_base_oversubscribe=1
- name: Cache Hypre Install
id: hypre-cache
uses: actions/cache@v5
with:
path: ${{ env.HYPRE_TOP_DIR }}
key: ${{ runner.os }}-ompi-build-${{ env.HYPRE_TOP_DIR }}-int32-fp64-${{ env.MFEM_ACTIONS_VERSION }}
- name: Get Hypre
if: steps.hypre-cache.outputs.cache-hit != 'true'
uses: mfem/github-actions/build-hypre@v2.7
with:
archive: ${{ env.HYPRE_ARCHIVE }}
dir: ${{ env.HYPRE_TOP_DIR }}
target: int32
precision: fp64
- name: Cache Metis Install
id: metis-cache
uses: actions/cache@v5
with:
path: ${{ env.METIS_TOP_DIR }}
key: ${{ runner.os }}-build-${{ env.METIS_TOP_DIR }}-${{ env.MFEM_ACTIONS_VERSION }}
- name: Install Metis
if: steps.metis-cache.outputs.cache-hit != 'true'
uses: mfem/github-actions/build-metis@v2.7
with:
archive: ${{ env.METIS_ARCHIVE }}
dir: ${{ env.METIS_TOP_DIR }}
# MFEM build and test
- name: build-mfem
uses: mfem/github-actions/build-mfem@v2.7
with:
os: ${{ runner.os }}
target: opt
codecov: NO
mpi: par
build-system: make
hypre-dir: ${{ env.HYPRE_TOP_DIR }}
metis-dir: ${{ env.METIS_TOP_DIR }}
mfem-dir: mfem
- name: test (no clean)
run: |
cd mfem && make test-noclean
- name: gitignore
run: |
cd mfem/tests/scripts
./runtest gitignore
+4 -33
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@@ -13,7 +13,6 @@ name: "Checks"
permissions:
actions: write
pull-requests: read
on:
push:
@@ -30,11 +29,6 @@ concurrency:
# by checking if the workflow trigger is 'push' ("github.event_name == 'push'")
# and if we are in a fork ("github.event.pull_request.head.repo.full_name !=
# github.repository").
#
# The logic for the branch-history check is slightly different, since that check
# also inspects the PR's labels to allow for overriding failures. In this case,
# we run on all 'pull_request' triggers, but only run for 'push' triggers that
# do not correspond to any open PRs.
jobs:
file-headers-check:
@@ -134,7 +128,10 @@ jobs:
branch-history:
if: |
github.ref != 'refs/heads/next' && github.ref != 'refs/heads/master'
github.ref != 'refs/heads/next' &&
github.ref != 'refs/heads/master' &&
(github.event_name == 'push' ||
github.event.pull_request.head.repo.full_name != github.repository)
runs-on: ubuntu-latest
steps:
- name: checkout mfem
@@ -142,27 +139,7 @@ jobs:
with:
fetch-depth: 0
- name: check for pull request
id: check_pr
if: github.event_name == 'push'
env:
GH_TOKEN: ${{ github.token }}
run: |
pr_exists=$(gh pr list --repo "$GITHUB_REPOSITORY" \
--head "$GITHUB_REF_NAME" \
--state open \
--json number \
--jq 'length > 0')
echo "pr_exists=$pr_exists" >> "$GITHUB_OUTPUT"
- name: branch-history
id: branch_history
if: |
(github.event_name == 'pull_request' ||
github.event_name == 'workflow_dispatch' ||
steps.check_pr.outputs.pr_exists == 'false')
continue-on-error: ${{ contains(github.event.pull_request.labels.*.name,
'branch-history-override') }}
run: |
# We override origin to make sure we point to the main repo.
# This is to have consistent test results on PRs from forks.
@@ -170,9 +147,3 @@ jobs:
git remote add origin https://github.com/mfem/mfem.git
git checkout -b gh-actions-branch-history
./config/githooks/pre-push --history
- name: report branch-history override
if: steps.branch_history.outcome == 'failure'
run: |
echo "::warning::branch-history check failed, but the" \
"'branch-history-override' label is set."
-10
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@@ -17,17 +17,7 @@ permissions:
on:
push:
branches: ["master", "next"]
paths-ignore: &docs-only-paths
- "**/*.md"
- "doc/**"
- ".binder/**"
- "CITATION.cff"
- "LICENSE"
- "NOTICE"
- "CHANGELOG"
- "INSTALL"
pull_request:
paths-ignore: *docs-only-paths
workflow_dispatch:
concurrency:
-2
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@@ -214,7 +214,6 @@ miniapps/adjoint/adjoint_advection_diffusion
miniapps/dfem/dfem-minimal-surface
miniapps/dfem/dfem-minimal-surface-output
miniapps/dfem/dfem-hyperelasticity_energy
miniapps/electromagnetics/volta
miniapps/electromagnetics/tesla
@@ -261,7 +260,6 @@ miniapps/meshing/polar-nc
miniapps/meshing/mesh-quality
miniapps/meshing/hpref
miniapps/meshing/phpref
miniapps/meshing/pref321
miniapps/meshing/mobius-strip.mesh
miniapps/meshing/klein-bottle.mesh
miniapps/meshing/toroid-*.mesh
+2 -4
View File
@@ -102,14 +102,12 @@ report_baseline:
mkdir -p ${MACHINE_NAME}
rundir="${MACHINE_NAME}/$(date +%Y-%m-%d)-gitlab-${BASELINE_TEST}-${CI_COMMIT_REF_SLUG}"
rundir=$(${CI_PROJECT_DIR}/.gitlab/scripts/safe_create_rundir ${rundir})
status=0
cp ${CI_PROJECT_DIR}/${ARTIFACTS_DIR}/* ${rundir} || { status=1; }
cp ${CI_PROJECT_DIR}/${ARTIFACTS_DIR}/* ${rundir}
printf "%s\n" "" "Pipeline URL:" "$CI_PIPELINE_URL" \
>> ${rundir}/pipeline.txt
# We create an autotest-email.html file, because that's how we signal
# that there was an error / diff (temporary).
if [[ $status -ne 0 ]] || \
[[ -f ${rundir}/${BASELINE_TEST}.err ]] || \
if [[ -f ${rundir}/${BASELINE_TEST}.err ]] || \
[[ -f ${rundir}/${BASELINE_TEST}-${MACHINE_NAME}.diff ]]; then
cp ${rundir}/pipeline.txt ${rundir}/autotest-email.html
fi
-31
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@@ -15,10 +15,6 @@ Version 4.9.1 (development)
Discretization improvements
---------------------------
- Improved FindPointsGSLIB surface mesh capability with support for simplices
and an option to specify axis-aligned bounding box padding for near-surface
point queries.
- Added GPU-enabled partial assembly for simplicial Bernstein H1 basis based on
ragged tensor algorithms (see DOI: 10.1137/11082539X) for mass and diffusion
integrators.
@@ -44,24 +40,10 @@ Discretization improvements
- Added methods to estimate function extremum using piecewise linear bounds plus
recursive subdivision.
- Added class VectorQuadratureSpace that represents a vector (multi-component)
version of the scalar (single-component) class QuadratureSpaceBase.
- Extend FindPointsGSLIB to support surface meshes.
- Added support for complex-valued mixed bilinear forms via the new classes
MixedSesquilinearForm and ParMixedSesquilinearForm, mirroring the existing
SesquilinearForm classes. Rectangular complex operators are now also
handled correctly by ComplexSparseMatrix::GetSystemMatrix and
ComplexHypreParMatrix::GetSystemMatrix, which previously assumed equal
trial and test spaces.
Meshing improvements
--------------------
- Added support for nonuniform anisotropic mesh refinement on parallel quad/hex
meshes with arbitrary spacing in each direction. This enables in particular
3:1 refinement in parallel, as demonstrated in the new meshing miniapp pref321.
- Added option to guarantee mesh validity during TMOP-based r-adaptivity, using
bounds on the determinant of the mesh transformation Jacobian.
@@ -84,15 +66,6 @@ Linear and nonlinear solvers
GPU computing
-------------
- Improved partial assembly for VectorDivergenceIntegrator with shared-memory
kernels, kernel registration, and transpose support.
- Improved partial-assembly diagonal kernels for VectorMassIntegrator (shared-
memory specializations) and ElasticityIntegrator (no scratch Q-vector).
- Added PA gradient and diagonal support for VectorConvectionNLFIntegrator
(AssembleGradPA, AddMultGradPA, AssembleGradDiagonalPA).
- Added device assembly support for 3D H(curl) VectorFEDomainLFIntegrator.
- Added NVIDIA cuDSS library interface. Implementation examples have been
@@ -100,10 +73,6 @@ GPU computing
details. Supported versions >= 0.6.0.
- Allow specifying GPU kernel launch bounds for native and RAJA GPU backends.
- Changed VectorFEMassIntegrator to use kernel specialization dispatch for
partial assembly.
- Added support for FiniteElement::MapType::INTEGRAL spaces to
QuadratureInterpolator.
+12 -75
View File
@@ -184,45 +184,6 @@ if (MFEM_USE_CUDA)
set(CMAKE_CUDA_EXTENSIONS OFF CACHE BOOL "Enable CUDA standard extensions.")
set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} ${CUDA_FLAGS}")
find_package(CUDAToolkit REQUIRED)
if(CMAKE_CUDA_COMPILER_ID STREQUAL "Clang")
set(_real_fatbinary "${CMAKE_CUDA_FATBINARY}")
set(_fatbinary_wrapper
"${CMAKE_BINARY_DIR}/cmake-fatbinary-cuda13")
file(WRITE "${_fatbinary_wrapper}"
"#!/usr/bin/env bash
real_fatbinary=\"${_real_fatbinary}\"
"
[=[
translated=()
for argument in "$@"; do
case "$argument" in
-im=profile=sm_*,file=*)
value=${argument#-im=profile=sm_}
architecture=${value%%,*}
filename=${value#*,file=}
translated+=(
"--image3=kind=elf,sm=${architecture},file=${filename}"
)
;;
*)
translated+=("$argument")
;;
esac
done
exec "$real_fatbinary" "${translated[@]}"
]=])
file(CHMOD "${_fatbinary_wrapper}"
PERMISSIONS
OWNER_READ OWNER_WRITE OWNER_EXECUTE
GROUP_READ GROUP_EXECUTE
WORLD_READ WORLD_EXECUTE)
set(CMAKE_CUDA_FATBINARY "${_fatbinary_wrapper}")
endif()
set(CUSPARSE_FOUND TRUE)
set(CUBLAS_FOUND TRUE)
# Initialize CUSPARSE_LIBRARIES and CUBLAS_LIBRARIES:
@@ -278,13 +239,6 @@ else()
set(MFEM_DEBUG OFF)
endif()
# Shadow warnings for clang only; GCC's -Wshadow flags more.
if (CMAKE_CXX_COMPILER_ID MATCHES "Clang")
set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} -pedantic -Wall -Wshadow")
elseif (CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} -pedantic -Wall")
endif()
# Shared build on Windows
if (WIN32 AND BUILD_SHARED_LIBS)
# CMAKE_WINDOWS_EXPORT_ALL_SYMBOLS works only with MSVC?
@@ -647,13 +601,6 @@ 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)
@@ -790,16 +737,6 @@ 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()
@@ -807,7 +744,7 @@ if (MINGW)
target_link_libraries(mfem PRIVATE ws2_32)
endif()
if (MSVC)
target_compile_options(mfem PUBLIC "/wd4819" "/bigobj")
target_compile_options(mfem PUBLIC "/wd4819")
endif()
message(STATUS "TPL_INCLUDE_DIRS = ${TPL_INCLUDE_DIRS}")
target_include_directories(mfem
@@ -836,7 +773,7 @@ set_target_properties(mfem PROPERTIES SOVERSION "${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 PUBLIC
target_compile_definitions(mfem PRIVATE
"MFEM_CONFIG_FILE=\"${PROJECT_BINARY_DIR}/config/_config.hpp\"")
endif()
@@ -896,15 +833,16 @@ if (MFEM_ENABLE_TESTING)
add_mfem_target(${MFEM_ALL_TESTS_TARGET_NAME} OFF)
add_subdirectory(tests EXCLUDE_FROM_ALL)
# 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}
${MFEM_ENABLE_BENCHMARKS})
if (MFEM_ENABLE_BENCHMARKS)
add_subdirectory(tests/benchmarks) #install benchmarks if enabled
else()
add_subdirectory(tests/benchmarks EXCLUDE_FROM_ALL)
if (MFEM_USE_BENCHMARK)
# Create a target for all benchmarks and, optionally, enable it.
set(MFEM_ALL_BENCHMARKS_TARGET_NAME benchmarks)
add_mfem_target(${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()
endif()
endif()
@@ -1084,7 +1022,6 @@ install(EXPORT ${PROJECT_NAME_UC}Targets
install(DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/data
DESTINATION ${MFEM_INSTALL_DIR} OPTIONAL)
#-------------------------------------------------------------------------------
# Create 'config.mk' from 'config.mk.in' for the build and install locations and
# define install rules for 'config.mk' and 'test.mk'
+1
View File
@@ -6,6 +6,7 @@
<a href="https://github.com/mfem/mfem/blob/master/LICENSE"><img alt="License" src="https://img.shields.io/badge/License-BSD-blue.svg"></a>
<a href="https://github.com/mfem/mfem/releases/latest"><img alt="GitHub release" src="https://img.shields.io/github/v/release/mfem/mfem"></a>
<a href="https://github.com/mfem/mfem/actions/workflows/repo-check.yml?query=branch%3Amaster"><img alt="Repo check" src="https://github.com/mfem/mfem/actions/workflows/repo-check.yml/badge.svg?branch=master"></a>
<a href="https://github.com/mfem/mfem/actions/workflows/mfem-analysis.yml?query=branch%3Amaster"><img alt="Build Analysis" src="https://github.com/mfem/mfem/actions/workflows/mfem-analysis.yml/badge.svg?branch=master"></a>
<a href="https://github.com/mfem/mfem/actions/workflows/builds-and-tests.yml?query=branch%3Amaster"><img alt="Builds and Tests" src="https://github.com/mfem/mfem/actions/workflows/builds-and-tests.yml/badge.svg?branch=master"></a>
<a href="https://ci.appveyor.com/project/mfem/mfem"><img alt="Build Status" src="https://ci.appveyor.com/api/projects/status/19non9sqm6msi2wy?svg=true"></a>
<a href="https://docs.mfem.org/html/index.html"><img alt="Documentation" src="https://img.shields.io/badge/code-documented-brightgreen.svg"></a>
+9 -9
View File
@@ -22,15 +22,15 @@ include(MfemCmakeUtilities)
mfem_find_package(SuiteSparse SuiteSparse SuiteSparse_DIR "" "" "" ""
"Paths to headers required by SuiteSparse."
"Libraries required by SuiteSparse."
ADD_COMPONENT "UMFPACK" "include;include/suitesparse;suitesparse" umfpack.h "lib" umfpack
ADD_COMPONENT "KLU" "include;include/suitesparse;suitesparse" klu.h "lib" klu
ADD_COMPONENT "AMD" "include;include/suitesparse;suitesparse" amd.h "lib" amd
ADD_COMPONENT "BTF" "include;include/suitesparse;suitesparse" btf.h "lib" btf
ADD_COMPONENT "CHOLMOD" "include;include/suitesparse;suitesparse" cholmod.h "lib" cholmod
ADD_COMPONENT "COLAMD" "include;include/suitesparse;suitesparse" colamd.h "lib" colamd
ADD_COMPONENT "CAMD" "include;include/suitesparse;suitesparse" camd.h "lib" camd
ADD_COMPONENT "CCOLAMD" "include;include/suitesparse;suitesparse" ccolamd.h "lib" ccolamd
ADD_COMPONENT "config" "include;include/suitesparse;suitesparse" SuiteSparse_config.h "lib"
ADD_COMPONENT "UMFPACK" "include;suitesparse" umfpack.h "lib" umfpack
ADD_COMPONENT "KLU" "include;suitesparse" klu.h "lib" klu
ADD_COMPONENT "AMD" "include;suitesparse" amd.h "lib" amd
ADD_COMPONENT "BTF" "include;suitesparse" btf.h "lib" btf
ADD_COMPONENT "CHOLMOD" "include;suitesparse" cholmod.h "lib" cholmod
ADD_COMPONENT "COLAMD" "include;suitesparse" colamd.h "lib" colamd
ADD_COMPONENT "CAMD" "include;suitesparse" camd.h "lib" camd
ADD_COMPONENT "CCOLAMD" "include;suitesparse" ccolamd.h "lib" ccolamd
ADD_COMPONENT "config" "include;suitesparse" SuiteSparse_config.h "lib"
suitesparseconfig)
if (SuiteSparse_FOUND AND METIS_VERSION_5)
+2 -2
View File
@@ -18,9 +18,9 @@
#define MFEM_CONFIG_HPP
#ifdef MFEM_CONFIG_FILE
#include MFEM_CONFIG_FILE // IWYU pragma: export
#include MFEM_CONFIG_FILE
#else
#include "_config.hpp" // IWYU pragma: export
#include "_config.hpp"
#endif
#include <cstdint>
+1 -7
View File
@@ -27,13 +27,7 @@ MPICXX = mpicxx
BASE_FLAGS = -std=c++17
OPTIM_FLAGS = -O3 $(BASE_FLAGS)
# Shadow warnings for clang only; GCC's -Wshadow flags more.
SHADOW_WARNING_FLAG = $(if $(findstring clang,\
$(shell $(MFEM_HOST_CXX) --version 2>/dev/null)),-Wshadow,)
WARNING_FLAGS = -pedantic -Wall $(SHADOW_WARNING_FLAG)
DEBUG_FLAGS = $(strip -g $(addprefix $(XCOMPILER),$(WARNING_FLAGS)) $(BASE_FLAGS))
DEBUG_FLAGS = -g $(XCOMPILER)-Wall $(BASE_FLAGS)
# Prefixes for passing flags to the compiler and linker when using CXX or MPICXX
CXX_XCOMPILER =
-5
View File
@@ -39,8 +39,3 @@ when a picture was added for documentation.
If that is the case, make sure the failure is indeed justified, and rerun the
push command with the `--no-verify` option. This will skip the hooks, allowing
you to push those changes.
The `branch-history` check is run automatically through GitHub Actions. If a
branch is known to have a large number of changes that are legitimate, the
check can be overridden by setting the label 'branch-history-override' on the
pull request.
-38
View File
@@ -1,38 +0,0 @@
MFEM mesh v1.0
#
# MFEM Geometry Types (see fem/geom.hpp):
#
# POINT = 0
# SEGMENT = 1
# TRIANGLE = 2
# SQUARE = 3
# TETRAHEDRON = 4
# CUBE = 5
# PRISM = 6
# PYRAMID = 7
dimension
2
elements
2
1 3 0 1 4 3
1 2 1 2 4
boundary
5
1 1 0 1
1 1 1 2
1 1 2 4
1 1 4 3
1 1 3 0
vertices
5
2
0 0
1 0
2 0
0 1
1 1
-4
View File
@@ -201,7 +201,6 @@ namespace mfem {
* - <a class="el" href="nurbs__naca__cmesh_8cpp_source.html">NURBS NACA Mesher</a>: generate NURBS based mesh around a NACA foil
* - <a class="el" href="nurbs__printfunc_8cpp_source.html">NURBS Printer</a>: print the NURBS-basis
* - <a class="el" href="nurbs__mesh_info_8cpp_source.html">NURBS Mesh info</a>: print the info of a NURBS mesh
* - <a class="el" href="nurbs__surface_8cpp_source.html">NURBS Surface</a>: interpolate a 3D Surface in a NURBS Patch
*
* <H3>Miniapps</H3>
* - <a class="el" href="volta_8cpp_source.html">Volta</a>: simple electrostatics simulation code
@@ -246,9 +245,6 @@ namespace mfem {
* - <a class="el" href="pdiffusion_8cpp_source.html">DPG Diffusion example</a>: DPG formulation for the diffusion problem
* - <a class="el" href="pmaxwell_8cpp_source.html">DPG Maxwell example</a>: DPG formulation for the indefinite Maxwell problem
* - <a class="el" href="lor__elast_8cpp_source.html">LOR Elasticity</a>: solve linear elasticity with LOR preconditioning on GPUs
* - <a class="el" href="reflector_8cpp_source.html">Reflector Miniapp</a>: reflect a mesh about a plane
* - <a class="el" href="ref321_8cpp_source.html">3:1 Refinement Miniapp</a>: perform 3:1 anisotropic mesh refinements
* - <a class="el" href="pref321_8cpp_source.html">3:1 Refinement Miniapp</a>: parallel 3:1 anisotropic mesh refinements
*
* See also the <a class="el" href="https://mfem.org/examples/">examples documentation</a> online.
*/
-1
View File
@@ -47,7 +47,6 @@ list(APPEND ALL_EXE_SRCS
ex39.cpp
ex40.cpp
ex41.cpp
# jitplayground.cpp
)
if (MFEM_USE_MPI)
-548
View File
@@ -1,548 +0,0 @@
#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
@@ -1,58 +0,0 @@
#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);
}
+16 -50
View File
@@ -57,8 +57,6 @@ set(SRCS
integ/lininteg_domain_grad.cpp
integ/lininteg_domain_vectorfe.cpp
integ/nonlininteg_vecconvection_pa.cpp
integ/nonlininteg_vecconvection_pa_diag.cpp
integ/nonlininteg_vecconvection_pa_grad.cpp
integ/nonlininteg_vecconvection_mf.cpp
coefficient.cpp
complex_fem.cpp
@@ -67,7 +65,6 @@ set(SRCS
dgmassinv.cpp
doftrans.cpp
dfem/doperator.cpp
dfem/backends/local_qf/kernels.cpp
eltrans.cpp
batchitrans.cpp
estimators.cpp
@@ -124,11 +121,6 @@ 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
@@ -141,7 +133,7 @@ set(SRCS
tmop/assemble/diag2.cpp
tmop/assemble/grad2_limit.cpp
tmop/assemble/grad2.cpp
tmop/assemble/diag3_limit.cpp
tmop/assemble/diag3_limit.cpp
tmop/assemble/diag3.cpp
tmop/assemble/grad3_limit.cpp
tmop/assemble/grad3.cpp
@@ -212,11 +204,7 @@ set(HDRS
integ/bilininteg_mass_kernels.hpp
integ/bilininteg_mass_pa_simplices.hpp
integ/bilininteg_vecdiffusion_pa.hpp
integ/bilininteg_vecdiv_pa.hpp
integ/bilininteg_vecmass_pa.hpp
integ/nonlininteg_vecconvection_pa.hpp
integ/nonlininteg_vecconvection_pa_diag.hpp
integ/nonlininteg_vecconvection_pa_grad.hpp
coefficient.hpp
complex_fem.hpp
convergence.hpp
@@ -225,32 +213,13 @@ set(HDRS
dgmassinv_kernels.hpp
doftrans.hpp
dfem/doperator.hpp
dfem/fielddescriptor.hpp
dfem/fieldoperator.hpp
dfem/integrator_ctx.hpp
dfem/integrate.hpp
dfem/parameterspace.hpp
dfem/tensor_functions.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
@@ -315,10 +284,8 @@ 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
@@ -344,7 +311,6 @@ set(HDRS
tmop_tools.hpp
tmop_amr.hpp
gslib.hpp
gslib/gslib_kernel_helpers.hpp
transfer.hpp
hyperbolic.hpp
integrator.hpp
@@ -353,36 +319,36 @@ 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
+25
View File
@@ -1255,6 +1255,31 @@ void BilinearForm::Mult(const Vector &x, Vector &y) const
}
}
void BilinearForm::AddMult(const Vector &x, Vector &y, const real_t a) const
{
if (ext)
{
ext->AddMult(x, y, a);
}
else
{
mat->AddMult(x, y, a);
}
}
void BilinearForm::AddMultTranspose(const Vector &x, Vector &y,
const real_t a) const
{
if (ext)
{
ext->AddMultTranspose(x, y, a);
}
else
{
mat->AddMultTranspose(x, y, a);
}
}
void BilinearForm::MultTranspose(const Vector & x, Vector & y) const
{
if (ext)
+3 -4
View File
@@ -307,8 +307,8 @@ public:
{ mat->Mult(x, y); mat_e->AddMult(x, y); }
/// Add the matrix vector multiple to a vector: $ y += a M x $
void AddMult(const Vector &x, Vector &y, const real_t a = 1.0) const override
{ mat -> AddMult (x, y, a); }
void AddMult(const Vector &x, Vector &y,
const real_t a = 1.0) const override;
/** @brief Add the original uneliminated matrix vector multiple to a vector.
The original matrix is $ M + Me $ so we have:
@@ -318,8 +318,7 @@ public:
/// Add the matrix transpose vector multiplication: $ y += a M^T x $
void AddMultTranspose(const Vector & x, Vector & y,
const real_t a = 1.0) const override
{ mat->AddMultTranspose(x, y, a); }
const real_t a = 1.0) const override;
/** @brief Add the original uneliminated matrix transpose vector
multiple to a vector. The original matrix is $ M + M_e $
+57 -31
View File
@@ -1110,20 +1110,36 @@ public:
MixedDotProductIntegrator(VectorCoefficient &vq)
: MixedScalarVectorIntegrator(vq, true) {}
inline virtual bool VerifyFiniteElementTypes(
inline bool VerifyFiniteElementTypes(
const FiniteElement & trial_fe,
const FiniteElement & test_fe) const
const FiniteElement & test_fe) const override
{
return (trial_fe.GetRangeType() == mfem::FiniteElement::VECTOR &&
test_fe.GetRangeType() == mfem::FiniteElement::SCALAR );
}
inline virtual const char * FiniteElementTypeFailureMessage() const
inline const char * FiniteElementTypeFailureMessage() const override
{
return "MixedDotProductIntegrator: "
"Trial space must be a vector field "
"and the test space must be a scalar field";
}
using BilinearFormIntegrator::AssemblePA;
void AssemblePA(const FiniteElementSpace &trial_fes,
const FiniteElementSpace &test_fes) override;
void AddMultPA(const Vector&, Vector&) const override;
void AddMultTransposePA(const Vector&, Vector&) const override;
private:
Vector pa_data;
const DofToQuad *mapsO = nullptr; ///< Not owned. Trial open map.
const DofToQuad *mapsC = nullptr; ///< Not owned. Trial closed map.
const DofToQuad *mapsTest = nullptr; ///< Not owned. Scalar test map.
const GeometricFactors *geom = nullptr;///< Not owned.
int dim = 0, ne = 0, dofs1D = 0, dofs1Dtest = 0, quad1D = 0;
bool test_map_integral = false;
};
/** Class for integrating the bilinear form $a(u,v) := (-\vec{V} \cdot u, \nabla \cdot v)$ in 2D or
@@ -2689,22 +2705,14 @@ public:
void AddMultMF(const Vector &x, Vector &y) const override;
bool SupportsCeed() const override { return DeviceCanUseCeed(); }
// PA AddMultPA kernels
using VectorMassAddMultPAType =
void(*)(const int, const int,
const Array<real_t>&, const Vector&,
const Vector&, Vector&, const int, const int);
MFEM_REGISTER_KERNELS(VectorMassAddMultPA,
VectorMassAddMultPAType,
(int, int, int));
// PA DiagonalPA kernels
using VectorMassAssembleDiagonalPAType =
void(*)(const int, const int, const int,
const real_t*, const real_t*, real_t*);
MFEM_REGISTER_KERNELS(VectorMassAssembleDiagonalPA,
VectorMassAssembleDiagonalPAType,
(int /*dim*/, int /*q1d*/));
};
@@ -3129,24 +3137,6 @@ public:
void AddMultPA(const Vector &x, Vector &y) const override;
void AddMultTransposePA(const Vector &x, Vector &y) const override;
using VectorDivergenceAddMultPAType =
void (*)(const int ne,
const Array<real_t> &b, const Array<real_t> &g, const Array<real_t> &bt,
const Vector &op, const Vector &x, Vector &y,
const int tr_d1d, const int te_d1d, const int q1d);
MFEM_REGISTER_KERNELS(VectorDivergenceAddMultPA,
VectorDivergenceAddMultPAType,
(int, int, int, int));
using VectorDivergenceAddMultTransposePAType =
void (*)(const int ne,
const Array<real_t> &bt, const Array<real_t> &gt, const Array<real_t> &b,
const Vector &q, const Vector &x, Vector &y,
const int tr_d1d, const int te_d1d, const int q1d);
MFEM_REGISTER_KERNELS(VectorDivergenceAddMultTransposePA,
VectorDivergenceAddMultTransposePAType,
(int, int, int, int));
static const IntegrationRule &GetRule(const FiniteElement &trial_fe,
const FiniteElement &test_fe,
const ElementTransformation &Trans);
@@ -3955,7 +3945,7 @@ class DiscreteInterpolator : public BilinearFormIntegrator { };
/** Class for constructing the gradient as a DiscreteLinearOperator from an
$H^1$-conforming space to an $H(curl$-conforming space. The range space can be
$H^1$-conforming space to an $H(curl)$-conforming space. The range space can be
vector $L_2$ space as well. */
class GradientInterpolator : public DiscreteInterpolator
{
@@ -4064,12 +4054,48 @@ public:
discrete curl matrix. */
class CurlInterpolator : public DiscreteInterpolator
{
int dim, ne;
// "dof" are the domain fespace dof counts
int ndof_o;
// "quads" are the range fespace dof counts
int nquad_o;
Vector pa_data;
public:
CurlInterpolator();
void AssembleElementMatrix2(const FiniteElement &dom_fe,
const FiniteElement &ran_fe,
ElementTransformation &Trans,
DenseMatrix &elmat) override
{ ran_fe.ProjectCurl(dom_fe, Trans, elmat); }
void AssemblePA(const FiniteElementSpace &dom_fes,
const FiniteElementSpace &ran_fes) override;
void AssemblePA(const FiniteElementSpace &fes) override
{
AssemblePA(fes, fes);
}
void AddMultPA(const Vector &x, Vector &y) const override;
void AddMultTransposePA(const Vector &x, Vector &y) const override;
using ApplyKernelType = void (*)(const int ne, const int ndof_o,
const int nquad_o, const Vector &pa,
const Vector &x, Vector &y);
/// arguments: DIM, ndof_o, nquad_o
MFEM_REGISTER_KERNELS(ApplyPAKernels, ApplyKernelType, (int, int, int));
/// arguments: DIM, ndof_o, nquad_o
MFEM_REGISTER_KERNELS(ApplyTPAKernels, ApplyKernelType, (int, int, int));
template <int DIM, int NDOF_O, int NQUAD_O> static void AddSpecialization()
{
ApplyPAKernels::Specialization<DIM, NDOF_O, NQUAD_O>::Add();
ApplyTPAKernels::Specialization<DIM, NDOF_O, NQUAD_O>::Add();
}
struct Kernels { Kernels(); };
};
+8 -931
View File
@@ -237,81 +237,6 @@ ComplexGridFunction::ProjectBdrCoefficientTangent(VectorCoefficient
gfi->SyncAliasMemory(*this);
}
real_t
ComplexGridFunction::ComputeLpError(const real_t p,
Coefficient &exsolr,
Coefficient &exsoli,
Coefficient *weight,
const IntegrationRule *irs[],
const Array<int> *elems) const
{
real_t error = 0.0;
const FiniteElement *fe;
ElementTransformation *T;
Vector valsr;
Vector valsi;
const GridFunction& gf_r = real();
const GridFunction& gf_i = imag();
for (int i = 0; i < fes->GetNE(); i++)
{
if (elems != NULL && (*elems)[i] == 0) { continue; }
fe = fes->GetFE(i);
const IntegrationRule *ir;
if (irs)
{
ir = irs[fe->GetGeomType()];
}
else
{
int intorder = 2*fe->GetOrder() + 3;
ir = &(IntRules.Get(fe->GetGeomType(), intorder));
}
real_t elem_error = 0.0;
gf_r.GetValues(i, *ir, valsr);
gf_i.GetValues(i, *ir, valsi);
T = fes->GetElementTransformation(i);
for (int j = 0; j < ir->GetNPoints(); j++)
{
const IntegrationPoint &ip = ir->IntPoint(j);
T->SetIntPoint(&ip);
real_t diffr = valsr(j) - exsolr.Eval(*T, ip);
real_t diffi = valsi(j) - exsoli.Eval(*T, ip);
real_t diff = hypot(diffr, diffi);
if (p < infinity())
{
diff = pow(diff, p);
if (weight)
{
diff *= weight->Eval(*T, ip);
}
elem_error += ip.weight * T->Weight() * diff;
}
else
{
if (weight)
{
diff *= weight->Eval(*T, ip);
}
error = std::max(error, diff);
}
}
if (p < infinity())
{
// negative quadrature weights may cause the error to be negative
error += fabs(elem_error);
}
}
if (p < infinity())
{
error = pow(error, 1./p);
}
return error;
}
void ComplexGridFunction::Save(std::ostream &os) const
{
os << "ComplexGridFunction\n";
@@ -718,8 +643,8 @@ SesquilinearForm::FormLinearSystem(const Array<int> &ess_tdof_list,
// A = A_r + i A_i
A.Clear();
if ((!A_r.Ptr() || A_r.Type() == Operator::MFEM_SPARSEMAT) &&
(!A_i.Ptr() || A_i.Type() == Operator::MFEM_SPARSEMAT))
if ( A_r.Type() == Operator::MFEM_SPARSEMAT ||
A_i.Type() == Operator::MFEM_SPARSEMAT )
{
ComplexSparseMatrix * A_sp =
new ComplexSparseMatrix(A_r.As<SparseMatrix>(),
@@ -779,8 +704,8 @@ SesquilinearForm::FormSystemMatrix(const Array<int> &ess_tdof_list,
// A = A_r + i A_i
A.Clear();
if ((!A_r.Ptr() || A_r.Type() == Operator::MFEM_SPARSEMAT) &&
(!A_i.Ptr() || A_i.Type() == Operator::MFEM_SPARSEMAT))
if ( A_r.Type() == Operator::MFEM_SPARSEMAT ||
A_i.Type() == Operator::MFEM_SPARSEMAT )
{
ComplexSparseMatrix * A_sp =
new ComplexSparseMatrix(A_r.As<SparseMatrix>(),
@@ -843,426 +768,6 @@ SesquilinearForm::Update(FiniteElementSpace *nfes)
if ( blfi ) { blfi->Update(nfes); }
}
bool
MixedSesquilinearForm::RealInteg()
{
int nint = mblfr->GetDBFI()->Size() + mblfr->GetBBFI()->Size() +
mblfr->GetFBFI()->Size() + mblfr->GetBFBFI()->Size() +
mblfr->GetTFBFI()->Size() + mblfr->GetBTFBFI()->Size();
return (nint != 0);
}
bool
MixedSesquilinearForm::ImagInteg()
{
int nint = mblfi->GetDBFI()->Size() + mblfi->GetBBFI()->Size() +
mblfi->GetFBFI()->Size() + mblfi->GetBFBFI()->Size() +
mblfi->GetTFBFI()->Size() + mblfi->GetBTFBFI()->Size();
return (nint != 0);
}
MixedSesquilinearForm::MixedSesquilinearForm(FiniteElementSpace * trial_fes,
FiniteElementSpace * test_fes,
ComplexOperator::Convention convention)
: conv(convention),
mblfr(new mfem::MixedBilinearForm(trial_fes, test_fes)),
mblfi(new mfem::MixedBilinearForm(trial_fes, test_fes))
{
}
MixedSesquilinearForm::MixedSesquilinearForm(FiniteElementSpace * trial_fes,
FiniteElementSpace * test_fes,
MixedBilinearForm * bfr,
MixedBilinearForm * bfi,
ComplexOperator::Convention convention)
: conv(convention),
mblfr(new MixedBilinearForm(trial_fes, test_fes, bfr)),
mblfi(new MixedBilinearForm(trial_fes, test_fes, bfi))
{
}
MixedSesquilinearForm::~MixedSesquilinearForm()
{
delete mblfr;
delete mblfi;
}
void
MixedSesquilinearForm::AddDomainIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag)
{
if (bfi_real)
{
mblfr->AddDomainIntegrator(bfi_real);
}
if (bfi_imag)
{
mblfi->AddDomainIntegrator(bfi_imag);
}
}
void
MixedSesquilinearForm::AddDomainIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag,
Array<int> & elem_marker)
{
if (bfi_real)
{
mblfr->AddDomainIntegrator(bfi_real, elem_marker);
}
if (bfi_imag)
{
mblfi->AddDomainIntegrator(bfi_imag, elem_marker);
}
}
void
MixedSesquilinearForm::AddBoundaryIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag)
{
if (bfi_real)
{
mblfr->AddBoundaryIntegrator(bfi_real);
}
if (bfi_imag)
{
mblfi->AddBoundaryIntegrator(bfi_imag);
}
}
void
MixedSesquilinearForm::AddBoundaryIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag,
Array<int> & bdr_marker)
{
if (bfi_real)
{
mblfr->AddBoundaryIntegrator(bfi_real, bdr_marker);
}
if (bfi_imag)
{
mblfi->AddBoundaryIntegrator(bfi_imag, bdr_marker);
}
}
void
MixedSesquilinearForm::AddInteriorFaceIntegrator(BilinearFormIntegrator *
bfi_real,
BilinearFormIntegrator * bfi_imag)
{
if (bfi_real)
{
mblfr->AddInteriorFaceIntegrator(bfi_real);
}
if (bfi_imag)
{
mblfi->AddInteriorFaceIntegrator(bfi_imag);
}
}
void
MixedSesquilinearForm::AddBdrFaceIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag)
{
if (bfi_real)
{
mblfr->AddBdrFaceIntegrator(bfi_real);
}
if (bfi_imag)
{
mblfi->AddBdrFaceIntegrator(bfi_imag);
}
}
void
MixedSesquilinearForm::AddBdrFaceIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag,
Array<int> & bdr_marker)
{
if (bfi_real)
{
mblfr->AddBdrFaceIntegrator(bfi_real, bdr_marker);
}
if (bfi_imag)
{
mblfi->AddBdrFaceIntegrator(bfi_imag, bdr_marker);
}
}
void MixedSesquilinearForm::AddTraceFaceIntegrator(BilinearFormIntegrator *
bfi_real,
BilinearFormIntegrator * bfi_imag)
{
if (bfi_real)
{
mblfr->AddTraceFaceIntegrator(bfi_real);
}
if (bfi_imag)
{
mblfi->AddTraceFaceIntegrator(bfi_imag);
}
}
void MixedSesquilinearForm::AddBdrTraceFaceIntegrator(BilinearFormIntegrator
*bfi_real,
BilinearFormIntegrator *bfi_imag)
{
if (bfi_real)
{
mblfr->AddBdrTraceFaceIntegrator(bfi_real);
}
if (bfi_imag)
{
mblfi->AddBdrTraceFaceIntegrator(bfi_imag);
}
}
void MixedSesquilinearForm::AddBdrTraceFaceIntegrator(BilinearFormIntegrator
*bfi_real,
BilinearFormIntegrator *bfi_imag,
Array<int> &bdr_marker)
{
if (bfi_real)
{
mblfr->AddBdrTraceFaceIntegrator(bfi_real, bdr_marker);
}
if (bfi_imag)
{
mblfi->AddBdrTraceFaceIntegrator(bfi_imag, bdr_marker);
}
}
void
MixedSesquilinearForm::Assemble(int skip_zeros)
{
mblfr->Assemble(skip_zeros);
mblfi->Assemble(skip_zeros);
}
void
MixedSesquilinearForm::Finalize(int skip_zeros)
{
mblfr->Finalize(skip_zeros);
mblfi->Finalize(skip_zeros);
}
ComplexSparseMatrix *
MixedSesquilinearForm::AssembleComplexSparseMatrix()
{
return new mfem::ComplexSparseMatrix(
&mblfr->SpMat(), &mblfi->SpMat(), false, false, conv);
}
void
MixedSesquilinearForm::FormRectangularLinearSystem(const Array<int> &
ess_trial_tdof_list,
const Array<int> & ess_test_tdof_list,
Vector & x,
Vector & b,
OperatorHandle & A,
Vector & X,
Vector & B)
{
FiniteElementSpace * fes_trial = mblfr->TrialFESpace();
FiniteElementSpace * fes_test = mblfr->TestFESpace();
const int vsize_trial = fes_trial->GetVSize();
const int vsize_test = fes_test->GetVSize();
// Allocate temporary Vector
Vector b_0;
b_0.UseDevice(true);
b_0.SetSize(vsize_test);
b_0 = 0.0;
// Extract the real and imaginary parts of the input Vectors
MFEM_ASSERT(x.Size() == 2 * vsize_trial,
"Input GridFunction of incorrect size!");
x.Read();
Vector x_r;
x_r.MakeRef(x, 0, vsize_trial);
Vector x_i;
x_i.MakeRef(x, vsize_trial, vsize_trial);
MFEM_ASSERT(b.Size() == 2 * vsize_test, "Input LinearForm of incorrect size!");
b.Read();
Vector b_r;
b_r.MakeRef(b, 0, vsize_test);
Vector b_i;
b_i.MakeRef(b, vsize_test, vsize_test);
if (conv == ComplexOperator::BLOCK_SYMMETRIC)
{
b_i *= -1.0;
}
const int tvsize_trial = fes_trial->GetTrueVSize();
const int tvsize_test = fes_test->GetTrueVSize();
OperatorHandle A_r, A_i;
X.UseDevice(true);
X.SetSize(2 * tvsize_trial);
X = 0.0;
B.UseDevice(true);
B.SetSize(2 * tvsize_test);
B = 0.0;
Vector X_r;
X_r.MakeRef(X, 0, tvsize_trial);
Vector X_i;
X_i.MakeRef(X, tvsize_trial, tvsize_trial);
Vector B_r;
B_r.MakeRef(B, 0, tvsize_test);
Vector B_i;
B_i.MakeRef(B, tvsize_test, tvsize_test);
Vector X_0, B_0;
if (RealInteg())
{
b_0 = b_r;
mblfr->FormRectangularLinearSystem(
ess_trial_tdof_list, ess_test_tdof_list, x_r, b_0, A_r, X_0, B_0);
X_r = X_0;
B_r = B_0;
b_0 = b_i;
mblfr->FormRectangularLinearSystem(
ess_trial_tdof_list, ess_test_tdof_list, x_i, b_0, A_r, X_0, B_0);
X_i = X_0;
B_i = B_0;
if (ImagInteg())
{
b_0 = 0.0;
mblfi->FormRectangularLinearSystem(
ess_trial_tdof_list, ess_test_tdof_list, x_i, b_0, A_i, X_0, B_0);
B_r -= B_0;
b_0 = 0.0;
mblfi->FormRectangularLinearSystem(
ess_trial_tdof_list, ess_test_tdof_list, x_r, b_0, A_i, X_0, B_0);
B_i += B_0;
}
}
else if (ImagInteg())
{
b_0 = b_i;
mblfi->FormRectangularLinearSystem(
ess_trial_tdof_list, ess_test_tdof_list, x_r, b_0, A_i, X_0, B_0);
X_r = X_0;
B_i = B_0;
b_0 = b_r;
b_0 *= -1.0;
mblfi->FormRectangularLinearSystem(
ess_trial_tdof_list, ess_test_tdof_list, x_i, b_0, A_i, X_0, B_0);
X_i = X_0;
B_r = B_0;
B_r *= -1.0;
}
else
{
MFEM_ABORT("Real and Imaginary part of the Mixed Sesquilinear form are empty");
}
if (conv == ComplexOperator::BLOCK_SYMMETRIC)
{
B_i *= -1.0;
b_i *= -1.0;
}
x_r.SyncAliasMemory(x);
x_i.SyncAliasMemory(x);
b_r.SyncAliasMemory(b);
b_i.SyncAliasMemory(b);
X_r.SyncAliasMemory(X);
X_i.SyncAliasMemory(X);
B_r.SyncAliasMemory(B);
B_i.SyncAliasMemory(B);
// A = A_r + i A_i
A.Clear();
if ((!A_r.Ptr() || A_r.Type() == Operator::MFEM_SPARSEMAT) &&
(!A_i.Ptr() || A_i.Type() == Operator::MFEM_SPARSEMAT))
{
ComplexSparseMatrix * A_hyp =
new ComplexSparseMatrix(A_r.As<SparseMatrix>(),
A_i.As<SparseMatrix>(),
A_r.OwnsOperator(),
A_i.OwnsOperator(),
conv);
A.Reset<ComplexSparseMatrix>(A_hyp, true);
}
else
{
ComplexOperator * A_op = new ComplexOperator(A_r.As<Operator>(),
A_i.As<Operator>(),
A_r.OwnsOperator(),
A_i.OwnsOperator(),
conv);
A.Reset<ComplexOperator>(A_op, true);
}
A_r.SetOperatorOwner(false);
A_i.SetOperatorOwner(false);
}
void
MixedSesquilinearForm::FormRectangularSystemMatrix(const mfem::Array<int> &
ess_trial_tdof_list,
const mfem::Array<int> & ess_test_tdof_list,
mfem::OperatorHandle & A)
{
OperatorHandle A_r, A_i;
if (RealInteg())
{
mblfr->FormRectangularSystemMatrix(ess_trial_tdof_list, ess_test_tdof_list,
A_r);
}
if (ImagInteg())
{
mblfi->FormRectangularSystemMatrix(ess_trial_tdof_list, ess_test_tdof_list,
A_i);
}
if (!RealInteg() && !ImagInteg())
{
MFEM_ABORT("Both Real and Imaginary part of the Mixed Sesquilinear form are empty");
}
// A = A_r + i A_i
A.Clear();
if ((!A_r.Ptr() || A_r.Type() == Operator::MFEM_SPARSEMAT) &&
(!A_i.Ptr() || A_i.Type() == Operator::MFEM_SPARSEMAT))
{
ComplexSparseMatrix * A_hyp =
new ComplexSparseMatrix(A_r.As<SparseMatrix>(),
A_i.As<SparseMatrix>(),
A_r.OwnsOperator(),
A_i.OwnsOperator(),
conv);
A.Reset<ComplexSparseMatrix>(A_hyp, true);
}
else
{
ComplexOperator * A_op = new ComplexOperator(A_r.As<Operator>(),
A_i.As<Operator>(),
A_r.OwnsOperator(),
A_i.OwnsOperator(),
conv);
A.Reset<ComplexOperator>(A_op, true);
}
A_r.SetOperatorOwner(false);
A_i.SetOperatorOwner(false);
}
void
MixedSesquilinearForm::Update()
{
mblfr->Update();
mblfi->Update();
}
#ifdef MFEM_USE_MPI
@@ -2034,8 +1539,8 @@ ParSesquilinearForm::FormLinearSystem(const Array<int> &ess_tdof_list,
// A = A_r + i A_i
A.Clear();
if ((!A_r.Ptr() || A_r.Type() == Operator::Hypre_ParCSR) &&
(!A_i.Ptr() || A_i.Type() == Operator::Hypre_ParCSR))
if ( A_r.Type() == Operator::Hypre_ParCSR ||
A_i.Type() == Operator::Hypre_ParCSR )
{
ComplexHypreParMatrix * A_hyp =
new ComplexHypreParMatrix(A_r.As<HypreParMatrix>(),
@@ -2102,8 +1607,8 @@ ParSesquilinearForm::FormSystemMatrix(const Array<int> &ess_tdof_list,
// A = A_r + i A_i
A.Clear();
if ((!A_r.Ptr() || A_r.Type() == Operator::Hypre_ParCSR) &&
(!A_i.Ptr() || A_i.Type() == Operator::Hypre_ParCSR))
if ( A_r.Type() == Operator::Hypre_ParCSR ||
A_i.Type() == Operator::Hypre_ParCSR )
{
ComplexHypreParMatrix * A_hyp =
new ComplexHypreParMatrix(A_r.As<HypreParMatrix>(),
@@ -2161,434 +1666,6 @@ ParSesquilinearForm::Update(FiniteElementSpace *nfes)
if ( pblfi ) { pblfi->Update(nfes); }
}
bool
ParMixedSesquilinearForm::RealInteg()
{
int nint = pmblfr->GetDBFI()->Size() + pmblfr->GetBBFI()->Size() +
pmblfr->GetFBFI()->Size() + pmblfr->GetBFBFI()->Size() +
pmblfr->GetTFBFI()->Size() + pmblfr->GetBTFBFI()->Size();
return (nint != 0);
}
bool
ParMixedSesquilinearForm::ImagInteg()
{
int nint = pmblfi->GetDBFI()->Size() + pmblfi->GetBBFI()->Size() +
pmblfi->GetFBFI()->Size() + pmblfi->GetBFBFI()->Size() +
pmblfi->GetTFBFI()->Size() + pmblfi->GetBTFBFI()->Size();
return (nint != 0);
}
ParMixedSesquilinearForm::ParMixedSesquilinearForm(ParFiniteElementSpace *
trial_fes,
ParFiniteElementSpace * test_fes,
ComplexOperator::Convention convention)
: conv(convention),
pmblfr(new ParMixedBilinearForm(trial_fes, test_fes)),
pmblfi(new ParMixedBilinearForm(trial_fes, test_fes))
{
}
ParMixedSesquilinearForm::ParMixedSesquilinearForm(ParFiniteElementSpace *
trial_fes,
ParFiniteElementSpace * test_fes,
ParMixedBilinearForm * pbfr,
ParMixedBilinearForm * pbfi,
ComplexOperator::Convention convention)
: conv(convention),
pmblfr(new ParMixedBilinearForm(trial_fes, test_fes, pbfr)),
pmblfi(new ParMixedBilinearForm(trial_fes, test_fes, pbfi))
{
}
ParMixedSesquilinearForm::~ParMixedSesquilinearForm()
{
delete pmblfr;
delete pmblfi;
}
void
ParMixedSesquilinearForm::AddDomainIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag)
{
if (bfi_real)
{
pmblfr->AddDomainIntegrator(bfi_real);
}
if (bfi_imag)
{
pmblfi->AddDomainIntegrator(bfi_imag);
}
}
void
ParMixedSesquilinearForm::AddDomainIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag,
Array<int> & elem_marker)
{
if (bfi_real)
{
pmblfr->AddDomainIntegrator(bfi_real, elem_marker);
}
if (bfi_imag)
{
pmblfi->AddDomainIntegrator(bfi_imag, elem_marker);
}
}
void
ParMixedSesquilinearForm::AddBoundaryIntegrator(BilinearFormIntegrator *
bfi_real,
BilinearFormIntegrator * bfi_imag)
{
if (bfi_real)
{
pmblfr->AddBoundaryIntegrator(bfi_real);
}
if (bfi_imag)
{
pmblfi->AddBoundaryIntegrator(bfi_imag);
}
}
void
ParMixedSesquilinearForm::AddBoundaryIntegrator(BilinearFormIntegrator *
bfi_real,
BilinearFormIntegrator * bfi_imag,
Array<int> & bdr_marker)
{
if (bfi_real)
{
pmblfr->AddBoundaryIntegrator(bfi_real, bdr_marker);
}
if (bfi_imag)
{
pmblfi->AddBoundaryIntegrator(bfi_imag, bdr_marker);
}
}
void
ParMixedSesquilinearForm::AddInteriorFaceIntegrator(BilinearFormIntegrator *
bfi_real,
BilinearFormIntegrator * bfi_imag)
{
if (bfi_real)
{
pmblfr->AddInteriorFaceIntegrator(bfi_real);
}
if (bfi_imag)
{
pmblfi->AddInteriorFaceIntegrator(bfi_imag);
}
}
void
ParMixedSesquilinearForm::AddBdrFaceIntegrator(BilinearFormIntegrator *
bfi_real,
BilinearFormIntegrator * bfi_imag)
{
if (bfi_real)
{
pmblfr->AddBdrFaceIntegrator(bfi_real);
}
if (bfi_imag)
{
pmblfi->AddBdrFaceIntegrator(bfi_imag);
}
}
void
ParMixedSesquilinearForm::AddBdrFaceIntegrator(BilinearFormIntegrator *
bfi_real,
BilinearFormIntegrator * bfi_imag,
Array<int> & bdr_marker)
{
if (bfi_real)
{
pmblfr->AddBdrFaceIntegrator(bfi_real, bdr_marker);
}
if (bfi_imag)
{
pmblfi->AddBdrFaceIntegrator(bfi_imag, bdr_marker);
}
}
void ParMixedSesquilinearForm::AddTraceFaceIntegrator(BilinearFormIntegrator *
bfi_real,
BilinearFormIntegrator * bfi_imag)
{
if (bfi_real)
{
pmblfr->AddTraceFaceIntegrator(bfi_real);
}
if (bfi_imag)
{
pmblfi->AddTraceFaceIntegrator(bfi_imag);
}
}
void ParMixedSesquilinearForm::AddBdrTraceFaceIntegrator(
BilinearFormIntegrator *bfi_real,
BilinearFormIntegrator *bfi_imag)
{
if (bfi_real)
{
pmblfr->AddBdrTraceFaceIntegrator(bfi_real);
}
if (bfi_imag)
{
pmblfi->AddBdrTraceFaceIntegrator(bfi_imag);
}
}
void ParMixedSesquilinearForm::AddBdrTraceFaceIntegrator(
BilinearFormIntegrator *bfi_real,
BilinearFormIntegrator *bfi_imag,
Array<int> &bdr_marker)
{
if (bfi_real)
{
pmblfr->AddBdrTraceFaceIntegrator(bfi_real, bdr_marker);
}
if (bfi_imag)
{
pmblfi->AddBdrTraceFaceIntegrator(bfi_imag, bdr_marker);
}
}
void
ParMixedSesquilinearForm::Assemble(int skip_zeros)
{
pmblfr->Assemble(skip_zeros);
pmblfi->Assemble(skip_zeros);
}
void
ParMixedSesquilinearForm::Finalize(int skip_zeros)
{
pmblfr->Finalize(skip_zeros);
pmblfi->Finalize(skip_zeros);
}
ComplexHypreParMatrix *
ParMixedSesquilinearForm::ParallelAssemble()
{
return new ComplexHypreParMatrix(
pmblfr->ParallelAssemble(), pmblfi->ParallelAssemble(), true, true, conv);
}
void
ParMixedSesquilinearForm::FormRectangularLinearSystem(const Array<int> &
ess_trial_tdof_list,
const Array<int> & ess_test_tdof_list,
Vector & x,
Vector & b,
OperatorHandle & A,
Vector & X,
Vector & B)
{
FiniteElementSpace * pfes_trial = pmblfr->TrialFESpace();
FiniteElementSpace * pfes_test = pmblfr->TestFESpace();
const int vsize_trial = pfes_trial->GetVSize();
const int vsize_test = pfes_test->GetVSize();
// Allocate temporary Vector
Vector b_0;
b_0.UseDevice(true);
b_0.SetSize(vsize_test);
b_0 = 0.0;
// Extract the real and imaginary parts of the input Vectors
MFEM_ASSERT(x.Size() == 2 * vsize_trial,
"Input GridFunction of incorrect size!");
x.Read();
Vector x_r;
x_r.MakeRef(x, 0, vsize_trial);
Vector x_i;
x_i.MakeRef(x, vsize_trial, vsize_trial);
MFEM_ASSERT(b.Size() == 2 * vsize_test, "Input LinearForm of incorrect size!");
b.Read();
Vector b_r;
b_r.MakeRef(b, 0, vsize_test);
Vector b_i;
b_i.MakeRef(b, vsize_test, vsize_test);
if (conv == ComplexOperator::BLOCK_SYMMETRIC)
{
b_i *= -1.0;
}
const int tvsize_trial = pfes_trial->GetTrueVSize();
const int tvsize_test = pfes_test->GetTrueVSize();
OperatorHandle A_r, A_i;
X.UseDevice(true);
X.SetSize(2 * tvsize_trial);
X = 0.0;
B.UseDevice(true);
B.SetSize(2 * tvsize_test);
B = 0.0;
Vector X_r;
X_r.MakeRef(X, 0, tvsize_trial);
Vector X_i;
X_i.MakeRef(X, tvsize_trial, tvsize_trial);
Vector B_r;
B_r.MakeRef(B, 0, tvsize_test);
Vector B_i;
B_i.MakeRef(B, tvsize_test, tvsize_test);
Vector X_0, B_0;
if (RealInteg())
{
b_0 = b_r;
pmblfr->FormRectangularLinearSystem(
ess_trial_tdof_list, ess_test_tdof_list, x_r, b_0, A_r, X_0, B_0);
X_r = X_0;
B_r = B_0;
b_0 = b_i;
pmblfr->FormRectangularLinearSystem(
ess_trial_tdof_list, ess_test_tdof_list, x_i, b_0, A_r, X_0, B_0);
X_i = X_0;
B_i = B_0;
if (ImagInteg())
{
b_0 = 0.0;
pmblfi->FormRectangularLinearSystem(
ess_trial_tdof_list, ess_test_tdof_list, x_i, b_0, A_i, X_0, B_0);
B_r -= B_0;
b_0 = 0.0;
pmblfi->FormRectangularLinearSystem(
ess_trial_tdof_list, ess_test_tdof_list, x_r, b_0, A_i, X_0, B_0);
B_i += B_0;
}
}
else if (ImagInteg())
{
b_0 = b_i;
pmblfi->FormRectangularLinearSystem(
ess_trial_tdof_list, ess_test_tdof_list, x_r, b_0, A_i, X_0, B_0);
X_r = X_0;
B_i = B_0;
b_0 = b_r;
b_0 *= -1.0;
pmblfi->FormRectangularLinearSystem(
ess_trial_tdof_list, ess_test_tdof_list, x_i, b_0, A_i, X_0, B_0);
X_i = X_0;
B_r = B_0;
B_r *= -1.0;
}
else
{
MFEM_ABORT("Real and Imaginary part of the Mixed Sesquilinear form are empty");
}
if (conv == ComplexOperator::BLOCK_SYMMETRIC)
{
B_i *= -1.0;
b_i *= -1.0;
}
x_r.SyncAliasMemory(x);
x_i.SyncAliasMemory(x);
b_r.SyncAliasMemory(b);
b_i.SyncAliasMemory(b);
X_r.SyncAliasMemory(X);
X_i.SyncAliasMemory(X);
B_r.SyncAliasMemory(B);
B_i.SyncAliasMemory(B);
// A = A_r + i A_i
A.Clear();
if ((!A_r.Ptr() || A_r.Type() == Operator::Hypre_ParCSR) &&
(!A_i.Ptr() || A_i.Type() == Operator::Hypre_ParCSR))
{
ComplexHypreParMatrix * A_hyp =
new ComplexHypreParMatrix(A_r.As<HypreParMatrix>(),
A_i.As<HypreParMatrix>(),
A_r.OwnsOperator(),
A_i.OwnsOperator(),
conv);
A.Reset<ComplexHypreParMatrix>(A_hyp, true);
}
else
{
ComplexOperator * A_op = new ComplexOperator(A_r.As<Operator>(),
A_i.As<Operator>(),
A_r.OwnsOperator(),
A_i.OwnsOperator(),
conv);
A.Reset<ComplexOperator>(A_op, true);
}
A_r.SetOperatorOwner(false);
A_i.SetOperatorOwner(false);
}
void
ParMixedSesquilinearForm::FormRectangularSystemMatrix(const Array<int> &
ess_trial_tdof_list,
const Array<int> & ess_test_tdof_list,
OperatorHandle & A)
{
OperatorHandle A_r, A_i;
if (RealInteg())
{
pmblfr->FormRectangularSystemMatrix(ess_trial_tdof_list, ess_test_tdof_list,
A_r);
}
if (ImagInteg())
{
pmblfi->FormRectangularSystemMatrix(ess_trial_tdof_list, ess_test_tdof_list,
A_i);
}
if (!RealInteg() && !ImagInteg())
{
MFEM_ABORT("Both Real and Imaginary part of the Mixed Sesquilinear form are empty");
}
// A = A_r + i A_i
A.Clear();
if ((!A_r.Ptr() || A_r.Type() == Operator::Hypre_ParCSR) &&
(!A_i.Ptr() || A_i.Type() == Operator::Hypre_ParCSR))
{
ComplexHypreParMatrix * A_hyp =
new ComplexHypreParMatrix(A_r.As<HypreParMatrix>(),
A_i.As<HypreParMatrix>(),
A_r.OwnsOperator(),
A_i.OwnsOperator(),
conv);
A.Reset<ComplexHypreParMatrix>(A_hyp, true);
}
else
{
ComplexOperator * A_op = new ComplexOperator(A_r.As<Operator>(),
A_i.As<Operator>(),
A_r.OwnsOperator(),
A_i.OwnsOperator(),
conv);
A.Reset<ComplexOperator>(A_op, true);
}
A_r.SetOperatorOwner(false);
A_i.SetOperatorOwner(false);
}
void
ParMixedSesquilinearForm::Update()
{
pmblfr->Update();
pmblfi->Update();
}
#endif // MFEM_USE_MPI
}
-412
View File
@@ -166,75 +166,6 @@ public:
return sqrt(err_r * err_r + err_i * err_i);
}
/// @brief Returns Max|u_ex - u_h| error for complex-valued H1 or L2 elements
///
/// Compute the $L_\infty$ error across the entire domain.
///
/// @param[in] exsolr Coefficient object reproducing the real part of the
/// anticipated values of the scalar field, Re(u_ex).
/// @param[in] exsoli Coefficient object reproducing the imaginary part of
/// the anticipated values of the scalar field, Im(u_ex).
/// @param[in] irs Optional pointer to an array of custom integration
/// rules e.g. higher order than the default rules. If
/// present the array will be indexed by
/// Geometry::Type.
///
/// @note Uses ComputeLpError internally. See the ComputeLpError
/// documentation for generalizations of this error computation.
///
/// @note If an array of integration rules is provided through @a irs, be
/// sure to include valid rules for each element type that may occur
/// in the list of elements.
///
virtual real_t ComputeMaxError(Coefficient &exsolr,
Coefficient &exsoli,
const IntegrationRule *irs[] = NULL) const
{
return ComputeLpError(infinity(), exsolr, exsoli, NULL, irs);
}
/// @brief Returns ||u_ex - u_h||_Lp for complex-valued H1 or L2 elements
///
/// Computes:
/// $$(\sum_{elems} \int_{elem} w \, |u_{ex} - u_h|^p)^{1/p}$$
/// Where:
/// $$|u_{ex} - u_h| = \sqrt{Re(u_{ex} - u_h)^2 + Im(u_{ex} - u_h)^2}$$
///
/// @param[in] p Real value indicating the exponent of the $L^p$ norm.
/// To avoid domain errors p should have a positive value,
/// either finite or infinite.
/// @param[in] exsolr Coefficient object reproducing the real part of the
/// anticipated values of the scalar field, Re(u_ex).
/// @param[in] exsoli Coefficient object reproducing the imaginary part of
/// the anticipated values of the scalar field, Im(u_ex).
/// @param[in] weight Optional pointer to a Coefficient object reproducing
/// a weighting function, w.
/// @param[in] irs Optional pointer to an array of custom integration
/// rules e.g. higher order than the default rules. If
/// present the array will be indexed by Geometry::Type.
/// @param[in] elems Optional pointer to a marker array, with a length
/// equal to the number of local elements, indicating
/// which elements to integrate over. Only those elements
/// corresponding to non-zero entries in @a elems will
/// contribute to the computed L2 error.
///
/// @note If an array of integration rules is provided through @a irs, be
/// sure to include valid rules for each element type that may occur
/// in the list of elements.
///
/// @note Quadratures with negative weights (as in some simplex integration
/// rules in MFEM) can produce negative integrals even with
/// non-negative integrands. To avoid returning negative errors this
/// function uses the absolute values of the element-wise integrals.
/// This may lead to results which are not entirely consistent with
/// such integration rules.
virtual real_t ComputeLpError(const real_t p,
Coefficient &exsolr,
Coefficient &exsoli,
Coefficient *weight = NULL,
const IntegrationRule *irs[] = NULL,
const Array<int> *elems = NULL) const;
/// Save the ComplexGridFunction to an output stream.
virtual void Save(std::ostream &out) const;
@@ -505,186 +436,6 @@ public:
virtual ~SesquilinearForm();
};
/** Class for a mixed sesquilinear form
A mixed sesquilinear form is a generalization of a mixed bilinear form to
complex-valued fields. Mixed sesquilinear forms are linear in the second
argument but the first argument involves a complex conjugate in the sense
that:
a(alpha u, beta v) = conj(alpha) beta a(u, v)
The @a convention argument in the class's constructor is documented in the
mfem::ComplexOperator class found in linalg/complex_operator.hpp.
When supplying integrators to the MixedSesquilinearForm either the real or
imaginary integrator can be NULL. This indicates that the corresponding
portion of the complex-valued material coefficient is equal to zero.
*/
class MixedSesquilinearForm
{
private:
ComplexOperator::Convention conv;
MixedBilinearForm * mblfr;
MixedBilinearForm * mblfi;
/* These methods check if the real/imag parts of the sesqulinear form are not
empty */
bool RealInteg();
bool ImagInteg();
public:
MixedSesquilinearForm(
FiniteElementSpace * trial_fes,
FiniteElementSpace * test_fes,
ComplexOperator::Convention convention = ComplexOperator::HERMITIAN);
/** @brief Create a MixedSesquilinearForm on the given trial and test
FiniteElementSpaces, using the same integrators as the
MixedBilinearForms @a bfr and @a bfi.
The FiniteElementSpace pointers are not owned by the newly constructed
object.
The integrators are copied as pointers and they are not owned by the
newly constructed MixedSesquilinearForm. */
MixedSesquilinearForm(
FiniteElementSpace * trial_fes,
FiniteElementSpace * test_fes,
MixedBilinearForm * bfr,
MixedBilinearForm * bfi,
ComplexOperator::Convention convention = ComplexOperator::HERMITIAN);
ComplexOperator::Convention GetConvention() const { return conv; }
void SetConvention(const ComplexOperator::Convention & convention) { conv = convention; }
/// Set the desired assembly level.
/** Valid choices are:
- AssemblyLevel::LEGACY (default)
- AssemblyLevel::FULL
- AssemblyLevel::PARTIAL
- AssemblyLevel::ELEMENT
- AssemblyLevel::NONE
This method must be called before assembly. */
void SetAssemblyLevel(AssemblyLevel assembly_level)
{
mblfr->SetAssemblyLevel(assembly_level);
mblfi->SetAssemblyLevel(assembly_level);
}
MixedBilinearForm & real() { return *mblfr; }
MixedBilinearForm & imag() { return *mblfi; }
const MixedBilinearForm & real() const { return *mblfr; }
const MixedBilinearForm & imag() const { return *mblfi; }
/// Adds new Domain Integrator.
void AddDomainIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag);
/// Adds new Domain Integrator, restricted to specific attributes.
void AddDomainIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag,
Array<int> & elem_marker);
/// Adds new Boundary Integrator.
void AddBoundaryIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag);
/** @brief Adds new boundary Integrator, restricted to specific boundary
attributes.
Assumes ownership of @a bfi.
The mfem::array @a bdr_marker is stored internally as a pointer to the given
mfem::Array<int> object. */
void AddBoundaryIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag,
Array<int> & bdr_marker);
/// Adds new interior Face Integrator. Assumes ownership of @a bfi.
void AddInteriorFaceIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag);
/// Adds new boundary Face Integrator. Assumes ownership of @a bfi.
void AddBdrFaceIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag);
/** @brief Adds new boundary Face Integrator, restricted to specific boundary
attributes.
Assumes ownership of @a bfi.
The mfem::array @a bdr_marker is stored internally as a pointer to the given
mfem::Array<int> object. */
void AddBdrFaceIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag,
Array<int> & bdr_marker);
/** @brief Add a trace face integrator. Assumes ownership of @a bfi.
This type of integrator assembles terms over all faces of the mesh using
the face FE from the trial space and the two adjacent volume FEs from
the test space. */
void AddTraceFaceIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag);
/// Adds a boundary trace face integrator. Assumes ownership of @a bfi.
void AddBdrTraceFaceIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag);
/// Adds a boundary trace face integrator. Assumes ownership of @a bfi.
void AddBdrTraceFaceIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag,
Array<int> &bdr_marker);
/// Assemble the local matrix
void Assemble(int skip_zeros = 1);
/// Finalizes the matrix initialization.
void Finalize(int skip_zeros = 1);
/// Updates the internal mixed forms with the new finite element space.
virtual void Update();
/** @brief Return a ComplexSparseMatrix wrapping the local (L-dof) real
and imaginary matrices of the form.
The returned wrapper has to be deleted by the caller, but it does not
own the wrapped real and imaginary matrices, which remain owned by
this form. */
ComplexSparseMatrix *AssembleComplexSparseMatrix();
/// Return the trial FE space associated with the MixedSesquilinearForm.
FiniteElementSpace *TrialFESpace() { return mblfr->TrialFESpace(); }
/// Read-only access to the associated trial FiniteElementSpace.
const FiniteElementSpace *TrialFESpace() const { return mblfr->TrialFESpace(); }
/// Return the test FE space associated with the MixedSesquilinearForm.
FiniteElementSpace *TestFESpace() { return mblfr->TestFESpace(); }
/// Read-only access to the associated test FiniteElementSpace.
const FiniteElementSpace *TestFESpace() const { return mblfr->TestFESpace(); }
void FormRectangularLinearSystem(const Array<int> & ess_trial_tdof_list,
const Array<int> & ess_test_tdof_list,
Vector & x,
Vector & b,
OperatorHandle & A,
Vector & X,
Vector & B);
void FormRectangularSystemMatrix(const Array<int> & ess_trial_tdof_list,
const Array<int> & ess_test_tdof_list,
OperatorHandle & A);
virtual ~MixedSesquilinearForm();
};
#ifdef MFEM_USE_MPI
/// Class for parallel complex-valued grid function - real + imaginary part
@@ -1101,169 +852,6 @@ public:
virtual ~ParSesquilinearForm();
};
/** Class for a parallel mixed sesquilinear form
A mixed sesquilinear form is a generalization of a mixed bilinear form to
complex-valued fields. Mixed sesquilinear forms are linear in the second
argument but the first argument involves a complex conjugate in the sense
that:
a(alpha u, beta v) = conj(alpha) beta a(u, v)
The @a convention argument in the class's constructor is documented in the
mfem::ComplexOperator class found in linalg/complex_operator.hpp.
When supplying integrators to the ParMixedSesquilinearForm either the real
or imaginary integrator can be NULL. This indicates that the corresponding
portion of the complex-valued material coefficient is equal to zero.
*/
class ParMixedSesquilinearForm
{
private:
ComplexOperator::Convention conv;
ParMixedBilinearForm * pmblfr;
ParMixedBilinearForm * pmblfi;
/* These methods check if the real/imag parts of the sesqulinear form are
not empty */
bool RealInteg();
bool ImagInteg();
public:
ParMixedSesquilinearForm(
ParFiniteElementSpace * trial_fes,
ParFiniteElementSpace * test_fes,
ComplexOperator::Convention convention = ComplexOperator::HERMITIAN);
/** @brief Create a ParMixedSesquilinearForm on the given trial and test
ParFiniteElementSpaces, using the same integrators as the
ParMixedBilinearForms @a pbfr and @a pbfi.
The ParFiniteElementSpace pointers are not owned by the newly
constructed object.
The integrators are copied as pointers and they are not owned by the
newly constructed ParMixedSesquilinearForm. */
ParMixedSesquilinearForm(
ParFiniteElementSpace * trial_fes,
ParFiniteElementSpace * test_fes,
ParMixedBilinearForm * pbfr,
ParMixedBilinearForm * pbfi,
ComplexOperator::Convention convention = ComplexOperator::HERMITIAN);
ComplexOperator::Convention GetConvention() const { return conv; }
void SetConvention(const ComplexOperator::Convention & convention) { conv = convention; }
/// Set the desired assembly level.
/** Valid choices are:
- AssemblyLevel::LEGACY (default)
- AssemblyLevel::FULL
- AssemblyLevel::PARTIAL
- AssemblyLevel::ELEMENT
- AssemblyLevel::NONE
This method must be called before assembly. */
void SetAssemblyLevel(AssemblyLevel assembly_level)
{
pmblfr->SetAssemblyLevel(assembly_level);
pmblfi->SetAssemblyLevel(assembly_level);
}
ParMixedBilinearForm & real() { return *pmblfr; }
ParMixedBilinearForm & imag() { return *pmblfi; }
const ParMixedBilinearForm & real() const { return *pmblfr; }
const ParMixedBilinearForm & imag() const { return *pmblfi; }
/// Adds new Domain Integrator.
void AddDomainIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag);
/// Adds new Domain Integrator, restricted to specific attributes.
void AddDomainIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag,
Array<int> & elem_marker);
/// Adds new Boundary Integrator.
void AddBoundaryIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag);
/** @brief Adds new boundary Integrator, restricted to specific boundary
attributes.
Assumes ownership of @a bfi.
The mfem::array @a bdr_marker is stored internally as a pointer to the given
mfem::Array<int> object. */
void AddBoundaryIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag,
Array<int> & bdr_marker);
/// Adds new interior Face Integrator. Assumes ownership of @a bfi.
void AddInteriorFaceIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag);
/// Adds new boundary Face Integrator. Assumes ownership of @a bfi.
void AddBdrFaceIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag);
/** @brief Adds new boundary Face Integrator, restricted to specific boundary
attributes.
Assumes ownership of @a bfi.
The mfem::array @a bdr_marker is stored internally as a pointer to the given
mfem::Array<int> object. */
void AddBdrFaceIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag,
Array<int> & bdr_marker);
/** @brief Add a trace face integrator. Assumes ownership of @a bfi.
This type of integrator assembles terms over all faces of the mesh using
the face FE from the trial space and the two adjacent volume FEs from
the test space. */
void AddTraceFaceIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag);
/// Adds a boundary trace face integrator. Assumes ownership of @a bfi.
void AddBdrTraceFaceIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag);
/// Adds a boundary trace face integrator. Assumes ownership of @a bfi.
void AddBdrTraceFaceIntegrator(BilinearFormIntegrator * bfi_real,
BilinearFormIntegrator * bfi_imag,
Array<int> &bdr_marker);
/// Assemble the local matrix
void Assemble(int skip_zeros = 1);
/// Finalizes the matrix initialization.
void Finalize(int skip_zeros = 1);
/// Updates the internal mixed forms with the new finite element space.
virtual void Update();
/// Returns the matrix assembled on the true dofs, i.e. P^t A P.
/** The returned matrix has to be deleted by the caller. */
ComplexHypreParMatrix * ParallelAssemble();
void FormRectangularLinearSystem(const Array<int> & ess_trial_tdof_list,
const Array<int> & ess_test_tdof_list,
Vector & x,
Vector & b,
OperatorHandle & A,
Vector & X,
Vector & B);
void FormRectangularSystemMatrix(const Array<int> & ess_trial_tdof_list,
const Array<int> & ess_test_tdof_list,
OperatorHandle & A);
virtual ~ParMixedSesquilinearForm();
};
#endif // MFEM_USE_MPI
}
+2 -4
View File
@@ -809,7 +809,7 @@ ParaViewDataCollectionBase::ParaViewDataCollectionBase(
void ParaViewDataCollectionBase::SetLevelsOfDetail(int levels_of_detail_)
{
levels_of_detail = std::max(levels_of_detail_, 1);
levels_of_detail = levels_of_detail_;
}
void ParaViewDataCollectionBase::SetHighOrderOutput(bool high_order_output_)
@@ -1181,14 +1181,12 @@ void ParaViewDataCollection::SaveGFieldVTU(std::ostream &os, int ref_,
DenseMatrix vval, pmat;
std::vector<char> buf;
int vec_dim = it->second->VectorDim();
int map_type = it->second->FESpace()->GetTypicalFE()->GetMapType();
os << "<DataArray type=\"" << GetDataTypeString()
<< "\" Name=\"" << it->first
<< "\" NumberOfComponents=\"" << vec_dim << "\" "
<< VTKComponentLabels(vec_dim) << " "
<< "format=\"" << GetDataFormatString() << "\" >" << '\n';
if (vec_dim == 1 && (map_type == FiniteElement::VALUE ||
map_type == FiniteElement::INTEGRAL))
if (vec_dim == 1)
{
for (int i = 0; i < mesh->GetNE(); i++)
{
+403
View File
@@ -0,0 +1,403 @@
// 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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@@ -1,122 +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 "../../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;
};
}
}
@@ -1,180 +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 "../../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
@@ -1,242 +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 "../../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
@@ -1,260 +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 "../../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
@@ -1,244 +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 "../../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> {});
}
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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@@ -1,219 +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 "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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@@ -1,658 +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 "../../fieldoperator.hpp"
#include "kernels.hpp"
#include "util.hpp"
#include "../../integrator_ctx.hpp"
#include "../util.hpp"
#include <utility>
namespace mfem::future::LocalQFImpl
{
template <typename outputs_t, typename index_seq>
struct action_outputs_direct_impl;
template <typename outputs_t, std::size_t... Is>
struct action_outputs_direct_impl<outputs_t, std::index_sequence<Is...>>
{
static constexpr bool value =
((is_identity_fop_v<tuple_element_t<Is, outputs_t>> ||
is_functionalvalue_fop_v<tuple_element_t<Is, outputs_t>>) && ...);
};
template <typename outputs_t>
constexpr bool action_outputs_direct_v = action_outputs_direct_impl<outputs_t,
std::make_index_sequence<tuple_size<outputs_t>::value>>::value;
template <typename qfunc_t, typename inputs_t, typename outputs_t,
typename index_seq>
struct action_outputs_direct_value_impl;
template <typename qfunc_t, typename inputs_t, typename outputs_t,
std::size_t... Is>
struct action_outputs_direct_value_impl<qfunc_t, inputs_t, outputs_t,
std::index_sequence<Is...>>
{
static constexpr std::size_t n_inputs = tuple_size<inputs_t>::value;
static constexpr bool value =
((is_identity_fop_v<tuple_element_t<Is, outputs_t>> ||
is_functionalvalue_fop_v<tuple_element_t<Is, outputs_t>>) && ...)
&& ((!qf_param_uses_dual_v<
typename qf_param_slot<qfunc_t, n_inputs + Is>::qf_decay_param_t>)
&& ...);
};
template <typename qfunc_t, typename inputs_t, typename outputs_t>
constexpr bool action_outputs_direct_value_v =
action_outputs_direct_value_impl<qfunc_t, inputs_t, outputs_t,
std::make_index_sequence<tuple_size<outputs_t>::value>>::value;
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");
template<typename backend_t, std::size_t I, typename RArgs, typename InXEs>
static MFEM_HOST_DEVICE decltype(auto) direct_input_arg(
RArgs &rargs,
const InXEs &in_XE,
const int qx,
const int qy,
const int qz,
const int e)
{
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>)
{
return backend_t::template identity_qp_pull_dual<DT>(
false, XE, XE, qx, qy, qz, e);
}
else
{
return as_tensor<ARG>(&XE(0, qx, qy, qz, e));
}
}
else if constexpr (is_weight_fop_v<FOP>)
{
return XE(qx, qy, qz, 0, 0);
}
else if constexpr (is_value_fop_v<FOP> || is_gradient_fop_v<FOP>)
{
return backend_t::template qp_pull<ARG>(get<I>(rargs), qx, qy, qz);
}
else
{
static_assert(false, "Unsupported");
}
}
template<std::size_t I, typename OutYEs>
static MFEM_HOST_DEVICE decltype(auto) direct_output_arg(
const OutYEs &out_YE,
const int qx,
const int qy,
const int qz,
const int e)
{
constexpr size_t o = n_inputs + I;
const auto &YE = out_YE[I];
using DT = typename qf_param_slot<qfunc_t, o>::qf_decay_param_t;
using ARG = typename qf_param_slot<qfunc_t, o>::qf_reg_param_t;
if constexpr (std::is_same_v<DT, real_t>)
{
return YE(0, qx, qy, qz, e);
}
else
{
return as_tensor<ARG>(&YE(0, qx, qy, qz, e));
}
}
template<typename backend_t, typename RArgs, typename InXEs, typename OutYEs,
std::size_t... InIs, std::size_t... OutIs>
static MFEM_HOST_DEVICE void call_qfunc_direct(
const qfunc_t &qfunc,
RArgs &rargs,
const InXEs &in_XE,
const OutYEs &out_YE,
const int qx,
const int qy,
const int qz,
const int e,
std::index_sequence<InIs...>,
std::index_sequence<OutIs...>)
{
qfunc(direct_input_arg<backend_t, InIs>(rargs, in_XE, qx, qy, qz, e)...,
direct_output_arg<OutIs>(out_YE, qx, qy, qz, e)...);
}
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
// -----------------------------------------------
action_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)
{
if constexpr (action_outputs_direct_value_v<qfunc_t, inputs_t,
outputs_t>)
{
call_qfunc_direct<backend_t>(
qfunc, rargs, in_XE, out_YE, qx, qy, qz, e,
std::make_index_sequence<n_inputs> {},
std::make_index_sequence<n_outputs> {});
}
else
{
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");
}
});
}
}
}
}
if constexpr (!action_outputs_direct_v<outputs_t>)
{
MFEM_SYNC_THREAD;
}
// -----------------------------------------------
// Integrate outputs
// -----------------------------------------------
if constexpr (!action_outputs_direct_v<outputs_t>)
{
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>;
if constexpr (DIM == 3 && Q1D == LocalQFLOBackendMQ1() &&
action_outputs_direct_value_v<qfunc_t, inputs_t, outputs_t>)
{
return action_t::template action_callback<LocalQFLOBackend<DIM, Q1D, Q1D / 2>>;
}
else
{
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
@@ -1,926 +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 "../../integrator_ctx.hpp"
#include "kernels.hpp"
#include "util.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");
/// Which inputs carry a tangent, i.e. are attached to the field being
/// differentiated against. This is a property of `inputs_t` and
/// `derivative_id` alone, so it is available at compile time: it decides the
/// Enzyme activity of every q-function parameter, which loads the tangent
/// pass has to do, and how large the shadow register bank has to be. The
/// runtime `input_is_dependent` below holds the same values and is kept for
/// the host-side sizing checks.
static constexpr auto input_activity =
mfem::future::detail::make_activity_map <
static_cast<std::size_t>(derivative_id) > (inputs_t {});
static_assert(input_activity.size() == n_inputs);
/// Shadow register bank: only the active input slots are materialized.
template <typename backend_t, int MQ1, std::size_t... Is>
static auto shadow_bank_type(std::index_sequence<Is...>)
#ifdef MFEM_USE_ENZYME
-> masked_input_args_reg_t<backend_t, qfunc_t, MQ1, input_activity[Is]...>;
#else
// The dual-number path pulls through every input slot unconditionally.
-> input_args_reg_t<backend_t, qfunc_t, inputs_t, outputs_t, MQ1>;
#endif
template <typename backend_t, int MQ1>
using shadow_bank_t = decltype(shadow_bank_type<backend_t, MQ1>(
std::make_index_sequence<n_inputs> {}));
/// Per-quadrature-point shadow argument tuple. Only the active inputs and
/// the outputs are materialized where supported; the rest are `enzyme_const`
/// and their shadow slots are never addressed. This is the innermost live
/// state of the kernel, and on device it shares a per-thread register budget
/// capped by the launch bounds, so the dead slots are worth removing
/// explicitly rather than hoping the optimizer splits the tuple.
#ifdef _MSC_VER
using shadow_args_t = args_tuple_t;
#else
template <std::size_t... Is>
static auto shadow_tuple_type(std::index_sequence<Is...>)
-> masked_args_tuple_t < args_tuple_t,
(Is<n_inputs ? input_activity[Is] : true)... >;
using shadow_args_t = decltype(shadow_tuple_type(
std::make_index_sequence<n_inputs + n_outputs> {}));
#endif
#ifdef MFEM_USE_ENZYME
/// Forward-mode call with the activity of every q-function parameter fixed
/// at compile time. Outputs are always active; inputs follow
/// `input_activity`, so an inactive input (the mesh nodes and the quadrature
/// weight, for a derivative w.r.t. the trial field) is marked `enzyme_const`
/// rather than dup'd with a zero tangent. Without this Enzyme differentiates
/// everything those inputs feed - for a diffusion q-function the whole
/// inv(J) / det(J) chain - to produce a tangent that is structurally zero.
// `qf_t` is deduced because the kernel captures the q-function by value into
// a const lambda, so it arrives here as `const qfunc_t`.
template <typename qf_t, std::size_t... Is>
MFEM_FUTURE_ALWAYS_INLINE
MFEM_HOST_DEVICE static void call_fwddiff(qf_t &qfunc,
args_tuple_t &primal_args,
shadow_args_t &shadow_args,
std::index_sequence<Is...>)
{
mfem::future::call_enzyme_fwddiff_active <
(Is < n_inputs ? input_activity[Is] : true)... > (
qfunc, primal_args, shadow_args);
}
#endif
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, int T_Q1D>
struct DerivativeActionKernelData
{
qfunc_t qfunc;
std::array<DeviceTensor<3 + 1 + 1, const real_t>, n_inputs> in_XE;
std::array<DeviceTensor<3 + 1 + 1, const real_t>, n_inputs> in_XE_dir;
std::array<DeviceTensor<3 + 1 + 1, real_t>, n_outputs> out_YE;
std::array<const real_t *, n_inputs> in_B;
std::array<const real_t *, n_inputs> in_G;
std::array<int, n_inputs> in_d1d;
std::array<int, n_inputs> in_q1d;
std::array<const real_t *, n_outputs> out_B;
std::array<const real_t *, n_outputs> out_G;
std::array<int, n_outputs> out_d1d;
std::array<int, n_outputs> out_q1d;
std::array<bool, n_inputs> input_dep;
const int *d_attr;
bool has_attr;
const int *d_elem_attr;
int q1d;
};
template<typename backend_t, int T_Q1D>
MFEM_FUTURE_ALWAYS_INLINE MFEM_HOST_DEVICE static void
derivative_action_kernel_body(
const DerivativeActionKernelData<backend_t, T_Q1D> &data, const int e)
{
static constexpr auto B2D = backend_t::DIM == 2;
static constexpr auto MQ1 = T_Q1D ? T_Q1D : backend_t::MQ1;
auto &qfunc = data.qfunc;
const auto &in_XE = data.in_XE;
const auto &in_XE_dir = data.in_XE_dir;
const auto &out_YE = data.out_YE;
const auto &in_B = data.in_B;
const auto &in_G = data.in_G;
const auto &in_d1d = data.in_d1d;
const auto &in_q1d = data.in_q1d;
const auto &out_B = data.out_B;
const auto &out_G = data.out_G;
const auto &out_d1d = data.out_d1d;
const auto &out_q1d = data.out_q1d;
const auto &input_dep = data.input_dep;
MFEM_CONTRACT_VAR(input_dep);
const auto d_attr = data.d_attr;
const bool has_attr = data.has_attr;
const auto d_elem_attr = data.d_elem_attr;
const int q1d = data.q1d;
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;
shadow_bank_t<backend_t, MQ1> sargs; // shadow, active inputs only
// -----------------------------------------------
// 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;
using FOP = tuple_element_t<i, inputs_t>;
if constexpr (input_activity[i] &&
(is_value_fop_v<FOP> || is_gradient_fop_v<FOP>))
{
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
if constexpr (is_value_fop_v<FOP>)
{
backend_t::LoadValue(smem, e, d, q, Q1D, B, XE, sarg);
}
else
{
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
{
// Inactive input, or an input read straight from quadrature
// point data (weight / identity): nothing to interpolate.
static_assert(!input_activity[i] || is_weight_fop_v<FOP> ||
is_identity_fop_v<FOP>, "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_t 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;
MFEM_CONTRACT_VAR(targ);
MFEM_CONTRACT_VAR(XEd);
if constexpr (is_identity_fop_v<FOP>)
{
parg = as_tensor<ARG>(&XE(0, qx, qy, qz, e));
if constexpr (input_activity[i])
{
targ = as_tensor<ARG>(&XEd(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);
if constexpr (input_activity[i])
{
targ = backend_t::template qp_pull<ARG>(
get<i>(sargs), qx, qy, qz);
}
}
else
{
static_assert(false, "Unsupported");
}
});
// --------------------------------------
// Call the quadrature function. Inactive inputs are
// enzyme_const, so their shadow slots are never read and are
// deliberately left unset above.
// --------------------------------------
call_fwddiff(qfunc, primal_args, shadow_args,
std::make_index_sequence<n_inputs + n_outputs> {});
// --------------------------------------
// 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");
}
});
}
template<typename backend_t, int T_Q1D>
struct DerivativeActionKernelBody
{
MFEM_FUTURE_ALWAYS_INLINE MFEM_HOST_DEVICE static void run(
const DerivativeActionKernelData<backend_t, T_Q1D> &data, const int e)
{
derivative_action_kernel_body<backend_t, T_Q1D>(data, e);
}
};
//////////////////////////////////////////////////////////////////
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");
// Dependency is resolved at compile time through `input_activity`; the
// runtime array is only carried for the non-Enzyme dual-number path.
MFEM_CONTRACT_VAR(input_dep);
if (ctx.attr.Size() == 0) { return; }
static constexpr auto B2D = backend_t::DIM == 2;
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 constexpr (input_activity[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 constexpr (input_activity[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();
DerivativeActionKernelData<backend_t, T_Q1D> data
{
qfunc,
in_XE,
in_XE_dir,
out_YE,
in_B,
in_G,
in_d1d,
in_q1d,
out_B,
out_G,
out_d1d,
out_q1d,
input_dep,
d_attr,
has_attr,
d_elem_attr,
q1d
};
const auto blocks = backend_t::thread_blocks(
compute_kernel_thread_1d<inputs_t, outputs_t>(q1d, in_d1d, out_d1d));
if (Device::Allows(Backend::CUDA_MASK) ||
Device::Allows(Backend::HIP_MASK))
{
dfem::forall_data<backend_t::MAX_THREADS_PER_BLOCK(),
DerivativeActionKernelBody<backend_t, T_Q1D>>(
data, ne, blocks);
}
else if (Device::Allows(Backend::CPU_MASK))
{
for (int e = 0; e < ne; e++)
{
derivative_action_kernel_body<backend_t, T_Q1D>(data, e);
}
}
else
{
MFEM_ABORT("no compute backend available");
}
}
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
@@ -1,738 +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 "../../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
@@ -1,637 +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 "../../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
@@ -1,987 +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 "../../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<5, 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 row_offset,
const int test_vdim,
const int test_op_dim,
const int q1d,
const int num_trial_dof_1d,
real_t *fhat_storage,
Shared &smem)
{
static constexpr int MQN = (DIM == 2) ? MQ1 * MQ1 : MQ1 * MQ1 * MQ1;
// Slab must hold full (test_vdim, test_op_dim, nq) fhat.
// It is allocated by the caller, and is shared by every output, so it must be
// Before, declaring it here allocated one slab per output and the device
// kernel ran out of shared memory once an integrator had more outputs.
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, output_size_on_qp, ne),
// where output_size_on_qp spans every output FieldOperator (multi-output mode).
// The rows of one output start at @a row_offset and are laid out as
// i * test_op_dim + k, matching how DerivativeSetup writes the cache.
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
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, row_offset + tv * test_op_dim + k, 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, row_offset + tv * test_op_dim + k, 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, row_offset + i * test_op_dim + k, 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, row_offset + i * test_op_dim + k, 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;
/// Per-output row geometry of the quadrature point cache. DerivativeSetup
/// lays that cache out over every output FieldOperator, so reading it needs
/// all of them.
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 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;
}()),
// All outputs are attached to the same test field, so vdim is common to
// them; only the operator dimension differs, and that lives in out_op_dim.
test_vdim(get<0>(outputs).vdim),
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;
}()),
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
{
// Every output is contracted into one element matrix Ae, sized from the
// test space of get<0>(outputs), and filled through a single test
// ElementRestriction.
//
// WIP:
// This takes care of single-field, multiple-outputs case.
// For a multiple fields case, outputs on a second field would need a second
// matrix -- the derivative then eould be a block column with one row block per
// test space.
//
// For now we just add a check that all outputs are attached to the same test field, and abort if not.
for_constexpr<n_outputs>([&](auto o)
{
MFEM_VERIFY(get<o>(outputs).GetFieldId() == get<0>(outputs).GetFieldId(),
"DerivativeAssemble: every output FieldOperator has to be "
"attached to the same test field; assembling outputs that "
"span several fields is not supported");
});
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,
out_vdim,
out_op_dim,
out_offsets,
output_size_on_qp,
inputs_trial_op_dim,
test_vdim,
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 std::array<DofToQuadMap, n_outputs> &output_dtq_maps,
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 Vector &inputs_trial_op_dim,
const int test_vdim,
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");
for_constexpr<n_outputs>([&](auto o)
{
MFEM_VERIFY(out_op_dim[o] <= 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,
output_size_on_qp,
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;
static constexpr int MQN = (DIM == 2) ? MQ1 * MQ1 : MQ1 * MQ1 * MQ1;
static constexpr int fhat_slab_size = MQN * 4;
MFEM_SHARED typename backend_t::Shared s;
// One slab shared by every output. Declaring it inside the templated
// per-output kernel allocates one per output instead, and static
// shared memory is summed across instantiations on device.
MFEM_SHARED real_t fhat_storage[fhat_slab_size];
// Each output contributes its own rows of the cache, contracted
// against its own test basis operation; map_quadrature_data_to_fields
// accumulates, so the element matrix is the sum over outputs for the
// same field.
for_constexpr<n_outputs>([&](auto o)
{
using output_fop_t = std::decay_t<decltype(get<o>(outputs))>;
if constexpr (!is_identity_fop_v<output_fop_t>)
{
// The outputs share fhat_storage, so one has to be done with it
// before the next zeroes it.
MFEM_SYNC_THREAD;
detail::assemble_element_mat_sumfact<DIM, MQ1>(Ae,
qpdc,
e,
itod,
inputs,
get<o>(outputs),
input_dtq_maps,
output_dtq_maps[o],
out_offsets[o],
out_vdim[o],
out_op_dim[o],
q1d,
num_trial_dof_1d,
fhat_storage,
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
@@ -1,540 +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 "../../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
@@ -1,600 +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 "../../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
@@ -1,277 +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"
#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()
{
return 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>
MFEM_FUTURE_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
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@@ -1,83 +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.
// 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
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@@ -1,77 +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 "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
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@@ -1,803 +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 "../../../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
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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 "../../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{});
}
}
@@ -1,606 +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 "util.hpp"
#include "../../util.hpp"
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);
};
/// Scalar-level view of a per-point argument: the plain value type it stores
/// and the dual type used to carry a first-order tangent alongside it.
template <typename T>
struct qp_scalar_traits
{
using view_type = T;
using dual_type = dual<T, T>;
};
template <typename V, typename G>
struct qp_scalar_traits<dual<V, G>>
{
using view_type = V;
using dual_type = dual<V, G>;
};
// Component count and writable counterpart of a per-point argument, which
// is either a tensor or a plain scalar. `view_type` keeps the argument's own
// scalar type; `dual_type` is the same shape with a dual scalar, used for the
// gradient blocks of the native dual-number backend.
template <typename Arg> struct qp_traits
{
static_assert(std::is_arithmetic_v<Arg> || is_dual_number<Arg>::value,
"per-point arguments must be tensors or scalars");
using scalar_type = std::remove_const_t<Arg>;
using view_type = scalar_type;
using dual_type = typename qp_scalar_traits<scalar_type>::dual_type;
static constexpr int components = 1;
};
template <typename T, int... Sizes> struct qp_traits<tensor<T, Sizes...>>
{
using scalar_type = std::remove_const_t<T>;
using view_type = tensor<scalar_type, Sizes...>;
using dual_type =
tensor<typename qp_scalar_traits<scalar_type>::dual_type, Sizes...>;
static constexpr int components = (Sizes * ... * 1);
};
template <typename... T1s, typename... T2s>
constexpr tuple<T1s..., T2s...> concat_tuples(tuple<T1s...>, tuple<T2s...>);
///////////////////////////////////////////////////////////////////////////////
/// Nested ("hyper") dual utilities, used for second derivatives on the native
/// dual-number backend.
///
/// A second derivative taken with plain duals would have to reuse the single
/// gradient slot that already carries the incoming direction. Lifting the
/// scalar to `dual<dual<V,G>, dual<V,G>>` adds a second, independent slot:
///
/// dual(a, b) -> ((a, c), (b, d))
///
/// `a`/`b` stay the incoming primal/direction, `c` is seeded per component and
/// `d` returns the second-order result.
template <typename T>
struct make_nested_qp_type
{
using type = T;
};
template <typename V, typename G>
struct make_nested_qp_type<dual<V, G>>
{
using type = dual<dual<V, G>, dual<V, G>>;
};
template <typename S, int... Sizes>
struct make_nested_qp_type<tensor<S, Sizes...>>
{
using type = tensor<typename make_nested_qp_type<S>::type, Sizes...>;
};
template <typename T>
using make_nested_qp_type_t = typename make_nested_qp_type<T>::type;
using native_dual_t = typename qp_scalar_traits<real_t>::dual_type;
using nested_native_dual_t = make_nested_qp_type_t<native_dual_t>;
/// Rebinds a q-function's scalar template parameter so its arguments are
/// nested duals. Only the leading scalar parameter is rebound; any remaining
/// non-type parameters (e.g. `dim`) are carried through unchanged. This
/// requires q-functions of the form `QFunc<scalar_t>` or `QFunc<scalar_t,
/// Params...>`; `supported` reports whether that shape was matched, so callers
/// can fail with a readable static_assert.
template <typename qfunc_t, typename nested_scalar_t, typename = void>
struct rebind_qfunc_scalar
{
static constexpr bool supported = false;
};
template <template <typename> class qfunc_template_t,
typename old_scalar_t,
typename nested_scalar_t>
struct rebind_qfunc_scalar<qfunc_template_t<old_scalar_t>, nested_scalar_t>
{
static constexpr bool supported = true;
using type = qfunc_template_t<nested_scalar_t>;
};
template <template <typename, auto...> class qfunc_template_t,
typename old_scalar_t,
auto... Params,
typename nested_scalar_t>
struct rebind_qfunc_scalar<qfunc_template_t<old_scalar_t, Params...>,
nested_scalar_t,
std::enable_if_t<(sizeof...(Params) > 0)>>
{
static constexpr bool supported = true;
using type = qfunc_template_t<nested_scalar_t, Params...>;
};
template <typename qfunc_t, typename nested_scalar_t>
using rebind_qfunc_scalar_t =
typename rebind_qfunc_scalar<qfunc_t, nested_scalar_t>::type;
/// Copies a q-function argument into its nested-dual counterpart, mapping
/// dual(a, b) -> ((a, 0), (b, 0)). The inner gradients stay zero; the caller
/// seeds one of them per component.
template <typename Dst, typename Src>
MFEM_HOST_DEVICE void lift_to_nested_arg(const Src &src, Dst &dst)
{
using dst_t = std::decay_t<Dst>;
constexpr bool dst_uses_dual = is_dual_number<dst_t>::value ||
qf_param_uses_dual_v<dst_t> ||
is_nested_dual_number<dst_t>::value ||
qf_param_uses_nested_dual_v<dst_t>;
if constexpr (dst_uses_dual)
{
constexpr int ncomp = qp_traits<dst_t>::components;
for (int component = 0; component < ncomp; component++)
{
qf_set_flat_value(dst, component, qf_flat_value(src, component));
qf_set_flat_gradient(dst, component, qf_flat_gradient(src, component));
}
}
else
{
// Destination carries no derivative slots: a plain copy is the lift.
dst = src;
}
}
// 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 and allocation-free.
//
// Without Enzyme the same interface is served by a forward-mode dual-number
// fallback (`call_dual_rev`), which seeds one component at a time. `mode`
// selects what that fallback is being asked for: `Eval` is the plain gradient,
// `Derivative` is a gradient taken inside an outer derivative, which lifts the
// q-function to nested duals so seeding does not clobber the outer direction.
// With Enzyme both modes use the single reverse-mode call and `mode` is inert.
enum class RevDiffDualMode
{
Eval,
Derivative
};
// 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 <typename activity_t, size_t num_inputs, size_t... Is>
constexpr size_t count_active_inputs(std::index_sequence<Is...>)
{
return ((Is < num_inputs && qf_param_is_active_v<activity_t, Is>
? size_t{1} : size_t{0}) + ...);
}
template <typename activity_t, size_t num_inputs, size_t num_active,
size_t... Is>
constexpr std::array<size_t, num_active>
collect_active_inputs(std::index_sequence<Is...>)
{
std::array<size_t, num_active> idx{};
size_t j = 0;
(((Is < num_inputs && qf_param_is_active_v<activity_t, Is>)
? (idx[j++] = Is) : size_t{0}), ...);
return idx;
}
template <typename Func, typename InputActivityTuple,
typename OutputActivityTuple,
RevDiffDualMode mode = RevDiffDualMode::Eval>
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");
static constexpr size_t num_active_inputs =
count_active_inputs<activity, num_inputs>(
std::make_index_sequence<arity> {});
static constexpr auto active_inputs =
collect_active_inputs<activity, num_inputs, num_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()
{
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_qparam<activity, num_inputs, 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>;
// True when reverse mode is served by the dual-number fallback rather than
// Enzyme. Everything below that widens a type to a dual is gated on this, so
// an Enzyme build sees exactly the types it saw before nested duals existed.
#ifdef MFEM_USE_ENZYME
static constexpr bool native_dual_backend = false;
#else
static constexpr bool native_dual_backend = true;
#endif
static constexpr bool use_native_dual_derivative =
native_dual_backend && (mode == RevDiffDualMode::Derivative);
// Under the native-dual second-derivative path the active primals arrive
// carrying the outer direction, so they must be dual-typed.
template <size_t I>
using derivative_arg_t =
std::conditional_t<use_native_dual_derivative &&
qf_param_is_active_v<activity, I>,
typename qp_traits<std::decay_t<tuple_element_t<I, args_tuple>>>::dual_type,
primal_arg_t<I>>;
template <size_t S>
using active_arg_decay_t =
std::decay_t<tuple_element_t<active_inputs[S], args_tuple>>;
template <size_t S>
static constexpr bool active_arg_uses_dual()
{
return native_dual_backend &&
(is_dual_number<active_arg_decay_t<S>>::value ||
qf_param_uses_dual_v<active_arg_decay_t<S>>);
}
// A gradient block mirrors its active input's shape. It needs a dual scalar
// whenever the fallback has to return a value and a tangent through it.
template <size_t S>
using grad_arg_t =
std::conditional_t<use_native_dual_derivative || active_arg_uses_dual<S>(),
typename qp_traits<active_arg_decay_t<S>>::dual_type,
typename qp_traits<active_arg_decay_t<S>>::view_type>
&;
template <typename qfunc_type>
using qfunc_args_tuple_t =
decay_tuple<typename function_traits<decltype(&qfunc_type::operator())>::args_tuple>;
template <size_t... Is, size_t... Ss>
static FunctionSignature<void(derivative_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> {}));
Func func {};
RevDiff() = default;
MFEM_HOST_DEVICE explicit RevDiff(const Func &func_) : func(func_) { }
// Plain function with the qfunction's exact (reference) signature, plus the
// configured qfunction instance, so it can be handed to Enzyme as a function
// pointer without default-constructing away runtime qfunction state.
template <size_t... Is>
MFEM_HOST_DEVICE static MFEM_FUTURE_ALWAYS_INLINE void
static_call(Func *func, 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()
{
return fn_ptr(std::make_index_sequence<arity> {});
}
// Load primal inputs from the pointer tuple into a local qargs copy. Dual
// gradient parts are implicitly zero because qargs is value-initialized.
template <typename QArgs, typename AllPtrs, size_t... Is>
MFEM_HOST_DEVICE static MFEM_FUTURE_ALWAYS_INLINE void load_qargs(
QArgs &qargs, AllPtrs &ptrs, std::index_sequence<Is...>)
{
((mfem::future::get<int(Is)>(qargs) =
*mfem::future::get<int(Is)>(ptrs)), ...);
}
template <typename QArgs, typename AllPtrs, size_t... Is>
MFEM_HOST_DEVICE static MFEM_FUTURE_ALWAYS_INLINE void
lift_qargs_to_nested_dual(QArgs &qargs, AllPtrs &ptrs,
std::index_sequence<Is...>)
{
(lift_to_nested_arg(*mfem::future::get<int(Is)>(ptrs),
mfem::future::get<Is>(qargs)), ...);
}
// The nested-dual q-function is a *different* type — its scalar template
// parameter is rebound — so a configured instance cannot simply be copied
// over. Runtime q-function state must still survive, or the second
// derivative would silently be taken of a differently-parameterised energy.
//
// Three cases, in order:
// * the rebound type converts from this one: use that conversion;
// * no state at all: nothing to carry;
// * same size and trivially copyable: none of the members depend on the
// rebound scalar, so the two are layout-identical and the state copies
// over bytewise. A member that *did* depend on the scalar would change
// the size and land in the static_assert below instead.
template <typename nested_func_t>
MFEM_HOST_DEVICE MFEM_FUTURE_ALWAYS_INLINE nested_func_t
make_nested_func() const
{
if constexpr (std::is_constructible_v<nested_func_t, const Func &>)
{
return nested_func_t(func);
}
else if constexpr (std::is_empty_v<Func>)
{
return nested_func_t {};
}
else
{
static_assert(std::is_trivially_copyable_v<Func> &&
std::is_trivially_copyable_v<nested_func_t> &&
sizeof(Func) == sizeof(nested_func_t),
"second derivatives on the native dual backend rebind "
"the q-function's scalar type; a q-function whose state "
"depends on that scalar must be constructible from its "
"rebound form");
nested_func_t nested {};
const auto *src = reinterpret_cast<const unsigned char *>(&func);
auto *dst = reinterpret_cast<unsigned char *>(&nested);
for (size_t b = 0; b < sizeof(Func); b++) { dst[b] = src[b]; }
return nested;
}
}
// Seed the s-th Active input one component at a time and read the resulting
// gradient block back out. This is the forward-mode dual-number stand-in for
// one reverse-mode call: O(ncomp) evaluations instead of O(1).
template <size_t S, typename AllPtrs>
MFEM_HOST_DEVICE MFEM_FUTURE_ALWAYS_INLINE void seed_active_input(
AllPtrs &ptrs) const
{
constexpr size_t input_idx = active_inputs[S];
using active_arg_t = std::decay_t<tuple_element_t<input_idx, args_tuple>>;
constexpr int ncomp = qp_traits<active_arg_t>::components;
for (int component = 0; component < ncomp; component++)
{
if constexpr (mode == RevDiffDualMode::Eval)
{
// Fresh value-initialized qargs: primals loaded below, all dual
// gradient parts start at zero, so no explicit clear is needed.
qfunc_args_tuple_t<Func> qargs {};
load_qargs(qargs, ptrs, std::make_index_sequence<num_inputs> {});
auto &grad = *mfem::future::get<num_inputs + S>(ptrs);
qf_set_flat_gradient(mfem::future::get<input_idx>(qargs), component,
1.0);
call_qfunc_no_move(func, qargs);
auto &out = mfem::future::get<active_output>(qargs);
qf_set_flat_value(grad, component, qf_flat_gradient(out, 0));
}
else
{
// Lift the incoming dual (a, b) to ((a, c), (b, d)): b is the outer
// Hessian-action direction, c is this loop's component seed. After
// evaluating E the nested output holds ((E, dE/dx_i), (E'[b],
// H_i[b])), and we hand dfem back (dE/dx_i, H_i[b]).
static_assert(rebind_qfunc_scalar<Func, nested_native_dual_t>::supported,
"RevDiff native-dual derivative mode requires "
"q-function types of the form QFunc<scalar_t> so they "
"can be rebound to nested dual scalars");
using nested_func_t = rebind_qfunc_scalar_t<Func, nested_native_dual_t>;
qfunc_args_tuple_t<nested_func_t> nested_qargs {};
lift_qargs_to_nested_dual(nested_qargs, ptrs,
std::make_index_sequence<num_inputs> {});
qf_set_flat_value_gradient(
mfem::future::get<input_idx>(nested_qargs), component, 1.0);
call_qfunc_no_move(make_nested_func<nested_func_t>(), nested_qargs);
auto &out = mfem::future::get<active_output>(nested_qargs);
auto &grad = *mfem::future::get<num_inputs + S>(ptrs);
qf_set_flat_value(grad, component, qf_flat_value_gradient(out, 0));
qf_set_flat_gradient(grad, component,
qf_flat_gradient_gradient(out, 0));
}
}
}
// Dual-number fallback for the whole reverse-mode call: one seeded sweep per
// Active input.
template <typename AllPtrs>
MFEM_HOST_DEVICE MFEM_FUTURE_ALWAYS_INLINE void call_dual_rev(
AllPtrs &ptrs) const
{
for_constexpr<num_active_inputs>([&](auto s)
{
seed_active_input<decltype(s)::value>(ptrs);
});
}
#ifdef MFEM_USE_ENZYME
// Recursive builder of the per-argument reverse-mode enzyme call.
template <size_t I = 0, typename AllPtrs, typename... Built>
MFEM_HOST_DEVICE MFEM_FUTURE_ALWAYS_INLINE void
call_enzyme_rev(AllPtrs &ptrs, output_view &scratch, output_view &adjoint,
Built... built) const
{
if constexpr (I == arity)
{
__enzyme_autodiff<void>(fn(), enzyme_const, const_cast<Func *>(&func),
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 (qf_param_is_active_v<activity, 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));
}
}
#endif // MFEM_USE_ENZYME
// Zero all gradient outputs before the enzyme call (Enzyme accumulates).
template <typename AllPtrs, size_t... Ss>
MFEM_HOST_DEVICE static
MFEM_FUTURE_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 MFEM_FUTURE_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> {});
#ifdef MFEM_USE_ENZYME
output_view out_scratch {};
output_view out_adjoint{1.0}; // seed: d(output)/d(output) = 1
call_enzyme_rev(ptrs, out_scratch, out_adjoint);
#else
call_dual_rev(ptrs);
#endif
}
static MFEM_FUTURE_ALWAYS_INLINE void print() { print_impl(std::make_index_sequence<arity> {}); }
template <size_t... Is> static MFEM_FUTURE_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 (qf_param_is_active_v<activity, Is>)
mfem::out << ", enzyme_dup, " << name << ", grad out";
else
{
mfem::out << ", enzyme_const, " << name;
}
}()),
...);
mfem::out << ")\n";
}
};
template <typename Func, typename InputActivityTuple,
typename OutputActivityTuple, RevDiffDualMode mode>
struct create_function_signature<RevDiff<Func, InputActivityTuple,
OutputActivityTuple, mode>>
{
using type = typename
RevDiff<Func, InputActivityTuple, OutputActivityTuple, mode>::signature;
};
/// Builds the reverse-mode transform of @a f, differentiating the inputs marked
/// Active in @a activity_t.
///
/// A factory rather than a plain declaration of a RevDiff variable for compatibility with MSVC.
template <typename activity_t, RevDiffDualMode mode = RevDiffDualMode::Eval,
typename func_t>
auto make_revdiff(const func_t &f)
{
return RevDiff<func_t, activity_t, tuple<Active>, mode>(f);
}
} // 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 "../../../general/error.hpp"
#include "../../../linalg/vector.hpp"
#include "../tuple.hpp"
#include <initializer_list>
#include <memory>
#include <type_traits>
#include <utility>
#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.
//
// @a scalar_t is the scalar the owning q-function uses at a quadrature point.
// With Enzyme this is real_t and the tangent lives in a separate shadow bank.
// Without Enzyme the q-function is evaluated on native duals, which carry the
// tangent inside the value itself; the bank then widens its backing storage
// accordingly so that a scratch entry can round-trip a dual without dropping
// the gradient. Backing storage stays a real_t Vector in both cases, so the
// device and shadow plumbing is unchanged.
template <typename scalar_t, typename... GlobalScratchTypes>
struct ScratchBank
{
static_assert(sizeof(scalar_t) % sizeof(real_t) == 0,
"scratch scalar must be a whole number of real_t");
/// Number of real_t needed to back one scalar_t scratch entry.
static constexpr int scalar_size = sizeof(scalar_t) / sizeof(real_t);
//=================================
///<--- 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 * scalar_size;
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
//===========================
/// Scratch buffer @a i viewed as the q-function's scalar type.
scalar_t *GetScratchPointer(const int i) const
{
return reinterpret_cast<scalar_t *>(ptrs[i]);
}
scalar_t *operator[](const int i) const { return GetScratchPointer(i); }
/// Raw real_t backing storage of scratch buffer @a i. Its size is
/// scalar_size times the number of scalar_t entries.
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. Under Enzyme a matching
// scratch shadow is created for forward differentiation; with native duals the
// tangent rides along in the scratch entry and no shadow is created.
template <typename scalar_t, typename... GlobalScratchTypes>
struct QFWithScratch
{
using GlobalScratchTuple = tuple<GlobalScratchTypes...>;
using ScratchScalar = scalar_t;
/// Number of real_t backing one scratch entry; see ScratchBank.
static constexpr int scalar_size =
ScratchBank<scalar_t, GlobalScratchTypes...>::scalar_size;
int nq = 0;
ScratchBank<scalar_t, 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);
}
scalar_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;
}
};
/// Q-function base with quadrature-point scratch only. @a scalar_t is the
/// scalar the q-function signature uses (real_t under Enzyme, dual otherwise).
template <typename scalar_t = real_t>
using QFWithScratchType = QFWithScratch<scalar_t>;
/// Q-function base with quadrature-point scratch and a global scratch tuple.
template <typename scalar_t = real_t>
using QFWithGlobalScratchType =
QFWithScratch<scalar_t, bool, real_t, Vector>;
namespace detail
{
template <typename T>
struct qfunc_uses_scratch
{
private:
template <typename scalar_t, typename... GlobalScratchTypes>
static std::true_type Test(
const QFWithScratch<scalar_t, 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 { };
// A separate shadow scratch bank only exists for Enzyme, which writes tangents
// into shadow memory. The native dual fallback carries the tangent inside the
// scratch entry itself (see ScratchBank::scalar_size), so a shadow bank would
// be allocated and never read; it is dropped entirely there.
template <typename T>
inline constexpr bool qfunc_needs_shadow_v =
#ifdef MFEM_USE_ENZYME
qfunc_uses_scratch_v<T>;
#else
false;
#endif
template <typename qfunc_t, bool needs_shadow>
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_needs_shadow_v<qfunc_t>>::type;
// Create a persistent q-function shadow if one is needed, otherwise return an empty struct.
template <typename qfunc_t>
inline qfunc_shadow_t<qfunc_t> MakeQFunctionShadowStorage(
const qfunc_t &qfunc)
{
if constexpr (qfunc_needs_shadow_v<qfunc_t>)
{
return qfunc.CreateShadow();
}
else
{
MFEM_CONTRACT_VAR(qfunc);
return {};
}
}
} // namespace detail
}
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#include "doperator.hpp"
#include <algorithm>
#ifdef MFEM_USE_MPI
using namespace mfem;
using namespace mfem::future;
namespace
void DifferentiableOperator::SetParameters(std::vector<Vector *> p) const
{
int GetTotalTrueVSize(const std::vector<FieldDescriptor> &fds)
{
int size = 0;
for (const auto &fd : fds)
MFEM_ASSERT(parameters.size() == p.size(),
"number of parameters doesn't match descriptors");
for (size_t i = 0; i < parameters.size(); i++)
{
size += mfem::future::GetTrueVSize(fd);
p[i]->Read();
parameters_l[i] = *p[i];
}
return size;
}
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> &infds,
const std::vector<FieldDescriptor> &outfds,
const std::vector<FieldDescriptor> &solutions,
const std::vector<FieldDescriptor> &parameters,
const ParMesh &mesh) :
Operator(),
mesh(mesh),
infds(infds),
outfds(outfds)
solutions(solutions),
parameters(parameters)
{
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());
fields.resize(solutions.size() + parameters.size());
fields_e.resize(fields.size());
solutions_l.resize(solutions.size());
parameters_l.resize(parameters.size());
infields_l.resize(infds.size());
for (size_t i = 0; i < infds.size(); i++)
for (size_t i = 0; i < solutions.size(); i++)
{
infields_l[i] = new Vector(GetVSize(infds[i]));
fields[i] = solutions[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,
for (size_t i = 0; i < parameters.size(); 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(HasFunctionalIntegrator(),
"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(HasFunctionalIntegrator(),
"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(HasFunctionalIntegrator(),
"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);
}
bool DifferentiableOperator::HasSecondDerivative(size_t gradient_id,
size_t direction_id) const
{
const second_derivative_key_t derivative_key{gradient_id, direction_id};
const auto it = second_derivative_action_callbacks.find(derivative_key);
return it != second_derivative_action_callbacks.end() && !it->second.empty();
fields[i + solutions.size()] = parameters[i];
}
}
#endif // MFEM_USE_MPI
+979 -1236
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-64
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@@ -1,64 +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 "../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);
}
};
}
+2 -73
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@@ -10,7 +10,6 @@
// CONTRIBUTING.md for details.
#pragma once
#include <ostream>
#include <type_traits>
namespace mfem::future
@@ -75,15 +74,6 @@ 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
@@ -100,14 +90,6 @@ 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
@@ -119,20 +101,11 @@ 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>
inline std::ostream& operator<<(std::ostream& out, Value<FIELD_ID>)
{
return out << "Value<" << FIELD_ID << ">";
}
struct is_value_fop<Value<FIELD_ID>> : std::true_type {};
/// @brief Gradient FieldOperator.
///
@@ -151,15 +124,6 @@ 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
@@ -177,39 +141,4 @@ 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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@@ -0,0 +1,536 @@
// 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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@@ -1,37 +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 <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
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@@ -0,0 +1,678 @@
// 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);
}
}
});
}
}
+5 -8
View File
@@ -20,7 +20,7 @@ namespace mfem::future
class ParameterSpace
{
public:
ParameterSpace(int vdim = 1) : vdim(vdim) { dtq.FE = nullptr; dtq.IntRule = nullptr; }
ParameterSpace(int vdim = 1) : vdim(vdim) {}
/// @brief Get vector dimension at each point
///
@@ -43,7 +43,7 @@ public:
/// Get spatial dimension
///
/// returns always 1.
constexpr int Dimension() const
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) const
virtual const Operator* GetElementRestriction(ElementDofOrdering o) const
{
if (!elem_restr)
{
@@ -74,14 +74,11 @@ 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, elem_restr, B, Bt;
mutable std::unique_ptr<Operator> prolongation;
mutable std::unique_ptr<Operator> elem_restr;
};
/// @brief Uniform parameter space
+619
View File
@@ -0,0 +1,619 @@
// 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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@@ -0,0 +1,346 @@
// 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
-264
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@@ -1,264 +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.
/**
* @file tensor_functions.hpp
*
* @brief Differentiable functions of tensors
*/
#pragma once
#include <cmath>
#include "../../linalg/dual.hpp"
#include "../../linalg/tensor.hpp"
#include "tuple.hpp"
#include "util.hpp"
// 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
{
/**
* @brief Differentiable approximation of maximum eigenvale of a symmetric tensor
*
* Estimates the maximum eigenvalue using
* $$
* smooth_max_eigenvalue(A) = \frac{1}{\beta} \log\Big( \mathrm{tr}\big(\exp(\beta A) \big) \Big)
* $$
* which is equivalent to using the log-sum-exp function on the eigenvalues of A.
*
* @param A The input tensor
* @param beta Sharpness parameter. Must be > 0. Larger values makes the approximation sharper.
* @return Approximate maximum eigenvalue of A
*/
template <int n> MFEM_HOST_DEVICE
real_t smooth_max_eigenvalue_symm(const tensor<real_t, n, n>& A, real_t beta)
{
auto [lambda, V] = eig_symm(A);
real_t lambda_max = lambda[n - 1];
real_t sum = 0;
for (int i = 0; i < n - 1; i++)
{
sum += std::exp(beta*(lambda[i] - lambda_max));
}
return lambda_max + std::log1p(sum)/beta;
}
/**
* @brief Differentiable approximation of minimum eigenvale of a symmetric tensor
*
* Estimates the minimum eigenvalue using
* $$
* smooth_min_eigenvalue(A) = -\frac{1}{\beta} \log\Big( \mathrm{tr}\big(\exp(-\beta A) \big) \Big)
* $$
* which is equivalent to using the negated log-sum-exp function on the eigenvalues of -A.
*
* @param A The input tensor
* @param beta Sharpness parameter. Must be > 0. Larger values makes the approximation sharper.
* @return Approximate minimum eigenvalue of A
*/
template <int n> MFEM_HOST_DEVICE
real_t smooth_min_eigenvalue_symm(const tensor<real_t, n, n>& A, real_t beta)
{
return -smooth_max_eigenvalue_symm<n>(-A, beta);
}
#ifdef MFEM_USE_ENZYME
namespace detail
{
// Custom forward-mode derivative rule for Enzyme
template<int n> MFEM_HOST_DEVICE
dual<real_t, real_t> smooth_max_eigenvalue_symm_fwddiff(
const tensor<real_t, n, n>& A, const tensor<real_t, n, n>& A_dot, real_t beta,
real_t beta_dot)
{
auto [lambda, V] = eig_symm(A);
real_t lambda_max = lambda[n - 1];
real_t sum = 0;
tensor<real_t, n> eg;
tensor<real_t, n> lambda_shifted;
for (int i = 0; i < n; i++)
{
lambda_shifted[i] = lambda[i] - lambda_max;
eg[i] = std::exp(beta*lambda_shifted[i]);
if (i != n - 1) { sum += eg[i]; }
}
real_t value = lambda_max + std::log1p(sum)/beta;
real_t Z = sum + 1.0;
real_t derivative{};
for (int mu = 0; mu < n; mu++)
{
real_t w_mu = eg[mu]/Z;
for (int i = 0; i < n; i++)
{
for (int j = 0; j < n; j++)
{
derivative += w_mu*V[i][mu]*V[j][mu]*A_dot[i][j];
}
}
}
derivative += (lambda_max - value + dot(eg, lambda_shifted)/Z)/beta * beta_dot;
return {value, derivative};
}
// Types and functions for Enzyme custom reverse mode derivative
template <int n>
struct SmoothMaxEigenvalueSymmTape
{
tensor<real_t, n> lambda;
tensor<real_t, n, n> V;
tensor<real_t, n> eg;
real_t sum;
real_t logZ;
};
template <int n>
struct SmoothMaxEigenvalueSymmAugmentedReturn
{
void* tape;
real_t value;
};
template <int n> MFEM_HOST_DEVICE
SmoothMaxEigenvalueSymmAugmentedReturn<n>
smooth_max_eigenvalue_symm_aug(const tensor<real_t, n, n>* A,
tensor<real_t, n, n>* A_bar,
real_t beta)
{
(void)A_bar; // accumulated in reverse pass
auto [lambda, V] = eig_symm(*A);
const real_t lambda_max = lambda[n - 1];
tensor<real_t, n> eg;
real_t sum = 0;
for (int i = 0; i < n; i++)
{
eg[i] = std::exp(beta*(lambda[i] - lambda_max));
if (i != n - 1) { sum += eg[i]; }
}
const real_t logZ = std::log1p(sum);
const real_t value = lambda_max + logZ/beta;
auto* tape = static_cast<SmoothMaxEigenvalueSymmTape<n>*>(
std::malloc(sizeof(SmoothMaxEigenvalueSymmTape<n>)));
if (tape)
{
tape->lambda = lambda;
tape->V = V;
tape->eg = eg;
tape->sum = sum;
tape->logZ = logZ;
}
return {static_cast<void*>(tape), value};
}
template <int n> MFEM_HOST_DEVICE
real_t smooth_max_eigenvalue_symm_rev(const tensor<real_t, n, n>* A,
tensor<real_t, n, n>* A_bar,
real_t beta,
real_t out_bar,
void* tape_ptr)
{
(void)A; // all needed info is on the tape
const auto* tape = static_cast<const SmoothMaxEigenvalueSymmTape<n>*>(tape_ptr);
if (!tape)
{
return 0.0;
}
const real_t Z = tape->sum + 1.0;
// d/dA = Σ_mu w_mu v_mu v_mu^T, where w_mu = eg[mu]/Z
for (int mu = 0; mu < n; mu++)
{
const real_t w_mu = tape->eg[mu] / Z;
for (int i = 0; i < n; i++)
{
for (int j = 0; j < n; j++)
{
(*A_bar)[i][j] += out_bar * w_mu * tape->V[i][mu] * tape->V[j][mu];
}
}
}
// d/dβ = -(log Z)/β^2 + (1/(β Z)) Σ_{i<n-1} exp(β(λ_i-λ_max)) (λ_i-λ_max)
real_t dZ_dBeta = 0.0;
const real_t& lambda_max = tape->lambda[n - 1];
for (int i = 0; i < n - 1; i++)
{
dZ_dBeta += tape->eg[i] * (tape->lambda[i] - lambda_max);
}
const real_t beta2 = beta * beta;
const real_t d_value_dBeta = -(tape->logZ)/beta2 + dZ_dBeta/(beta * Z);
std::free(const_cast<SmoothMaxEigenvalueSymmTape<n>*>(tape));
return out_bar * d_value_dBeta;
}
} // namespace detail
// Register custom derivatives (forward mode) with Enzyme
__attribute__((used))
void* __enzyme_register_derivative_smooth_max_eigenvalue_symm_2d[] =
{
reinterpret_cast<void*>(smooth_max_eigenvalue_symm<2>),
reinterpret_cast<void*>(detail::smooth_max_eigenvalue_symm_fwddiff<2>)
};
__attribute__((used))
void* __enzyme_register_derivative_smooth_max_eigenvalue_symm_3d[] =
{
reinterpret_cast<void*>(smooth_max_eigenvalue_symm<3>),
reinterpret_cast<void*>(detail::smooth_max_eigenvalue_symm_fwddiff<3>)
};
// Register custom gradients (combined reverse mode) with Enzyme
__attribute__((used))
void* __enzyme_register_gradient_smooth_max_eigenvalue_symm_2d[] =
{
reinterpret_cast<void*>(smooth_max_eigenvalue_symm<2>),
reinterpret_cast<void*>(detail::smooth_max_eigenvalue_symm_aug<2>),
reinterpret_cast<void*>(detail::smooth_max_eigenvalue_symm_rev<2>)
};
__attribute__((used))
void* __enzyme_register_gradient_smooth_max_eigenvalue_symm_3d[] =
{
reinterpret_cast<void*>(smooth_max_eigenvalue_symm<3>),
reinterpret_cast<void*>(detail::smooth_max_eigenvalue_symm_aug<3>),
reinterpret_cast<void*>(detail::smooth_max_eigenvalue_symm_rev<3>)
};
#endif // MFEM_USE_ENZYME
} // namespace future
} // namespace mfem
#if defined(__clang__)
#pragma clang attribute pop
#endif
+738 -638
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+804 -1389
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File diff suppressed because it is too large Load Diff
+2
View File
@@ -1446,6 +1446,8 @@ public:
dof2quad_array_open);
}
const Poly_1D::Basis &GetOpenBasis1D() const { return obasis1d; }
virtual ~VectorTensorFiniteElement();
};
+4 -4
View File
@@ -307,12 +307,12 @@ public:
/** @brief virtual function which evaluates the values of all
shape functions at a given point ip and stores
them in the vector shape of dimension Dof (6) */
them in the vector shape of dimension Dof (4) */
void CalcShape(const IntegrationPoint &ip, Vector &shape) const override;
/** @brief virtual function which evaluates the values of all
partial derivatives of all shape functions at a given
point ip and stores them in the matrix dshape (Dof x Dim) (6 x 3)
point ip and stores them in the matrix dshape (Dof x Dim) (4 x 3)
so that each row contains the derivatives of one shape function */
void CalcDShape(const IntegrationPoint &ip,
DenseMatrix &dshape) const override;
@@ -336,12 +336,12 @@ public:
/** @brief virtual function which evaluates the values of all
shape functions at a given point ip and stores
them in the vector shape of dimension Dof (5) */
them in the vector shape of dimension Dof (4) */
void CalcShape(const IntegrationPoint &ip, Vector &shape) const override;
/** @brief virtual function which evaluates the values of all
partial derivatives of all shape functions at a given
point ip and stores them in the matrix dshape (Dof x Dim) (5 x 3)
point ip and stores them in the matrix dshape (Dof x Dim) (4 x 3)
so that each row contains the derivatives of one shape function */
void CalcDShape(const IntegrationPoint &ip,
DenseMatrix &dshape) const override;
+57 -130
View File
@@ -1757,45 +1757,22 @@ H1_BergotPyramidElement::H1_BergotPyramidElement(const int p, const int btype)
real_t y = (ip.z < 1.0) ? (ip.y / (1.0 - ip.z)) : 0.0;
real_t z = ip.z;
if (std::abs(z - 1.0) < apex_tol)
{
// Compute the limit of the basis functions as z->1 with x and y on the
// line between the center of the base and the apex
o = 0;
for (int i = 0; i <= p; i++)
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
for (int k = 0; k <= p - maxij; k++)
if (i == 0 && j == 0)
{
T(o++, m) = ((k + 3.) * k + 2.) / 2.;
}
else
{
T(o++, m) = 0.;
}
}
}
else
{
poly1d.CalcLegendre(p, x, shape_x.GetData());
poly1d.CalcLegendre(p, y, shape_y.GetData());
poly1d.CalcLegendre(p, x, shape_x.GetData());
poly1d.CalcLegendre(p, y, shape_y.GetData());
o = 0;
for (int i = 0; i <= p; i++)
o = 0;
for (int i = 0; i <= p; i++)
{
for (int j = 0; j <= p; j++)
{
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
FuentesPyramid::CalcScaledJacobi(p-maxij, 2.0 * (maxij + 1.0),
z, 1.0, shape_z);
int maxij = std::max(i, j);
FuentesPyramid::CalcScaledJacobi(p-maxij, 2.0 * (maxij + 1.0),
z, 1.0, shape_z);
for (int k = 0; k <= p - maxij; k++)
{
T(o++, m) = shape_x(i) * shape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij);
}
for (int k = 0; k <= p - maxij; k++)
{
T(o++, m) = shape_x(i) * shape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij);
}
}
}
@@ -1816,44 +1793,25 @@ void H1_BergotPyramidElement::CalcShape(const IntegrationPoint &ip,
Vector u(dof);
#endif
const real_t x = (ip.z < 1.0) ? (ip.x / (1.0 - ip.z)) : 0.0;
const real_t y = (ip.z < 1.0) ? (ip.y / (1.0 - ip.z)) : 0.0;
const real_t z = ip.z;
real_t x = (ip.z < 1.0) ? (ip.x / (1.0 - ip.z)) : 0.0;
real_t y = (ip.z < 1.0) ? (ip.y / (1.0 - ip.z)) : 0.0;
real_t z = ip.z;
if (std::abs(z - 1.0) < apex_tol)
{
// Compute the limit of the basis functions as z->1 with x and y on the
// line between the center of the base and the apex
u = 0.;
int o = 0;
for (int i = 0; i <= p; i++)
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
for (int k = 0; k <= p - maxij; k++, o++)
if (i == 0 && j == 0)
{
u(o) = ((k + 3.) * k + 2.) / 2.;
}
}
}
else
{
poly1d.CalcLegendre(p, x, shape_x.GetData());
poly1d.CalcLegendre(p, y, shape_y.GetData());
poly1d.CalcLegendre(p, x, shape_x.GetData());
poly1d.CalcLegendre(p, y, shape_y.GetData());
int o = 0;
for (int i = 0; i <= p; i++)
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
FuentesPyramid::CalcScaledJacobi(p-maxij, 2.0 * (maxij + 1.0), z, 1.0,
shape_z);
for (int k = 0; k <= p - maxij; k++)
u[o++] = shape_x(i) * shape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij);
}
int o = 0;
for (int i = 0; i <= p; i++)
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
FuentesPyramid::CalcScaledJacobi(p-maxij, 2.0 * (maxij + 1.0),
z, 1.0, shape_z);
for (int k = 0; k <= p - maxij; k++)
u[o++] = shape_x(i) * shape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij);
}
}
Ti.Mult(u, shape);
}
@@ -1872,68 +1830,37 @@ void H1_BergotPyramidElement::CalcDShape(const IntegrationPoint &ip,
Vector dshape_z(order+1);
Vector dshape_z_dt(order+1);
#endif
const real_t x = (ip.z < 1.0) ? (ip.x / (1.0 - ip.z)) : 0.0;
const real_t y = (ip.z < 1.0) ? (ip.y / (1.0 - ip.z)) : 0.0;
const real_t z = ip.z;
real_t x = (ip.z < 1.0) ? (ip.x / (1.0 - ip.z)) : 0.0;
real_t y = (ip.z < 1.0) ? (ip.y / (1.0 - ip.z)) : 0.0;
real_t z = ip.z;
if (std::abs(z - 1.0) < apex_tol)
{
// Compute the limit of the gradients of the basis functions as
// z->1 with x and y on the line between the center of the base and the
// apex
du = 0.;
int o = 0;
for (int i = 0; i <= p; i++)
for (int j = 0; j <= p; j++)
poly1d.CalcLegendre(p, x, shape_x.GetData(), dshape_x.GetData());
poly1d.CalcLegendre(p, y, shape_y.GetData(), dshape_y.GetData());
int o = 0;
for (int i = 0; i <= p; i++)
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
FuentesPyramid::CalcScaledJacobi(p-maxij, 2.0 * (maxij + 1.0), z, 1.0,
shape_z, dshape_z, dshape_z_dt);
for (int k = 0; k <= p - maxij; k++, o++)
{
int maxij = std::max(i, j);
for (int k = 0; k <= p - maxij; k++, o++)
{
if (i == 0 && j == 0)
{
du(o,2) = (((k + 6.) * k + 11.) * k + 6.) * k / 6.;
}
else if (i == 1 && j == 0)
{
du(o,0) = ((((k + 10.) * k + 35.) * k + 50.) * k + 24.) / 24.;
}
else if (i == 0 && j == 1)
{
du(o,1) = ((((k + 10.) * k + 35.) * k + 50.) * k + 24.) / 24.;
}
}
du(o,0) = dshape_x(i) * shape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij - 1);
du(o,1) = shape_x(i) * dshape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij - 1);
du(o,2) = shape_x(i) * shape_y(j) * dshape_z(k) *
pow(1.0 - ip.z, maxij) +
(ip.x * dshape_x(i) * shape_y(j) +
ip.y * shape_x(i) * dshape_y(j)) *
shape_z(k) * pow(1.0 - ip.z, maxij - 2) -
maxij * shape_x(i) * shape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij - 1);
}
}
else
{
poly1d.CalcLegendre(p, x, shape_x.GetData(), dshape_x.GetData());
poly1d.CalcLegendre(p, y, shape_y.GetData(), dshape_y.GetData());
}
int o = 0;
for (int i = 0; i <= p; i++)
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
FuentesPyramid::CalcScaledJacobi(p-maxij, 2.0 * (maxij + 1.0),
z, 1.0,
shape_z, dshape_z, dshape_z_dt);
for (int k = 0; k <= p - maxij; k++, o++)
{
du(o,0) = dshape_x(i) * shape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij - 1);
du(o,1) = shape_x(i) * dshape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij - 1);
du(o,2) = shape_x(i) * shape_y(j) * dshape_z(k) *
pow(1.0 - ip.z, maxij) +
(ip.x * dshape_x(i) * shape_y(j) +
ip.y * shape_x(i) * dshape_y(j)) *
shape_z(k) * pow(1.0 - ip.z, maxij - 2) -
maxij * shape_x(i) * shape_y(j) * shape_z(k) *
(maxij > 0 ? pow(1.0 - ip.z, maxij - 1) : 0.0);
}
}
}
Ti.Mult(du, dshape);
}
-2
View File
@@ -208,8 +208,6 @@ private:
#endif
DenseMatrixInverse Ti;
static constexpr real_t apex_tol = 1e-8;
public:
H1_BergotPyramidElement(const int p,
const int btype = BasisType::GaussLobatto);
+57 -131
View File
@@ -1106,16 +1106,9 @@ L2_BergotPyramidElement::L2_BergotPyramidElement(const int p, const int btype)
{
const real_t wik = op[i] + op[k] + op[p-i-k];
const real_t w = wik * wjk * op[p-k];
if (std::abs(w) < apex_tol)
{
Nodes.IntPoint(o++).Set3(0.,0.,1.);
}
else
{
Nodes.IntPoint(o++).Set3(op[i] * (op[j] + op[p-j-k]) / w,
op[j] * (op[i] + op[p-i-k]) / w,
op[k] * op[p-k] / w);
}
Nodes.IntPoint(o++).Set3(op[i] * (op[j] + op[p-j-k]) / w,
op[j] * (op[j] + op[p-j-k]) / w,
op[k] * op[p-k] / w);
}
}
@@ -1132,45 +1125,22 @@ L2_BergotPyramidElement::L2_BergotPyramidElement(const int p, const int btype)
const real_t y = (ip.z < 1.0) ? (ip.y / (1.0 - ip.z)) : 0.0;
const real_t z = ip.z;
if (std::abs(z - 1.0) < apex_tol)
{
// Compute the limit of the basis functions as z->1 with x and y on the
// line between the center of the base and the apex
o = 0;
for (int i = 0; i <= p; i++)
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
for (int k = 0; k <= p - maxij; k++)
if (i == 0 && j == 0)
{
T(o++, m) = ((k + 3.) * k + 2.) / 2.;
}
else
{
T(o++, m) = 0.;
}
}
}
else
{
poly1d.CalcLegendre(p, x, shape_x.GetData());
poly1d.CalcLegendre(p, y, shape_y.GetData());
poly1d.CalcLegendre(p, x, shape_x.GetData());
poly1d.CalcLegendre(p, y, shape_y.GetData());
o = 0;
for (int i = 0; i <= p; i++)
o = 0;
for (int i = 0; i <= p; i++)
{
for (int j = 0; j <= p; j++)
{
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
FuentesPyramid::CalcScaledJacobi(p-maxij, 2.0 * (maxij + 1.0),
z, 1.0, shape_z);
int maxij = std::max(i, j);
FuentesPyramid::CalcScaledJacobi(p-maxij, 2.0 * (maxij + 1.0),
z, 1.0, shape_z);
for (int k = 0; k <= p - maxij; k++)
{
T(o++, m) = shape_x(i) * shape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij);
}
for (int k = 0; k <= p - maxij; k++)
{
T(o++, m) = shape_x(i) * shape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij);
}
}
}
@@ -1195,41 +1165,26 @@ void L2_BergotPyramidElement::CalcShape(const IntegrationPoint &ip,
const real_t y = (ip.z < 1.0) ? (ip.y / (1.0 - ip.z)) : 0.0;
const real_t z = ip.z;
if (std::abs(z - 1.0) < apex_tol)
{
// Compute the limit of the basis functions as z->1 with x and y on the
// line between the center of the base and the apex
u = 0.;
int o = 0;
for (int i = 0; i <= p; i++)
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
for (int k = 0; k <= p - maxij; k++, o++)
if (i == 0 && j == 0)
{
u(o) = ((k + 3.) * k + 2.) / 2.;
}
}
}
else
{
poly1d.CalcLegendre(p, x, shape_x.GetData());
poly1d.CalcLegendre(p, y, shape_y.GetData());
poly1d.CalcLegendre(p, x, shape_x.GetData());
poly1d.CalcLegendre(p, y, shape_y.GetData());
int o = 0;
for (int i = 0; i <= p; i++)
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
FuentesPyramid::CalcScaledJacobi(p-maxij, 2.0 * (maxij + 1.0),
z, 1.0, shape_z);
int o = 0;
for (int i = 0; i <= p; i++)
{
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
FuentesPyramid::CalcScaledJacobi(p-maxij, 2.0 * (maxij + 1.0), z, 1.0,
shape_z);
for (int k = 0; k <= p - maxij; k++)
u[o++] = shape_x(i) * shape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij);
for (int k = 0; k <= p - maxij; k++)
{
u[o++] = shape_x(i) * shape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij);
}
}
}
Ti.Mult(u, shape);
}
@@ -1253,64 +1208,35 @@ void L2_BergotPyramidElement::CalcDShape(const IntegrationPoint &ip,
const real_t y = (ip.z < 1.0) ? (ip.y / (1.0 - ip.z)) : 0.0;
const real_t z = ip.z;
if (std::abs(z - 1.0) < apex_tol)
{
// Compute the limit of the gradients of the basis functions as
// z->1 with x and y on the line between the center of the base and the
// apex
du = 0.;
int o = 0;
for (int i = 0; i <= p; i++)
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
for (int k = 0; k <= p - maxij; k++, o++)
{
if (i == 0 && j == 0)
{
du(o,2) = (((k + 6.) * k + 11.) * k + 6.) * k / 6.;
}
else if (i == 1 && j == 0)
{
du(o,0) = ((((k + 10.) * k + 35.) * k + 50.) * k + 24.) / 24.;
}
else if (i == 0 && j == 1)
{
du(o,1) = ((((k + 10.) * k + 35.) * k + 50.) * k + 24.) / 24.;
}
}
}
}
else
{
Poly_1D::CalcLegendre(p, x, shape_x.GetData(), dshape_x.GetData());
Poly_1D::CalcLegendre(p, y, shape_y.GetData(), dshape_y.GetData());
Poly_1D::CalcLegendre(p, x, shape_x.GetData(), dshape_x.GetData());
Poly_1D::CalcLegendre(p, y, shape_y.GetData(), dshape_y.GetData());
int o = 0;
for (int i = 0; i <= p; i++)
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
FuentesPyramid::CalcScaledJacobi(p-maxij, 2.0 * (maxij + 1.0),
z, 1.0,
shape_z, dshape_z, dshape_z_dt);
int o = 0;
for (int i = 0; i <= p; i++)
{
for (int j = 0; j <= p; j++)
{
int maxij = std::max(i, j);
FuentesPyramid::CalcScaledJacobi(p-maxij, 2.0 * (maxij + 1.0), z, 1.0,
shape_z, dshape_z, dshape_z_dt);
for (int k = 0; k <= p - maxij; k++, o++)
{
du(o,0) = dshape_x(i) * shape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij - 1);
du(o,1) = shape_x(i) * dshape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij - 1);
du(o,2) = shape_x(i) * shape_y(j) * dshape_z(k) *
pow(1.0 - ip.z, maxij) +
(ip.x * dshape_x(i) * shape_y(j) +
ip.y * shape_x(i) * dshape_y(j)) *
shape_z(k) * pow(1.0 - ip.z, maxij - 2) -
maxij * shape_x(i) * shape_y(j) * shape_z(k) *
(maxij > 0 ? pow(1.0 - ip.z, maxij - 1) : 0.0);
}
for (int k = 0; k <= p - maxij; k++, o++)
{
du(o,0) = dshape_x(i) * shape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij - 1);
du(o,1) = shape_x(i) * dshape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij - 1);
du(o,2) = shape_x(i) * shape_y(j) * dshape_z(k) *
pow(1.0 - ip.z, maxij) +
(ip.x * dshape_x(i) * shape_y(j) +
ip.y * shape_x(i) * dshape_y(j)) *
shape_z(k) * pow(1.0 - ip.z, maxij - 2) -
((maxij > 0) ? (maxij * shape_x(i) * shape_y(j) * shape_z(k) *
pow(1.0 - ip.z, maxij - 1)) : 0.0);
}
}
}
Ti.Mult(du, dshape);
}
-2
View File
@@ -225,8 +225,6 @@ private:
#endif
DenseMatrixInverse Ti;
static constexpr real_t apex_tol = 1e-8;
public:
/// Construct the L2_PyramidElement of order @a p and BasisType @a btype
L2_BergotPyramidElement(const int p,
+1 -38
View File
@@ -1282,49 +1282,12 @@ ND_SegmentElement::ND_SegmentElement(const int p, const int ob_type)
}
}
void ND_SegmentElement::CalcShape(const IntegrationPoint &ip,
Vector &shape) const
{
if (obasis1d.IsIntegratedType()) { obasis1d.ScaleIntegrated(false); }
obasis1d.Eval(ip.x, shape);
}
void ND_SegmentElement::CalcVShape(const IntegrationPoint &ip,
DenseMatrix &shape) const
{
Vector vshape(shape.Data(), dof);
CalcShape(ip, vshape);
}
void ND_SegmentElement::ProjectIntegrated(VectorCoefficient &vc,
ElementTransformation &Trans,
Vector &dofs) const
{
MFEM_ASSERT(obasis1d.IsIntegratedType(), "Not integrated type");
real_t vk[Geometry::MaxDim];
Vector xk(vk, vc.GetVDim());
const real_t *cp = poly1d.ClosedPoints(dof, BasisType::GaussLobatto);
const IntegrationRule &ir = IntRules.Get(Geometry::SEGMENT, dof);
IntegrationPoint ip;
for (int i = 0; i < dof; i++)
{
const real_t h = cp[i+1] - cp[i];
real_t val = 0.0;
for (int q = 0; q < ir.GetNPoints(); q++)
{
const IntegrationPoint &ip1d = ir.IntPoint(q);
ip.x = cp[i] + h*ip1d.x;
Trans.SetIntPoint(&ip);
vc.Eval(xk, Trans, ip);
val += ip1d.weight*Trans.Jacobian().InnerProduct(tk, vk);
}
dofs(i) = val*h;
}
obasis1d.Eval(ip.x, vshape);
}
const real_t ND_WedgeElement::tk[15] =
+3 -10
View File
@@ -303,7 +303,8 @@ public:
/** @brief Construct the ND_SegmentElement of order @a p and open
BasisType @a ob_type */
ND_SegmentElement(const int p, const int ob_type = BasisType::GaussLegendre);
void CalcShape(const IntegrationPoint &ip, Vector &shape) const override;
void CalcShape(const IntegrationPoint &ip, Vector &shape) const override
{ obasis1d.Eval(ip.x, shape); }
void CalcVShape(const IntegrationPoint &ip,
DenseMatrix &shape) const override;
void CalcVShape(ElementTransformation &Trans,
@@ -324,10 +325,7 @@ public:
using FiniteElement::Project;
void Project(VectorCoefficient &vc,
ElementTransformation &Trans, Vector &dofs) const override
{
if (obasis1d.IsIntegratedType()) { ProjectIntegrated(vc, Trans, dofs); }
else { Project_ND(tk, dof2tk, vc, Trans, dofs); }
}
{ Project_ND(tk, dof2tk, vc, Trans, dofs); }
void ProjectMatrixCoefficient(MatrixCoefficient &mc,
ElementTransformation &T,
Vector &dofs) const override
@@ -340,11 +338,6 @@ public:
ElementTransformation &Trans,
DenseMatrix &grad) const override
{ ProjectGrad_ND(tk, dof2tk, fe, Trans, grad); }
protected:
void ProjectIntegrated(VectorCoefficient &vc,
ElementTransformation &Trans,
Vector &dofs) const;
};
class ND_WedgeElement : public VectorFiniteElement
-6
View File
@@ -17,12 +17,6 @@
namespace mfem
{
struct ScalarPyramid
{
// Default basis type for H1 and L2 pyramids
static inline int DefaultType = 1; // Bergot(0) or Fuentes(1)
};
/** Base class for arbitrary order basis functions on pyramid-shaped elements
This base class provides a common class to store temporary vectors,
+30 -88
View File
@@ -228,19 +228,7 @@ FiniteElementCollection *FiniteElementCollection::New(const char *name)
}
else if (!strncmp(name, "H1_", 3))
{
// Parse pyramid basis type if included in the name
const char *pyr = strstr(name, "Pyr");
if (pyr == NULL)
{
// Use default pyramid type elements
fec = new H1_FECollection(atoi(name + 7), atoi(name + 3));
}
else
{
// Use specific pyramid type elements
fec = new H1_FECollection(atoi(name + 7), atoi(name + 3),
BasisType::GaussLobatto, atoi(pyr + 3));
}
fec = new H1_FECollection(atoi(name + 7), atoi(name + 3));
}
else if (!strncmp(name, "H1Pos_Trace_", 12))
{
@@ -257,44 +245,26 @@ FiniteElementCollection *FiniteElementCollection::New(const char *name)
}
else if (!strncmp(name, "H1@", 3))
{
// Parse pyramid basis type if included in the name
const char *pyr = strstr(name, "Pyr");
if (pyr == NULL)
{
// Use default pyramid type elements
fec = new H1_FECollection(atoi(name + 9), atoi(name + 5),
BasisType::GetType(name[3]));
}
else
{
// Use specific pyramid type elements
fec = new H1_FECollection(atoi(name + 9), atoi(name + 5),
BasisType::GetType(name[3]),
atoi(pyr + 3));
}
fec = new H1_FECollection(atoi(name + 9), atoi(name + 5),
BasisType::GetType(name[3]));
}
else if (!strncmp(name, "L2", 2))
else if (!strncmp(name, "L2_T", 4))
fec = new L2_FECollection(atoi(name + 10), atoi(name + 6),
atoi(name + 4));
else if (!strncmp(name, "L2_", 3))
{
// Parse Map Type
const int mtype = strstr(name, "Int") == NULL ?
FiniteElement::VALUE : FiniteElement::INTEGRAL;
// Parse the base order
const int p = atoi(strstr(name, "_P") + 2);
// Parse the mesh dimension
const int dim = atoi(strstr(name, "D") - 1);
// Parse basis type if specified
const char *t = strstr(name, "_T");
const int btype = t == NULL ? BasisType::GaussLegendre : atoi(t + 2);
// Parse the pyramid type if specified
const char *pyr = strstr(name, "Pyr");
const int ptype = pyr == NULL ? 1 : atoi(pyr + 3);
// Create collection
fec = new L2_FECollection(p, dim, btype, mtype, ptype);
fec = new L2_FECollection(atoi(name + 7), atoi(name + 3));
}
else if (!strncmp(name, "L2Int_T", 7))
{
fec = new L2_FECollection(atoi(name + 13), atoi(name + 9),
atoi(name + 7), FiniteElement::INTEGRAL);
}
else if (!strncmp(name, "L2Int_", 6))
{
fec = new L2_FECollection(atoi(name + 10), atoi(name + 6),
BasisType::GaussLegendre,
FiniteElement::INTEGRAL);
}
else if (!strncmp(name, "RT_Trace_", 9))
{
@@ -1739,10 +1709,9 @@ const int *RT1_3DFECollection::DofOrderForOrientation(Geometry::Type GeomType,
H1_FECollection::H1_FECollection(const int p, const int dim, const int btype,
const int pyr_type)
const int pyrtype)
: FiniteElementCollection(p)
, dim(dim)
, p_type(pyr_type)
{
MFEM_VERIFY(p >= 1, "H1_FECollection requires order >= 1.");
MFEM_VERIFY(dim >= 0 && dim <= 3, "H1_FECollection requires 0 <= dim <= 3.");
@@ -1755,14 +1724,7 @@ H1_FECollection::H1_FECollection(const int p, const int dim, const int btype,
{
case BasisType::GaussLobatto:
{
if (pyr_type == ScalarPyramid::DefaultType)
{
snprintf(h1_name, 32, "H1_%dD_P%d", dim, p);
}
else
{
snprintf(h1_name, 32, "H1_%dD_P%d_Pyr%d", dim, p, pyr_type);
}
snprintf(h1_name, 32, "H1_%dD_P%d", dim, p);
break;
}
case BasisType::Positive:
@@ -1948,11 +1910,11 @@ H1_FECollection::H1_FECollection(const int p, const int dim, const int btype,
H1_dof[Geometry::TETRAHEDRON] = (TriDof*pm3)/3;
H1_dof[Geometry::CUBE] = QuadDof*pm1;
H1_dof[Geometry::PRISM] = TriDof*pm1;
if (pyr_type == 0 || b_type == BasisType::Positive)
if (pyrtype == 0 || b_type == BasisType::Positive)
{
H1_dof[Geometry::PYRAMID] = pm2*pm1*(2*p-3)/6; // Bergot (JSC)
}
else if (pyr_type == 1)
else if (pyrtype == 1)
{
H1_dof[Geometry::PYRAMID] = pm1*pm1*pm1; // Fuentes
}
@@ -1973,15 +1935,13 @@ H1_FECollection::H1_FECollection(const int p, const int dim, const int btype,
new H1_TetrahedronElement(p, btype);
H1_Elements[Geometry::CUBE] = new H1_HexahedronElement(p, btype);
H1_Elements[Geometry::PRISM] = new H1_WedgeElement(p, btype);
if (pyr_type == 0)
if (pyrtype == 0)
{
H1_Elements[Geometry::PYRAMID] =
new H1_BergotPyramidElement(p, btype);
H1_Elements[Geometry::PYRAMID] = new H1_BergotPyramidElement(p, btype);
}
else
{
H1_Elements[Geometry::PYRAMID] =
new H1_FuentesPyramidElement(p, btype);
H1_Elements[Geometry::PYRAMID] = new H1_FuentesPyramidElement(p, btype);
}
}
@@ -2188,7 +2148,6 @@ L2_FECollection::L2_FECollection(const int p, const int dim, const int btype,
: FiniteElementCollection(p)
, dim(dim)
, m_type(map_type)
, p_type(pyr_type)
{
MFEM_VERIFY(p >= 0, "L2_FECollection requires order >= 0.");
@@ -2204,25 +2163,10 @@ L2_FECollection::L2_FECollection(const int p, const int dim, const int btype,
switch (btype)
{
case BasisType::GaussLegendre:
if (pyr_type == ScalarPyramid::DefaultType)
{
snprintf(d_name, 32, "%s_%dD_P%d", prefix, dim, p);
}
else
{
snprintf(d_name, 32, "%s_%dD_P%d_Pyr%d", prefix, dim, p, pyr_type);
}
snprintf(d_name, 32, "%s_%dD_P%d", prefix, dim, p);
break;
default:
if (pyr_type == ScalarPyramid::DefaultType)
{
snprintf(d_name, 32, "%s_T%d_%dD_P%d", prefix, btype, dim, p);
}
else
{
snprintf(d_name, 32, "%s_T%d_%dD_P%d_Pyr%d",
prefix, btype, dim, p, pyr_type);
}
snprintf(d_name, 32, "%s_T%d_%dD_P%d", prefix, btype, dim, p);
}
for (int g = 0; g < Geometry::NumGeom; g++)
@@ -2341,13 +2285,11 @@ L2_FECollection::L2_FECollection(const int p, const int dim, const int btype,
L2_Elements[Geometry::PRISM] = new L2_WedgeElement(p, btype);
if (pyr_type == 0)
{
L2_Elements[Geometry::PYRAMID] =
new L2_BergotPyramidElement(p, btype);
L2_Elements[Geometry::PYRAMID] = new L2_BergotPyramidElement(p, btype);
}
else
{
L2_Elements[Geometry::PYRAMID] =
new L2_FuentesPyramidElement(p, btype);
L2_Elements[Geometry::PYRAMID] = new L2_FuentesPyramidElement(p, btype);
}
}
+5 -10
View File
@@ -100,10 +100,6 @@ public:
return FiniteElementForGeometry(GeomType);
}
/** @brief Returns a collection of the trace elements.
@note The collection is owned by the caller and is NOT deleted in the
destructor. */
virtual FiniteElementCollection *GetTraceCollection() const;
virtual ~FiniteElementCollection();
@@ -290,7 +286,7 @@ protected:
class H1_FECollection : public FiniteElementCollection
{
protected:
int dim, b_type, p_type;
int dim, b_type;
char h1_name[32];
FiniteElement *H1_Elements[Geometry::NumGeom];
int H1_dof[Geometry::NumGeom];
@@ -299,7 +295,7 @@ protected:
public:
explicit H1_FECollection(const int p, const int dim = 3,
const int btype = BasisType::GaussLobatto,
const int pyr_type = ScalarPyramid::DefaultType);
const int pyrtype = 1);
const FiniteElement *
FiniteElementForGeometry(Geometry::Type GeomType) const override;
@@ -324,7 +320,7 @@ public:
const int *GetDofMap(Geometry::Type GeomType, int p) const;
FiniteElementCollection *Clone(int p) const override
{ return new H1_FECollection(p, dim, b_type, p_type); }
{ return new H1_FECollection(p, dim, b_type); }
int GetConstructorOrder() const override
{ return base_p; }
@@ -371,7 +367,6 @@ private:
int dim;
int b_type; // BasisType
int m_type; // map type
int p_type; // Pyramid type (0 -> Bergot, 1 -> Fuentes)
char d_name[32];
ScalarFiniteElement *L2_Elements[Geometry::NumGeom];
ScalarFiniteElement *Tr_Elements[Geometry::NumGeom];
@@ -384,7 +379,7 @@ public:
L2_FECollection(const int p, const int dim,
const int btype = BasisType::GaussLegendre,
const int map_type = FiniteElement::VALUE,
const int pyr_type = ScalarPyramid::DefaultType);
const int pyrtype = 1);
const FiniteElement *
FiniteElementForGeometry(Geometry::Type GeomType) const override;
@@ -414,7 +409,7 @@ public:
int GetBasisType() const { return b_type; }
FiniteElementCollection *Clone(int p) const override
{ return new L2_FECollection(p, dim, b_type, m_type, p_type); }
{ return new L2_FECollection(p, dim, b_type, m_type); }
int GetConstructorOrder() const override
{ return base_p; }
+1 -1
View File
@@ -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"
+725 -1233
View File
File diff suppressed because it is too large Load Diff
+51 -166
View File
@@ -12,9 +12,6 @@
#ifndef MFEM_GSLIB
#define MFEM_GSLIB
#include <map>
#include <vector>
#include "../config/config.hpp"
#ifdef MFEM_USE_MPI
#include "pgridfunc.hpp"
@@ -122,11 +119,6 @@ protected:
// IntegrationRules for simplex->Quad/Hex and to project to p_max in-case of
// p-refinement.
Array<IntegrationRule *> ir_split;
/// Integration rules built at the field polynomial order (only for surface
/// meshes when mesh order is not the same as gridfunction order).
Array<IntegrationRule *> ir_split_sol;
/// Order at which #ir_split_sol was built; -1 means not built.
int ir_split_sol_order = -1;
Array<FiniteElementSpace *> fes_rst_map; //FESpaces to map Quad/Hex->Simplex
Array<GridFunction *> gf_rst_map; // GridFunctions to map Quad/Hex->Simplex
FiniteElementCollection *fec_map_lin;
@@ -142,8 +134,6 @@ protected:
AvgType avgtype; // average type used for L2 functions
Array<int> split_element_map;
Array<int> split_element_index;
// Geometry::Type (as int) of the original element for each split quad.
Array<int> split_element_geom;
int NE_split_total; // total number of elements after mesh splitting
int mesh_points_cnt; // number of mesh nodes
// Tolerance to ignore points found beyond the mesh boundary.
@@ -151,12 +141,6 @@ protected:
double bdr_tol;
// Use CPU functions for Mesh/GridFunction on device for gslib1.0.7
bool gpu_to_cpu_fallback = false;
// Check if a point is inside the oriented bounding box of an
// element before the Newton iteration.
// Note: only used in MFEM implementation (not in gslib) which currently
// supports GPU kernels for area meshes in 2D, volume meshes in 3D,
// and surface meshes in 1D/2D/3D.
bool obb_check = true;
// Device specific data used for FindPoints
struct DEV_STRUCT
@@ -178,16 +162,11 @@ protected:
mutable double surf_dist_tol;
} DEV;
// Helper function to setup and free gslib's crystal router.
void SetupCrystal(); // Called inside Setup and SetupSurf_base
void FreeCrystal(); // Called inside FreeData
/// Use GSLIB for communication and interpolation. Updates field_out on
/// host.
/// Use GSLIB for communication and interpolation
virtual void InterpolateH1(const GridFunction &field_in, Vector &field_out,
const int field_out_ordering);
/// Uses GSLIB Crystal Router for communication followed by MFEM's
/// interpolation functions. Updates field_out on host.
/// interpolation functions
virtual void InterpolateGeneral(const GridFunction &field_in,
Vector &field_out,
const int field_out_ordering);
@@ -202,26 +181,12 @@ protected:
IntegrationRule *irule,
int order);
/** @brief Build integration rules at the given @a order for each split mesh
* and store them in @a ir_out. Requires that \ref SetupSplitMeshes has
* already been called. */
virtual void SetupIntegrationRules(const int order,
Array<IntegrationRule *> &ir_out);
/** @brief Helper function that calls \ref SetupSplitMeshes and
* \ref SetupIntegrationRules. */
* \ref SetupIntegrationRuleForSplitMesh. */
virtual void SetupSplitMeshesAndIntegrationRules(const int order);
/** @brief Get GridFunction value at the points expected by GSLIB.
* @param[in] gf_in Grid function to evaluate.
* @param[out] node_vals Output values.
* @param[in] ir_in If non-null, use these rules instead of #ir_split.
* @param[in] by_element If true, output has element-major layout
* [nel][vdim][ndofs]; otherwise component-major
* layout [vdim][total_pts]. */
virtual void GetNodalValues(const GridFunction *gf_in, Vector &node_vals,
const Array<IntegrationRule *> *ir_in = nullptr,
bool by_element = false) const;
/// Get GridFunction value at the points expected by GSLIB.
virtual void GetNodalValues(const GridFunction *gf_in, Vector &node_vals) const;
/** @brief Map {r,s,t} coordinates from [-1,1] to [0,1] for MFEM. For
* simplices, find the original element number (that was split into
@@ -326,60 +291,29 @@ protected:
void findptsedge_setup_2(DEV_STRUCT &devs,
const double *const elx[2],
const unsigned n,
const unsigned int nel,
const uint nel,
const unsigned m,
const double bbox_rel_size_inc,
const unsigned int local_hash_size,
const unsigned int global_hash_size,
const Vector *aabb_sz_inc);
const double bbox_tol,
const uint local_hash_size,
const uint global_hash_size);
/// Preprocess 3D surface mesh needed for FindPoints.
void findptssurf_setup_3(DEV_STRUCT &devs,
const double *const elx[3],
const unsigned n,
const unsigned int nel,
const uint nel,
const unsigned m,
const double bbox_rel_size_inc,
const unsigned int local_hash_size,
const unsigned int global_hash_size,
const int rD,
const Vector *aabb_sz_inc);
const double bbox_tol,
const uint local_hash_size,
const uint global_hash_size,
const int rD);
/** @brief Shared implementation for the public surface-setup methods.
*
* @details Initializes the surface-search data structures, builds the
* split-element representation expected by gslib, and constructs the
* element bounding boxes used by the MFEM surface kernels.
*
* If @a aabb_sz_inc is null, the setup stores the default oriented
* bounding boxes and uses @a bbox_rel_size_inc as their relative size
* increase factor.
*
* If @a aabb_sz_inc is non-null, the setup stores axis-aligned bounding
* boxes only, applies the requested absolute AABB expansion in each
* physical direction, and adjusts the tolerance @a bdr_tol so points
* found in the expanded region are classified as border points.
*
* @param[in] m Input surface mesh.
* @param[in] bbox_rel_size_inc Relative size increase applied when
* expanding each element bounding box during
* setup.
* @param[in] aabb_sz_inc Optional total absolute AABB expansion
* applied to the stored axis-aligned
* bounding boxes after construction.
* @param[in] newt_tol Newton tolerance for the point-search
* kernels.
*/
void SetupSurf_Base(Mesh &m,
const double bbox_rel_size_inc,
const Vector *aabb_sz_inc,
const double newt_tol);
public:
/// Serial constructor
FindPointsGSLIB();
/// Serial constructor + setup with given Mesh (see \ref Setup)
FindPointsGSLIB(Mesh &mesh_in, const double bbox_rel_size_inc = 0.1,
FindPointsGSLIB(Mesh &mesh_in, const double bb_t = 0.1,
const double newt_tol = 1.0e-12,
const int npt_max = 256);
@@ -388,7 +322,7 @@ public:
FindPointsGSLIB(MPI_Comm comm_);
/// Constructor + setup with given ParMesh (see \ref Setup)
FindPointsGSLIB(ParMesh &mesh_in, const double bbox_rel_size_inc = 0.1,
FindPointsGSLIB(ParMesh &mesh_in, const double bb_t = 0.1,
const double newt_tol = 1.0e-12,
const int npt_max = 256);
#endif
@@ -404,59 +338,23 @@ public:
Note: not tested with periodic (L2).
Note: the input mesh \p m must have Nodes set.
@param[in] m Input mesh.
@param[in] bbox_rel_size_inc (Optional) Relative size increase applied
when expanding each element bounding box.
@param[in] newt_tol (Optional) Newton tolerance for the gslib
search methods.
@param[in] npt_max (Optional) Number of points for
simultaneous iteration. This alters
performance and memory footprint.
@param[in] m Input mesh.
@param[in] bb_t (Optional) Relative size of bounding box around
each element.
@param[in] newt_tol (Optional) Newton tolerance for the gslib
search methods.
@param[in] npt_max (Optional) Number of points for simultaneous
iteration. This alters performance and
memory footprint.
*/
void Setup(Mesh &m, const double bbox_rel_size_inc = 0.1,
const double newt_tol = 1.0e-12,
void Setup(Mesh &m, const double bb_t = 0.1, const double newt_tol = 1.0e-12,
const int npt_max = 256);
/// Preprocess the surface mesh to compute data for FindPoints.
void SetupSurf(Mesh &m,
const double bbox_rel_size_inc = 0.1,
const double newt_tol = 1.0e-12);
/** @brief Preprocess the surface mesh to compute data for FindPoints using
* absolute AABB expansion.
*
* @details This method computes only axis-aligned bounding boxes and
* increases their total length by a user-specified amount in each
* physical direction. The absolute AABB expansion is applied
* symmetrically to the lower and upper bounds.
*
* The size of @a aabb_sz_inc determines how the expansion values are
* interpreted:
* - `1`: one expansion value used in every direction for every element
* - `NElements`: one expansion value per element, reused in x/y/z
* directions
* - `SpaceDim`: one expansion value per physical direction, reused for
* every element
* - `NElements*SpaceDim`: one expansion value per element and direction,
* ordered as `(dx1,dy1,dz1, ... dxN,dyN,dzN)`
*
* This method disables the oriented bounding-box precheck because the
* stored boxes are modified only in their axis-aligned representation.
*
* @param[in] m Input surface mesh.
* @param[in] aabb_sz_inc Total absolute AABB expansion applied in
* each physical direction to the stored
* axis-aligned bounding boxes.
* @param[in] newt_tol Newton tolerance for the point-search
* kernels.
*
* @note We disable the oriented bounding box check with this setup.
* @a bdr_tol is also adjusted so that all points in the AABBs can
* be found.
*/
void SetupSurfWithAABBExpansion(Mesh &m, const Vector &aabb_sz_inc,
const double newt_tol = 1.0e-12);
const double bb_t = 0.1,
const double newt_tol = 1.0e-12,
const int npt_max = 256);
/** @brief Searches positions given in physical space by \p point_pos.
@@ -503,8 +401,7 @@ public:
/// Setup FindPoints and search positions
void FindPoints(Mesh &m, const Vector &point_pos,
const int point_pos_ordering = Ordering::byNODES,
const double bbox_rel_size_inc = 0.1,
const double newt_tol = 1.0e-12,
const double bb_t = 0.1, const double newt_tol = 1.0e-12,
const int npt_max = 256);
/** @brief Interpolation of field values at prescribed reference space
@@ -516,11 +413,7 @@ public:
mesh that was given to Setup().
@param[out] field_out Interpolated values. For points that are not found
the value is set to #default_interp_value.
The output ordering is determined from field_in.
@note: field_out is moved to device if field_in is on device. Otherwise,
field_out memory allocation is not changed.
*/
The output ordering is determined from field_in.*/
virtual void Interpolate(const GridFunction &field_in, Vector &field_out);
/// Interpolation of field values, with output ordering specification.
@@ -575,12 +468,7 @@ public:
* @details When using FindPoints, gslib may return points as found on the
* boundary even when they are slightly outside the domain. This tolerance
* is used to filter such points based on the distance^2 value and mark them
* as not found.
*
* @note When the SetupSurfWithAABBExpansion method is used for surface
* meshes, this tolerance is automatically computed based on the size of
* expanded AABBs. Using this method will override that computed tolerance.
* */
* as not found.*/
virtual void SetDistanceToleranceForPointsFoundOnBoundary(double bdr_tol_)
{
bdr_tol = bdr_tol_;
@@ -715,28 +603,25 @@ public:
Note: not tested with periodic meshes (L2).
Note: the input mesh \p m must have Nodes set.
@param[in] m Input mesh.
@param[in] meshid A unique # for each overlapping mesh.
This id is used to make sure that points
being searched are not looked for in the
mesh that they belong to.
@param[in] gfmax (Optional) GridFunction in H1 that is used
as a discriminator when one point is
located in multiple meshes. The mesh that
maximizes gfmax is chosen. For example,
using the distance field based on the
overlapping boundaries is helpful for
convergence during Schwarz iterations.
@param[in] bbox_rel_size_inc (Optional) Relative size increase applied
when expanding each element bounding box.
@param[in] newt_tol (Optional) Newton tolerance for the gslib
search methods.
@param[in] npt_max (Optional) Number of points for
simultaneous iteration. This alters
performance and memory footprint.*/
void Setup(Mesh &m, const int meshid, GridFunction *gfmax = nullptr,
const double bbox_rel_size_inc = 0.1,
const double newt_tol = 1.0e-12,
@param[in] m Input mesh.
@param[in] meshid A unique # for each overlapping mesh. This id is
used to make sure that points being searched are not
looked for in the mesh that they belong to.
@param[in] gfmax (Optional) GridFunction in H1 that is used as a
discriminator when one point is located in multiple
meshes. The mesh that maximizes gfmax is chosen.
For example, using the distance field based on the
overlapping boundaries is helpful for convergence
during Schwarz iterations.
@param[in] bb_t (Optional) Relative size of bounding box around
each element.
@param[in] newt_tol (Optional) Newton tolerance for the gslib
search methods.
@param[in] npt_max (Optional) Number of points for simultaneous
iteration. This alters performance and
memory footprint.*/
void Setup(Mesh &m, const int meshid, GridFunction *gfmax = NULL,
const double bb_t = 0.1, const double newt_tol = 1.0e-12,
const int npt_max = 256);
/** Searches positions given in physical space by \p point_pos. All output
@@ -792,7 +677,7 @@ class GSOPGSLIB
protected:
struct gslib::crystal *cr; // gslib's internal data
struct gslib::comm *gsl_comm; // gslib's internal data
struct gslib::gs_data *gsl_data = nullptr;
struct gslib::gs_data *gsl_data = NULL;
int num_ids;
public:
+170 -64
View File
@@ -11,7 +11,7 @@
#include "../gslib.hpp"
#include "../../general/forall.hpp"
#include "gslib_kernel_helpers.hpp"
#include "../../linalg/kernels.hpp"
#ifdef MFEM_USE_GSLIB
@@ -27,6 +27,8 @@
#pragma GCC diagnostic pop
#endif
#include <climits>
namespace mfem
{
#if GSLIB_RELEASE_VERSION >= 10009
@@ -52,14 +54,127 @@ struct findptsElementGPT_t
double x[DIM], jac[DIM * DIM], hes[4];
};
using dbl_range_t = gslib::dbl_range_t;
using obbox_t = gslib::obbox_t<DIM>;
using findptsLocalHashData_t = gslib::findptsLocalHashData_t<DIM>;
using gslib::bbox_test;
using gslib::hash_index;
using gslib::l2norm2;
using gslib::lag_eval_first_der;
using gslib::lag_eval_second_der;
struct dbl_range_t
{
double min, max;
};
struct obbox_t
{
double c0[DIM], A[DIM * DIM];
dbl_range_t x[DIM];
};
struct findptsLocalHashData_t
{
int hash_n;
dbl_range_t bnd[DIM];
double fac[DIM];
unsigned int *offset;
int max;
};
// Eval the ith Lagrange interpolant and its first derivative at x.
// Note: lCoeff stores pre-computed coefficients for fast evaluation.
static MFEM_HOST_DEVICE inline void lag_eval_first_der(double *p0, double x,
int i, const double *z,
const double *lCoeff,
int pN)
{
double u0 = 1, u1 = 0;
for (int j = 0; j < pN; ++j)
{
if (i != j)
{
double d_j = 2 * (x - z[j]);
u1 = d_j * u1 + u0;
u0 = d_j * u0;
}
}
p0[i] = lCoeff[i] * u0;
p0[pN+i] = 2.0 * lCoeff[i] * u1;
}
// Eval the ith Lagrange interpolant and its first and second derivative at x.
// Note: lCoeff stores pre-computed coefficients for fast evaluation.
static MFEM_HOST_DEVICE inline void lag_eval_second_der(double *p0, double x,
int i, const double *z,
const double *lCoeff,
int pN)
{
double u0 = 1, u1 = 0, u2 = 0;
for (int j = 0; j < pN; ++j)
{
if (i != j)
{
double d_j = 2 * (x - z[j]);
u2 = d_j * u2 + u1;
u1 = d_j * u1 + u0;
u0 = d_j * u0;
}
}
p0[i] = lCoeff[i] * u0;
p0[pN+i] = 2.0 * lCoeff[i] * u1;
p0[2*pN+i] = 8.0 * lCoeff[i] * u2;
}
// Axis-aligned bounding box test.
static MFEM_HOST_DEVICE inline double AABB_test(const obbox_t *const b,
const double x[2])
{
double test = 1;
for (int d = 0; d < 2; ++d)
{
double b_d = (x[d] - b->x[d].min) * (b->x[d].max - x[d]);
test = test < 0 ? test : b_d;
}
return test;
}
// Axis-aligned bounding box test followed by oriented bounding-box test.
static MFEM_HOST_DEVICE inline double bbox_test(const obbox_t *const b,
const double x[2])
{
const double bxyz = AABB_test(b, x);
if (bxyz < 0)
{
return bxyz;
}
else
{
double dxyz[2];
for (int d = 0; d < 2; ++d)
{
dxyz[d] = x[d] - b->c0[d];
}
double test = 1;
for (int d = 0; d < 2; ++d)
{
double rst = 0;
for (int e = 0; e < 2; ++e)
{
rst += b->A[d * 2 + e] * dxyz[e];
}
double brst = (rst + 1) * (1 - rst);
test = test < 0 ? test : brst;
}
return test;
}
}
// Element index corresponding to hash mesh that the point is located in.
static MFEM_HOST_DEVICE inline int hash_index(const findptsLocalHashData_t *p,
const double x[2])
{
const int n = p->hash_n;
int sum = 0;
for (int d = 2 - 1; d >= 0; --d)
{
sum *= n;
int i = (int)floor((x[d] - p->bnd[d].min) * p->fac[d]);
sum += i < 0 ? 0 : (n - 1 < i ? n - 1 : i);
}
return sum;
}
/*Solve Ax=y. A is row-major */
static MFEM_HOST_DEVICE inline void lin_solve_2(double x[2], const double A[4],
@@ -70,6 +185,12 @@ static MFEM_HOST_DEVICE inline void lin_solve_2(double x[2], const double A[4],
x[1] = idet*(A[0]*y[1] - A[2]*y[0]);
}
/* L2 norm squared. */
static MFEM_HOST_DEVICE inline double l2norm2(const double x[2])
{
return x[0] * x[0] + x[1] * x[1];
}
/* the bit structure of flags is CSSRR
the C bit --- 1<<4 --- is set when the point is converged
RR is 0 = 00b if r is unconstrained,
@@ -231,7 +352,7 @@ static MFEM_HOST_DEVICE bool reject_prior_step_q(findptsElementPoint_t *res,
const findptsElementPoint_t *p,
const double tol)
{
const double dist2 = l2norm2<2>(resid);
const double dist2 = l2norm2(resid);
const double decr = p->dist2 - dist2;
const double pred = p->dist2p;
for (int d = 0; d < 2; ++d)
@@ -574,25 +695,25 @@ static MFEM_HOST_DEVICE double tensor_ig2_j(double *g_partials,
}
template<int T_D1D = 0>
static void FindPointsLocal2DKernel(const int npt,
const double tol,
const double *x,
const int point_pos_ordering,
const double *xElemCoord,
const int nel,
const double *wtend,
const double *boxinfo,
const int hash_n,
const double *hashMin,
const double *hashFac,
unsigned int *hashOffset,
unsigned int *const code_base,
unsigned int *const el_base,
double *const r_base,
double *const dist2_base,
const double *gll1D,
const double *lagcoeff,
const int pN = 0)
static void FindPointsLocal2D_Kernel(const int npt,
const double tol,
const double *x,
const int point_pos_ordering,
const double *xElemCoord,
const int nel,
const double *wtend,
const double *boxinfo,
const int hash_n,
const double *hashMin,
const double *hashFac,
unsigned int *hashOffset,
unsigned int *const code_base,
unsigned int *const el_base,
double *const r_base,
double *const dist2_base,
const double *gll1D,
const double *lagcoeff,
const int pN = 0)
{
const int MD1 = T_D1D ? T_D1D : DofQuadLimits::MAX_D1D;
const int D1D = T_D1D ? T_D1D : pN;
@@ -1054,45 +1175,30 @@ void FindPointsGSLIB::FindPointsLocal2(const Vector &point_pos,
switch (DEV.dof1d)
{
case 2:
FindPointsLocal2DKernel<2>(npt, DEV.newt_tol, pp,
point_pos_ordering, pgslm,
NE_split_total, pwt, pbb,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc);
break;
return FindPointsLocal2D_Kernel<2>(
npt, DEV.newt_tol, pp, point_pos_ordering, pgslm, NE_split_total, pwt,
pbb, DEV.lh_nx, plhm, plhf, plho, pcode, pelem, pref, pdist,
pgll1d, plc);
case 3:
FindPointsLocal2DKernel<3>(npt, DEV.newt_tol, pp,
point_pos_ordering, pgslm,
NE_split_total, pwt, pbb,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc);
break;
return FindPointsLocal2D_Kernel<3>(
npt, DEV.newt_tol, pp, point_pos_ordering, pgslm, NE_split_total, pwt,
pbb, DEV.lh_nx, plhm, plhf, plho, pcode, pelem, pref, pdist,
pgll1d, plc);
case 4:
FindPointsLocal2DKernel<4>(npt, DEV.newt_tol, pp,
point_pos_ordering, pgslm,
NE_split_total, pwt, pbb,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc);
break;
return FindPointsLocal2D_Kernel<4>(
npt, DEV.newt_tol, pp, point_pos_ordering, pgslm, NE_split_total, pwt,
pbb, DEV.lh_nx, plhm, plhf, plho, pcode, pelem, pref, pdist,
pgll1d, plc);
case 5:
FindPointsLocal2DKernel<5>(npt, DEV.newt_tol, pp,
point_pos_ordering, pgslm,
NE_split_total, pwt, pbb,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc);
break;
return FindPointsLocal2D_Kernel<5>(
npt, DEV.newt_tol, pp, point_pos_ordering, pgslm, NE_split_total, pwt,
pbb, DEV.lh_nx, plhm, plhf, plho, pcode, pelem, pref, pdist,
pgll1d, plc);
default:
FindPointsLocal2DKernel(npt, DEV.newt_tol, pp,
point_pos_ordering, pgslm,
NE_split_total, pwt, pbb,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc, DEV.dof1d);
break;
return FindPointsLocal2D_Kernel(npt, DEV.newt_tol, pp, point_pos_ordering,
pgslm, NE_split_total, pwt, pbb, DEV.lh_nx,
plhm, plhf, plho, pcode, pelem,
pref, pdist, pgll1d, plc, DEV.dof1d);
}
}
#undef DIM2
+157 -29
View File
@@ -11,7 +11,9 @@
#include "../gslib.hpp"
#include "../../general/forall.hpp"
#include "gslib_kernel_helpers.hpp"
#include "../../linalg/kernels.hpp"
#include <climits>
#ifdef MFEM_USE_GSLIB
@@ -57,15 +59,128 @@ struct findptsElemPt
double x[DIM], jac[DIM * DIM], hes[18];
};
using dbl_range_t = gslib::dbl_range_t;
using obbox_t = gslib::obbox_t<DIM>;
using findptsLocalHashData_t = gslib::findptsLocalHashData_t<DIM>;
using gslib::bbox_test;
using gslib::hash_index;
using gslib::l2norm2;
using gslib::lag_eval_first_der;
using gslib::lag_eval_second_der;
using gslib::lin_solve_sym_2;
struct dbl_range_t
{
double min, max;
};
struct obbox_t
{
double c0[DIM], A[DIM * DIM];
dbl_range_t x[DIM];
};
struct findptsLocalHashData_t
{
int hash_n;
dbl_range_t bnd[DIM];
double fac[DIM];
unsigned int *offset;
// int max;
};
// Eval the ith Lagrange interpolant and its first derivative at x.
// Note: lCoeff stores pre-computed coefficients for fast evaluation.
static MFEM_HOST_DEVICE inline void lag_eval_first_der(double *p0, double x,
int i, const double *z,
const double *lCoeff,
int pN)
{
double u0 = 1, u1 = 0;
for (int j = 0; j < pN; ++j)
{
if (i != j)
{
double d_j = 2*(x-z[j]);
u1 = d_j*u1+u0;
u0 = d_j*u0;
}
}
p0[i] = lCoeff[i]*u0;
p0[pN+i] = 2.0*lCoeff[i]*u1;
}
// Eval the ith Lagrange interpolant and its first and second derivative at x.
// Note: lCoeff stores pre-computed coefficients for fast evaluation.
static MFEM_HOST_DEVICE inline void lag_eval_second_der(double *p0, double x,
int i, const double *z,
const double *lCoeff,
int pN)
{
double u0 = 1, u1 = 0, u2 = 0;
for (int j = 0; j < pN; ++j)
{
if (i != j)
{
double d_j = 2*(x-z[j]);
u2 = d_j*u2+u1;
u1 = d_j*u1+u0;
u0 = d_j*u0;
}
}
p0[i] = lCoeff[i]*u0;
p0[pN+i] = 2.0*lCoeff[i]*u1;
p0[2*pN+i] = 8.0*lCoeff[i]*u2;
}
// Axis-aligned bounding box test.
static MFEM_HOST_DEVICE inline double AABB_test(const obbox_t *const b,
const double x[3])
{
double b_d;
for (int d = 0; d < 3; ++d)
{
b_d = (x[d]-b->x[d].min)*(b->x[d].max-x[d]);
if (b_d < 0) { return b_d; }
}
return b_d;
}
// Axis-aligned bounding box test followed by oriented bounding-box test.
static MFEM_HOST_DEVICE inline double bbox_test(const obbox_t *const b,
const double x[3])
{
const double bxyz = AABB_test(b, x);
if (bxyz < 0)
{
return bxyz;
}
else
{
double dxyz[3];
for (int d = 0; d < 3; ++d)
{
dxyz[d] = x[d]-b->c0[d];
}
double test = 1;
for (int d = 0; d < 3; ++d)
{
double rst = 0;
for (int e = 0; e < 3; ++e)
{
rst += b->A[d*3+e]*dxyz[e];
}
double brst = (rst+1)*(1-rst);
test = test < 0 ? test : brst;
}
return test;
}
}
// Element index corresponding to hash mesh that the point is located in.
static MFEM_HOST_DEVICE inline int hash_index(const findptsLocalHashData_t *p,
const double x[3])
{
const int n = p->hash_n;
int sum = 0;
for (int d = 3-1; d >= 0; --d)
{
sum *= n;
int i = (int)floor((x[d]-p->bnd[d].min)*p->fac[d]);
sum += i < 0 ? 0 : (n-1 < i ? n-1 : i);
}
return sum;
}
// Solve Ax=y. A is row-major.
static MFEM_HOST_DEVICE inline void lin_solve_3(double x[3], const double A[9],
@@ -84,6 +199,22 @@ static MFEM_HOST_DEVICE inline void lin_solve_3(double x[3], const double A[9],
x[2] = idet*(inv6*y[0]+inv7*y[1]+inv8*y[2]);
}
// Solve Ax=y. A is a symmetric 2x2 matrix.
static MFEM_HOST_DEVICE inline void lin_solve_sym_2(double x[2],
const double A[3],
const double y[2])
{
const double idet = 1 / (A[0]*A[2]-A[1]*A[1]);
x[0] = idet*(A[2]*y[0]-A[1]*y[1]);
x[1] = idet*(A[0]*y[1]-A[1]*y[0]);
}
// L2 norm.
static MFEM_HOST_DEVICE inline double l2norm2(const double x[3])
{
return x[0]*x[0]+x[1]*x[1]+x[2]*x[2];
}
/* the bit structure of flags is CTTSSRR
the C bit --- 1<<6 --- is set when the point is converged
RR is 0 = 00b if r is unconstrained,
@@ -328,7 +459,7 @@ static MFEM_HOST_DEVICE bool reject_prior_step_q(findptsPt *res,
const findptsPt *p,
const double tol)
{
const double dist2 = l2norm2<3>(resid);
const double dist2 = l2norm2(resid);
const double decr = p->dist2-dist2;
const double pred = p->dist2p;
for (int d = 0; d < 3; ++d)
@@ -1678,36 +1809,33 @@ void FindPointsGSLIB::FindPointsLocal3(const Vector &point_pos,
{
case 2:
FindPointsLocal3DKernel<2>(npt, DEV.newt_tol, pp, point_pos_ordering,
pgslm, NE_split_total, pwt, pbb,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist, pgll1d, plc);
pgslm, NE_split_total, pwt, pbb, DEV.lh_nx, plhm,
plhf, plho, pcode, pelem, pref, pdist, pgll1d,
plc);
break;
case 3:
FindPointsLocal3DKernel<3>(npt, DEV.newt_tol, pp, point_pos_ordering,
pgslm, NE_split_total, pwt, pbb,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist, pgll1d, plc);
pgslm, NE_split_total, pwt, pbb, DEV.lh_nx, plhm,
plhf, plho, pcode, pelem, pref, pdist, pgll1d,
plc);
break;
case 4:
FindPointsLocal3DKernel<4>(npt, DEV.newt_tol, pp, point_pos_ordering,
pgslm, NE_split_total, pwt, pbb,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist, pgll1d, plc);
pgslm, NE_split_total, pwt, pbb, DEV.lh_nx, plhm,
plhf, plho, pcode, pelem, pref, pdist, pgll1d,
plc);
break;
case 5:
FindPointsLocal3DKernel<5>(npt, DEV.newt_tol, pp, point_pos_ordering,
pgslm, NE_split_total, pwt, pbb,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist, pgll1d, plc);
pgslm, NE_split_total, pwt, pbb, DEV.lh_nx, plhm,
plhf, plho, pcode, pelem, pref, pdist, pgll1d,
plc);
break;
default:
FindPointsLocal3DKernel(npt, DEV.newt_tol, pp,
point_pos_ordering, pgslm,
NE_split_total, pwt, pbb,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist, pgll1d, plc,
FindPointsLocal3DKernel(npt, DEV.newt_tol, pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, DEV.lh_nx, plhm, plhf,
plho, pcode, pelem, pref, pdist, pgll1d, plc,
DEV.dof1d);
break;
}
}
#undef pMax
+176 -107
View File
@@ -11,7 +11,6 @@
#include "../gslib.hpp"
#include "../../general/forall.hpp"
#include "gslib_kernel_helpers.hpp"
#ifdef MFEM_USE_GSLIB
@@ -53,14 +52,113 @@ struct findptsElementGPT_t
double x[sDIM], jac[sDIM*rDIM], hes[sDIM*rDIM];
};
using dbl_range_t = gslib::dbl_range_t;
using obbox_t = gslib::obbox_t<sDIM>;
using findptsLocalHashData_t = gslib::findptsLocalHashData_t<sDIM>;
using gslib::AABB_test;
using gslib::bbox_test;
using gslib::hash_index;
using gslib::l2norm2;
using gslib::lag_eval_second_der;
struct dbl_range_t
{
double min, max;
};
struct obbox_t
{
double c0[sDIM], A[sDIM*sDIM];
dbl_range_t x[sDIM];
};
struct findptsLocalHashData_t
{
int hash_n;
dbl_range_t bnd[sDIM];
double fac[sDIM];
unsigned int *offset;
};
static MFEM_HOST_DEVICE inline void lag_eval_second_der(double *p0, double x,
int i, const double *z,
const double *lCoeff,
int pN)
{
double u0 = 1, u1 = 0, u2 = 0;
for (int j = 0; j < pN; ++j)
{
if (i != j)
{
double d_j = 2 * (x-z[j]);
u2 = d_j * u2 + u1;
u1 = d_j * u1 + u0;
u0 = d_j * u0;
}
}
double *p1 = p0 + pN, *p2 = p0 + 2 * pN;
p0[i] = lCoeff[i] * u0;
p1[i] = 2.0 * lCoeff[i] * u1;
p2[i] = 8.0 * lCoeff[i] * u2;
}
/* positive when possibly inside */
static MFEM_HOST_DEVICE inline double obbox_axis_test(const obbox_t *const b,
const double x[sDIM])
{
double b_d;
for (int d=0; d<sDIM; ++d)
{
b_d = (x[d] - b->x[d].min) * (b->x[d].max - x[d]);
if (b_d < 0) // if outside in any dimension
{
return b_d;
}
}
return b_d; // only positive if inside
}
/* positive when given point is possibly inside given obbox b */
static MFEM_HOST_DEVICE inline double obbox_test(const obbox_t *const b,
const double x[sDIM])
{
const double bxyz = obbox_axis_test(b,x);
if (bxyz<0) // test if point is in AABB
{
return bxyz;
}
else // test OBB only if inside AABB
{
double dxyz[sDIM];
for (int d=0; d<sDIM; ++d)
{
dxyz[d] = x[d] - b->c0[d];
}
double test = 1;
for (int d=0; d<sDIM; ++d)
{
double rst = 0;
for (int e=0; e<sDIM; ++e)
{
rst += b->A[d*2 + e] * dxyz[e];
}
double brst = (rst+1)*(1-rst);
test = test<0 ? test : brst;
}
return test;
}
}
/* Hash index in the hash table to the elements that possibly contain the point x */
static MFEM_HOST_DEVICE inline int hash_index(const findptsLocalHashData_t *p,
const double x[2])
{
const int n = p->hash_n;
int sum = 0;
for (int d=sDIM-1; d>=0; --d)
{
sum *= n;
int i = (int)floor((x[d] - p->bnd[d].min) * p->fac[d]);
sum += i<0 ? 0 : (n-1 < i ? n-1 : i);
}
return sum;
}
static MFEM_HOST_DEVICE inline double l2norm2(const double x[2])
{
return x[0] * x[0] + x[1] * x[1];
}
/* the bit structure of flags is CRR
the C bit --- 1<<2 --- is set when the point is converged
@@ -89,29 +187,29 @@ static MFEM_HOST_DEVICE inline int point_index(const int x)
/* check reduction in objective against prediction, and adjust
trust region radius (p->tr) accordingly;
may reject the prior step, returning 1; otherwise returns 0
sets out_pt->dist2, out_pt->index, out_pt->x, out_pt->oldr in any event,
leaving out_pt->r, out_pt->dr, out_pt->flags to be set when returning 0 */
static MFEM_HOST_DEVICE bool reject_prior_step_q(findptsElementPoint_t *out_pt,
sets out->dist2, out->index, out->x, out->oldr in any event,
leaving out->r, out->dr, out->flags to be set when returning 0 */
static MFEM_HOST_DEVICE bool reject_prior_step_q(findptsElementPoint_t *out,
const double resid[2],
const findptsElementPoint_t *p,
const double tol)
{
const double dist2 = l2norm2<2>(resid);
const double dist2 = l2norm2(resid);
const double decr = p->dist2 - dist2;
const double pred = p->dist2p;
out_pt->x[0] = p->x[0];
out_pt->x[1] = p->x[1];
out_pt->oldr = p->r;
out_pt->dist2 = dist2;
out->x[0] = p->x[0];
out->x[1] = p->x[1];
out->oldr = p->r;
out->dist2 = dist2;
if (decr >= 0.01*pred)
{
if (decr >= 0.9*pred) // very good iteration
{
out_pt->tr = p->tr*2;
out->tr = p->tr*2;
}
else // somewhat good iteration
{
out_pt->tr = p->tr;
out->tr = p->tr;
}
return false;
}
@@ -122,21 +220,21 @@ static MFEM_HOST_DEVICE bool reject_prior_step_q(findptsElementPoint_t *out_pt,
"very good iteration" --- this doubles the trust radius,
which is why we divide by 4 below */
double v0 = fabs(p->r - p->oldr);
out_pt->tr = v0/4.0;
out_pt->dist2 = p->dist2;
out_pt->r = p->oldr;
out_pt->flags = p->flags>>3;
out_pt->dist2p = -HUGE_VAL;
out->tr = v0/4.0;
out->dist2 = p->dist2;
out->r = p->oldr;
out->flags = p->flags>>3;
out->dist2p = -HUGE_VAL;
if (pred < dist2*tol)
{
out_pt->flags |= CONVERGED_FLAG;
out->flags |= CONVERGED_FLAG;
}
return true;
}
}
static MFEM_HOST_DEVICE inline void newton_edge( findptsElementPoint_t *const
out_pt,
out,
const double jac[2],
const double rhess,
const double resid[2],
@@ -206,9 +304,9 @@ newton_edge_fin:
{
new_flags |= CONVERGED_FLAG;
}
out_pt->r = newr;
out_pt->dist2p = -v;
out_pt->flags = flags | new_flags | ((p->flags & FLAG_MASK)<<3);
out->r = newr;
out->dist2p = -v;
out->flags = flags | new_flags | ((p->flags & FLAG_MASK)<<3);
}
static MFEM_HOST_DEVICE void seed_j( const double *elx[sDIM],
@@ -234,27 +332,26 @@ static MFEM_HOST_DEVICE void seed_j( const double *elx[sDIM],
}
template<int T_D1D = 0>
static void FindPointsEdgeLocal2DKernel( const int npt,
const double tol,
const double dist2tol,
const double *x,
const int point_pos_ordering,
const double *xElemCoord,
const int nel,
const double *wtend,
const double *boxinfo,
const bool obb_check,
const int hash_n,
const double *hashMin,
const double *hashFac,
unsigned int *hashOffset,
unsigned int *const code_base,
unsigned int *const el_base,
double *const r_base,
double *const dist2_base,
const double *gll1D,
const double *lagcoeff,
const int pN = 0 )
static void FindPointsEdgeLocal2D_Kernel( const int npt,
const double tol,
const double dist2tol,
const double *x,
const int point_pos_ordering,
const double *xElemCoord,
const int nel,
const double *wtend,
const double *boxinfo,
const int hash_n,
const double *hashMin,
const double *hashFac,
unsigned int *hashOffset,
unsigned int *const code_base,
unsigned int *const el_base,
double *const r_base,
double *const dist2_base,
const double *gll1D,
const double *lagcoeff,
const int pN = 0 )
{
const int MD1 = T_D1D ? T_D1D : DofQuadLimits::MAX_D1D;
const int D1D = T_D1D ? T_D1D : pN;
@@ -315,34 +412,22 @@ static void FindPointsEdgeLocal2DKernel( const int npt,
{
const unsigned int el = *elp;
const int n_box_ents = obb_check ? (3*sDIM + sDIM2) : (2*sDIM);
bool pass_bb = true;
obbox_t box;
if (obb_check)
int n_box_ents = 3*sDIM + sDIM2;
for (int idx = 0; idx < sDIM; ++idx)
{
for (int idx = 0; idx < sDIM; ++idx)
{
box.c0[idx] = boxinfo[n_box_ents*el + idx];
box.x[idx].min = boxinfo[n_box_ents*el + sDIM + idx];
box.x[idx].max = boxinfo[n_box_ents*el + 2*sDIM + idx];
}
for (int idx = 0; idx < sDIM2; ++idx)
{
box.A[idx] = boxinfo[n_box_ents*el + 3*sDIM + idx];
}
pass_bb = (bbox_test(&box, x_i) >= 0);
}
else
{
for (int d = 0; d < sDIM; ++d)
{
box.x[d].min = boxinfo[n_box_ents*el + d];
box.x[d].max = boxinfo[n_box_ents*el + sDIM + d];
}
pass_bb = (AABB_test(&box, x_i) >= 0);
box.c0[idx] = boxinfo[n_box_ents*el + idx];
box.x[idx].min = boxinfo[n_box_ents*el + sDIM + idx];
box.x[idx].max = boxinfo[n_box_ents*el + 2*sDIM + idx];
}
if (pass_bb)
for (int idx = 0; idx < sDIM2; ++idx)
{
box.A[idx] = boxinfo[n_box_ents*el + 3*sDIM + idx];
}
if (obbox_test(&box,x_i)>=0)
{
//------------ findpts_local ------------------
{
@@ -431,14 +516,11 @@ static void FindPointsEdgeLocal2DKernel( const int npt,
double *hess = jac + sDIM*rDIM;
findptsElementGEdge_t edge;
for (int d=0; d<sDIM; ++d)
{
edge.x[d] = constraint_workspace + d*D1D;
}
MFEM_FOREACH_THREAD(j,x,D1D)
{
for (int d=0; d<sDIM; ++d)
{
edge.x[d] = constraint_workspace + d*D1D;
edge.x[d][j] = elx[d][j];
}
}
@@ -599,41 +681,28 @@ void FindPointsGSLIB::FindPointsEdgeLocal2( const Vector &point_pos,
auto pgll1d = DEV.gll1d.ReadWrite(use_dev);
auto plc = DEV.lagcoeff.Read(use_dev);
double dist2tol = DEV.surf_dist_tol;
const bool obb_chk = obb_check;
switch (DEV.dof1d)
{
case 2:
FindPointsEdgeLocal2DKernel<2>(npt, DEV.newt_tol, dist2tol,
pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, obb_chk,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc);
break;
return FindPointsEdgeLocal2D_Kernel<2>(
npt, DEV.newt_tol, dist2tol, pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, DEV.lh_nx, plhm, plhf,
plho, pcode, pelem, pref, pdist, pgll1d, plc);
case 3:
FindPointsEdgeLocal2DKernel<3>(npt, DEV.newt_tol, dist2tol,
pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, obb_chk,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc);
break;
return FindPointsEdgeLocal2D_Kernel<3>(
npt, DEV.newt_tol, dist2tol, pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, DEV.lh_nx, plhm, plhf,
plho, pcode, pelem, pref, pdist, pgll1d, plc);
case 4:
FindPointsEdgeLocal2DKernel<4>(npt, DEV.newt_tol, dist2tol,
pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, obb_chk,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc);
break;
return FindPointsEdgeLocal2D_Kernel<4>(
npt, DEV.newt_tol, dist2tol, pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, DEV.lh_nx, plhm, plhf,
plho, pcode, pelem, pref, pdist, pgll1d, plc);
default:
FindPointsEdgeLocal2DKernel(npt, DEV.newt_tol, dist2tol, pp,
point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, obb_chk,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc, DEV.dof1d);
break;
return FindPointsEdgeLocal2D_Kernel(
npt, DEV.newt_tol, dist2tol, pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, DEV.lh_nx, plhm, plhf,
plho, pcode, pelem, pref, pdist, pgll1d, plc, DEV.dof1d);
}
}
#undef sDIM
+181 -109
View File
@@ -11,7 +11,6 @@
#include "../gslib.hpp"
#include "../../general/forall.hpp"
#include "gslib_kernel_helpers.hpp"
#ifdef MFEM_USE_GSLIB
@@ -55,14 +54,117 @@ struct findptsElementGPT_t
double x[sDIM], jac[sDIM], hes[sDIM*(1+1)];
};
using dbl_range_t = gslib::dbl_range_t;
using obbox_t = gslib::obbox_t<sDIM>;
using findptsLocalHashData_t = gslib::findptsLocalHashData_t<sDIM>;
using gslib::AABB_test;
using gslib::bbox_test;
using gslib::hash_index;
using gslib::l2norm2;
using gslib::lag_eval_second_der;
struct dbl_range_t
{
double min, max;
};
struct obbox_t
{
double c0[sDIM], A[sDIM*sDIM];
dbl_range_t x[sDIM];
};
struct findptsLocalHashData_t
{
int hash_n;
dbl_range_t bnd[sDIM];
double fac[sDIM];
unsigned int *offset;
};
static MFEM_HOST_DEVICE inline void lag_eval_second_der(double *p0, double x,
int i, const double *z,
const double *lCoeff,
int pN)
{
double u0 = 1, u1 = 0, u2 = 0;
for (int j=0; j<pN; ++j)
{
if (i!=j)
{
double d_j = 2 * (x-z[j]);
u2 = d_j * u2 + u1;
u1 = d_j * u1 + u0;
u0 = d_j * u0;
}
}
double *p1 = p0 + pN, *p2 = p0 + 2 * pN;
p0[i] = lCoeff[i] * u0;
p1[i] = 2.0 * lCoeff[i] * u1;
p2[i] = 8.0 * lCoeff[i] * u2;
}
/* positive when possibly inside */
static MFEM_HOST_DEVICE inline double obbox_axis_test(const obbox_t *const b,
const double x[sDIM])
{
double b_d;
for (int d=0; d<sDIM; ++d)
{
b_d = (x[d] - b->x[d].min) * (b->x[d].max - x[d]);
if (b_d < 0) // if outside in any dimension
{
return b_d;
}
}
return b_d; // only positive if inside in all dimensions
}
/* positive when possibly inside */
static MFEM_HOST_DEVICE inline double obbox_test(const obbox_t *const b,
const double x[sDIM])
{
const double bxyz = obbox_axis_test(b, x);
if (bxyz<0)
{
return bxyz;
}
else
{
double dxyz[3];
// dxyz: distance of the point from the center of the OBB
for (int d=0; d<sDIM; ++d)
{
dxyz[d] = x[d] - b->c0[d];
}
// transform dxyz to the local coordinate system of the OBB,
// and check if the point is inside the OBB [-1,1]^sDIM
double test = 1;
for (int d=0; d<sDIM; ++d)
{
double rst = 0;
for (int e=0; e<sDIM; ++e)
{
rst += b->A[d*sDIM + e] * dxyz[e];
}
double brst = (rst+1)*(1-rst);
test = test<0 ? test : brst;
}
return test;
}
}
/* Hash index in the hash table to the elements that possibly contain the point x */
static MFEM_HOST_DEVICE inline int hash_index(const findptsLocalHashData_t *p,
const double x[sDIM])
{
const int n = p->hash_n;
int sum = 0;
for (int d=sDIM-1; d>=0; --d)
{
sum *= n;
int i = (int)floor((x[d] - p->bnd[d].min) * p->fac[d]);
sum += i<0 ? 0 : (n-1 < i ? n-1 : i);
}
return sum;
}
static MFEM_HOST_DEVICE inline double norm2(const double x[sDIM])
{
return ( x[0]*x[0] + x[1]*x[1] + x[2]*x[2] );
}
/* the bit structure of flags is CRR
the C bit --- 1<<2 --- is set when the point is converged
@@ -73,46 +175,47 @@ using gslib::lag_eval_second_der;
#define CONVERGED_FLAG (1u<<2)
#define FLAG_MASK 0x07u
/* returns the number of constrained reference coordinates, max 1
/* returns the number of constrained reference coordinates, max 2
*/
static MFEM_HOST_DEVICE inline int num_constrained(const int flags)
{
return ((flags | flags>>1) & 1u);
const int y = (flags | flags>>1);
return (y & 1u) + (y>>2 & 1u);
}
static MFEM_HOST_DEVICE inline int point_index(const int x)
{
return ((x>>1)&1u);
return ((x>>1)&1u) | ((x>>2)&2u);
}
/* check reduction in objective against prediction, and adjust
trust region radius (p->tr) accordingly;
may reject the prior step, returning 1; otherwise returns 0
sets out_pt->dist2, out_pt->index, out_pt->x, out_pt->oldr in any event,
leaving out_pt->r, out_pt->dr, out_pt->flags to be set when returning 0 */
static MFEM_HOST_DEVICE bool reject_prior_step_q(findptsElementPoint_t *out_pt,
sets out->dist2, out->index, out->x, out->oldr in any event,
leaving out->r, out->dr, out->flags to be set when returning 0 */
static MFEM_HOST_DEVICE bool reject_prior_step_q(findptsElementPoint_t *out,
const double resid[3],
const findptsElementPoint_t *p,
const double tol)
{
const double dist2 = l2norm2<sDIM>(resid);
const double dist2 = norm2(resid);
const double decr = p->dist2 - dist2;
const double pred = p->dist2p;
for (int d=0; d<sDIM; ++d)
{
out_pt->x[d] = p->x[d];
out->x[d] = p->x[d];
}
out_pt->oldr = p->r;
out_pt->dist2 = dist2;
out->oldr = p->r;
out->dist2 = dist2;
if (decr>=0.01*pred)
{
if (decr>=0.9*pred) // very good iteration
{
out_pt->tr = 2*p->tr;
out->tr = 2*p->tr;
}
else // good iteration
{
out_pt->tr = p->tr;
out->tr = p->tr;
}
return false;
}
@@ -123,21 +226,21 @@ static MFEM_HOST_DEVICE bool reject_prior_step_q(findptsElementPoint_t *out_pt,
"very good iteration" --- this doubles the trust radius,
which is why we divide by 4 below */
double v0 = fabs(p->r - p->oldr);
out_pt->tr = v0/4.0;
out_pt->dist2 = p->dist2;
out_pt->r = p->oldr;
out_pt->flags = p->flags>>3;
out_pt->dist2p = -HUGE_VAL;
out->tr = v0/4.0;
out->dist2 = p->dist2;
out->r = p->oldr;
out->flags = p->flags>>3;
out->dist2p = -HUGE_VAL;
if (pred<dist2*tol)
{
out_pt->flags |= CONVERGED_FLAG;
out->flags |= CONVERGED_FLAG;
}
return true;
}
}
static MFEM_HOST_DEVICE inline void newton_edge(findptsElementPoint_t *const
out_pt,
out,
const double jac[sDIM*rDIM],
const double rhes,
const double resid[sDIM],
@@ -211,9 +314,9 @@ newton_edge_fin:
{
new_flags |= CONVERGED_FLAG;
}
out_pt->r = nr;
out_pt->dist2p = -v;
out_pt->flags = flags | new_flags | ((p->flags & FLAG_MASK)<<3);
out->r = nr;
out->dist2p = -v;
out->flags = flags | new_flags | ((p->flags & FLAG_MASK)<<3);
#undef EVAL
}
@@ -235,32 +338,31 @@ static MFEM_HOST_DEVICE void seed_j(const double *elx[sDIM],
{
dx[d] = x[d] - elx[d][ir];
}
dist2[ir] = l2norm2(dx);
dist2[ir] = norm2(dx);;
r[ir] = z[ir];
}
template<int T_D1D = 0>
static void FindPointsEdgeLocal3DKernel(const int npt,
const double tol,
const double dist2tol,
const double *x,
const int point_pos_ordering,
const double *xElemCoord,
const int nel,
const double *wtend,
const double *boxinfo,
const bool obb_check,
const int hash_n,
const double *hashMin,
const double *hashFac,
unsigned int *hashOffset,
unsigned int *const code_base,
unsigned int *const el_base,
double *const r_base,
double *const dist2_base,
const double *gll1D,
const double *lagcoeff,
const int pN = 0)
static void FindPointsEdgeLocal3D_Kernel(const int npt,
const double tol,
const double dist2tol,
const double *x,
const int point_pos_ordering,
const double *xElemCoord,
const int nel,
const double *wtend,
const double *boxinfo,
const int hash_n,
const double *hashMin,
const double *hashFac,
unsigned int *hashOffset,
unsigned int *const code_base,
unsigned int *const el_base,
double *const r_base,
double *const dist2_base,
const double *gll1D,
const double *lagcoeff,
const int pN = 0)
{
const int MD1 = T_D1D ? T_D1D : DofQuadLimits::MAX_D1D;
const int D1D = T_D1D ? T_D1D : pN;
@@ -317,35 +419,21 @@ static void FindPointsEdgeLocal3DKernel(const int npt,
for (; elp!=ele; ++elp)
{
const unsigned int el = *elp;
const int n_box_ents = obb_check ? (3*sDIM + sDIM2) : (2*sDIM);
bool pass_bb = true;
obbox_t box;
if (obb_check)
int n_box_ents = 3*sDIM + sDIM2;
for (int idx = 0; idx < sDIM; ++idx)
{
for (int idx = 0; idx < sDIM; ++idx)
{
box.c0[idx] = boxinfo[n_box_ents*el + idx];
box.x[idx].min = boxinfo[n_box_ents*el + sDIM + idx];
box.x[idx].max = boxinfo[n_box_ents*el + 2*sDIM + idx];
}
for (int idx = 0; idx < sDIM2; ++idx)
{
box.A[idx] = boxinfo[n_box_ents*el + 3*sDIM + idx];
}
pass_bb = (bbox_test(&box, x_i) >= 0);
box.c0[idx] = boxinfo[n_box_ents*el + idx];
box.x[idx].min = boxinfo[n_box_ents*el + sDIM + idx];
box.x[idx].max = boxinfo[n_box_ents*el + 2*sDIM + idx];
}
else
for (int idx = 0; idx < sDIM2; ++idx)
{
for (int d = 0; d < sDIM; ++d)
{
box.x[d].min = boxinfo[n_box_ents*el + d];
box.x[d].max = boxinfo[n_box_ents*el + sDIM + d];
}
pass_bb = (AABB_test(&box, x_i) >= 0);
box.A[idx] = boxinfo[n_box_ents*el + 3*sDIM + idx];
}
if (pass_bb)
if (obbox_test(&box, x_i)>=0)
{
//// findpts_local ////
{
@@ -433,14 +521,11 @@ static void FindPointsEdgeLocal3DKernel(const int npt,
double *hess = jac + sDIM*rDIM;
findptsElementGEdge_t edge;
for (int d=0; d<sDIM; ++d)
{
edge.x[d] = constraint_workspace + d*D1D;
}
MFEM_FOREACH_THREAD(j,x,D1D)
{
for (int d=0; d<sDIM; ++d)
{
edge.x[d] = constraint_workspace + d*D1D;
edge.x[d][j] = elx[d][j];
}
}
@@ -603,41 +688,28 @@ void FindPointsGSLIB::FindPointsEdgeLocal3(const Vector &point_pos,
auto pgll1d = DEV.gll1d.ReadWrite(use_dev);
auto plc = DEV.lagcoeff.Read(use_dev);
double dist2tol = DEV.surf_dist_tol;
const bool obb_chk = obb_check;
switch (DEV.dof1d)
{
case 2:
FindPointsEdgeLocal3DKernel<2>(npt, DEV.newt_tol, dist2tol,
pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, obb_chk,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc);
break;
return FindPointsEdgeLocal3D_Kernel<2>(
npt, DEV.newt_tol, dist2tol, pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, DEV.lh_nx, plhm, plhf,
plho, pcode, pelem, pref, pdist, pgll1d, plc);
case 3:
FindPointsEdgeLocal3DKernel<3>(npt, DEV.newt_tol, dist2tol,
pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, obb_chk,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc);
break;
return FindPointsEdgeLocal3D_Kernel<3>(
npt, DEV.newt_tol, dist2tol, pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, DEV.lh_nx, plhm, plhf,
plho, pcode, pelem, pref, pdist, pgll1d, plc);
case 4:
FindPointsEdgeLocal3DKernel<4>(npt, DEV.newt_tol, dist2tol,
pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, obb_chk,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc);
break;
return FindPointsEdgeLocal3D_Kernel<4>(
npt, DEV.newt_tol, dist2tol, pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, DEV.lh_nx, plhm, plhf,
plho, pcode, pelem, pref, pdist, pgll1d, plc);
default:
FindPointsEdgeLocal3DKernel(npt, DEV.newt_tol, dist2tol, pp,
point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, obb_chk,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc, DEV.dof1d);
break;
return FindPointsEdgeLocal3D_Kernel(
npt, DEV.newt_tol, dist2tol, pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, DEV.lh_nx, plhm, plhf,
plho, pcode, pelem, pref, pdist, pgll1d, plc, DEV.dof1d);
}
}
#undef rDIM2
+206 -131
View File
@@ -11,7 +11,6 @@
#include "../gslib.hpp"
#include "../../general/forall.hpp"
#include "gslib_kernel_helpers.hpp"
#ifdef MFEM_USE_GSLIB
#ifdef MFEM_HAVE_GCC_PRAGMA_DIAGNOSTIC
@@ -52,15 +51,124 @@ struct findptsElementGPT_t
double x[sDIM], jac[sDIM*rDIM], hes[sDIM*(rDIM+1)];
};
using dbl_range_t = gslib::dbl_range_t;
using obbox_t = gslib::obbox_t<sDIM>;
using findptsLocalHashData_t = gslib::findptsLocalHashData_t<sDIM>;
using gslib::AABB_test;
using gslib::bbox_test;
using gslib::hash_index;
using gslib::l2norm2;
using gslib::lag_eval_second_der;
using gslib::lin_solve_sym_2;
struct dbl_range_t
{
double min, max;
};
struct obbox_t
{
double c0[sDIM], A[sDIM*sDIM];
dbl_range_t x[sDIM];
};
struct findptsLocalHashData_t
{
int hash_n;
dbl_range_t bnd[sDIM];
double fac[sDIM];
unsigned int *offset;
};
static MFEM_HOST_DEVICE inline void lag_eval_second_der(double *p0, double x,
int i, const double *z,
const double *lCoeff,
int pN)
{
double u0 = 1, u1 = 0, u2 = 0;
for (int j = 0; j < pN; ++j)
{
if (i != j)
{
double d_j = 2 * (x - z[j]);
u2 = d_j * u2 + u1;
u1 = d_j * u1 + u0;
u0 = d_j * u0;
}
}
p0[i] = lCoeff[i] * u0;
p0[pN+i] = 2.0 * lCoeff[i] * u1;
p0[2*pN+i] = 8.0 * lCoeff[i] * u2;
}
/* positive when possibly inside */
static MFEM_HOST_DEVICE inline double AABB_test(const obbox_t *const b,
const double x[sDIM])
{
double b_d;
for (int d=0; d<sDIM; ++d)
{
b_d = (x[d] - b->x[d].min) * (b->x[d].max - x[d]);
if (b_d < 0) // if outside in any dimension
{
return b_d;
}
}
return b_d; // only positive if inside in all dimensions
}
/* positive when possibly inside */
static MFEM_HOST_DEVICE inline double bbox_test(const obbox_t *const b,
const double x[sDIM])
{
const double bxyz = AABB_test(b, x);
if (bxyz<0)
{
return bxyz;
}
else
{
double dxyz[3];
// dxyz: distance of the point from the center of the OBB
for (int d=0; d<sDIM; ++d)
{
dxyz[d] = x[d] - b->c0[d];
}
// tranform dxyz to the local coordinate system of the OBB,
// and check if the point is inside the OBB [-1,1]^sDIM
double test = 1;
for (int d=0; d<sDIM; ++d)
{
double rst = 0;
for (int e=0; e<sDIM; ++e)
{
rst += b->A[d*sDIM + e] * dxyz[e];
}
double brst = (rst+1)*(1-rst);
test = test<0 ? test : brst;
}
return test;
}
}
/* Hash index in the hash table to the elements that possibly contain the point x */
static MFEM_HOST_DEVICE inline int hash_index(const findptsLocalHashData_t *p,
const double x[sDIM])
{
const int n = p->hash_n;
int sum = 0;
for (int d=sDIM-1; d>=0; --d)
{
sum *= n;
int i = (int)floor((x[d] - p->bnd[d].min) * p->fac[d]);
sum += i<0 ? 0 : (n-1 < i ? n-1 : i);
}
return sum;
}
static MFEM_HOST_DEVICE inline void lin_solve_sym_2(double x[2],
const double A[3],
const double y[2])
{
const double idet = 1 / (A[0] * A[2] - A[1] * A[1]);
x[0] = idet * (A[2] * y[0] - A[1] * y[1]);
x[1] = idet * (A[0] * y[1] - A[1] * y[0]);
}
static MFEM_HOST_DEVICE inline double l2norm2(const double x[sDIM])
{
return ( x[0]*x[0] + x[1]*x[1] + x[2]*x[2]);
}
/* the bit structure of flags is CSSRR
the C bit --- 1<<4 --- is set when the point is converged
@@ -111,10 +219,18 @@ static MFEM_HOST_DEVICE inline int point_index(const int x)
return ((x>>1)&1u) | ((x>>2)&2u);
}
static MFEM_HOST_DEVICE inline void
static MFEM_HOST_DEVICE inline findptsElementGEdge_t
get_edge(const double *elx[3], const double *wtend, int ei,
int &side_init, int jidx, int pN, findptsElementGEdge_t &edge)
double *workspace, int &side_init, int jidx, int pN)
{
findptsElementGEdge_t edge;
for (int d=0; d<sDIM; ++d)
{
edge.x[d] = workspace + d*pN;
edge.dxdn[d] = workspace + sDIM*pN + d*pN;
edge.d2xdn[d] = workspace + 2*sDIM*pN + d*pN;
}
// given edge index, compute normal and tangential directions
const int dn = ei>>1, //0 for rmin/rmax, 1 for smin/smax
de = plus_1_mod_2(dn); // 1 for rmin/rmax, 0 for smin/smax
@@ -140,6 +256,7 @@ get_edge(const double *elx[3], const double *wtend, int ei,
edge.d2xdn[dd][jj] = sums_k[1];
#undef ELX
}
return edge;
}
static MFEM_HOST_DEVICE inline findptsElementGPT_t get_pt(const double *elx[3],
@@ -195,34 +312,34 @@ static MFEM_HOST_DEVICE inline findptsElementGPT_t get_pt(const double *elx[3],
/* check reduction in objective against prediction, and adjust
trust region radius (p->tr) accordingly;
may reject the prior step, returning 1; otherwise returns 0
sets out_pt->dist2, out_pt->index, out_pt->x, out_pt->oldr in any event,
leaving out_pt->r, out_pt->dr, out_pt->flags to be set when returning 0 */
static MFEM_HOST_DEVICE bool reject_prior_step_q(findptsElementPoint_t *out_pt,
sets out->dist2, out->index, out->x, out->oldr in any event,
leaving out->r, out->dr, out->flags to be set when returning 0 */
static MFEM_HOST_DEVICE bool reject_prior_step_q(findptsElementPoint_t *out,
const double resid[3],
const findptsElementPoint_t *p,
const double tol)
{
const double dist2 = l2norm2<sDIM>(resid);
const double dist2 = l2norm2(resid);
const double decr = p->dist2 - dist2;
const double pred = p->dist2p;
for (int d=0; d<sDIM; ++d)
{
out_pt->x[d] = p->x[d];
out->x[d] = p->x[d];
}
for (int d=0; d<rDIM; ++d)
{
out_pt->oldr[d] = p->r[d];
out->oldr[d] = p->r[d];
}
out_pt->dist2 = dist2;
out->dist2 = dist2;
if (decr>=0.01*pred)
{
if (decr>=0.9*pred) // very good iteration
{
out_pt->tr = 2*p->tr;
out->tr = 2*p->tr;
}
else // good iteration
{
out_pt->tr = p->tr;
out->tr = p->tr;
}
return false;
}
@@ -234,17 +351,17 @@ static MFEM_HOST_DEVICE bool reject_prior_step_q(findptsElementPoint_t *out_pt,
which is why we divide by 4 below */
double v0 = fabs(p->r[0] - p->oldr[0]),
v1 = fabs(p->r[1] - p->oldr[1]);
out_pt->tr = ( v0>v1 ? v0 : v1 )/4;
out_pt->dist2 = p->dist2;
out_pt->flags = p->flags >> 5;
out_pt->dist2p = -HUGE_VAL;
out->tr = ( v0>v1 ? v0 : v1 )/4;
out->dist2 = p->dist2;
out->flags = p->flags >> 5;
out->dist2p = -HUGE_VAL;
for (int d=0; d<rDIM; ++d)
{
out_pt->r[d] = p->oldr[d];
out->r[d] = p->oldr[d];
}
if (pred<dist2*tol)
{
out_pt->flags |= CONVERGED_FLAG;
out->flags |= CONVERGED_FLAG;
}
return true;
}
@@ -252,7 +369,7 @@ static MFEM_HOST_DEVICE bool reject_prior_step_q(findptsElementPoint_t *out_pt,
/* minimize ||resid - jac * dr||_2, with |dr| <= tr, |r0+dr|<=1
(exact solution of trust region problem) */
static MFEM_HOST_DEVICE void newton_face( findptsElementPoint_t *const out_pt,
static MFEM_HOST_DEVICE void newton_face( findptsElementPoint_t *const out,
const double jac[sDIM*rDIM],
const double rhes[3],
const double resid[sDIM],
@@ -423,19 +540,19 @@ newton_face_constrained:
}
newton_face_fin:
out_pt->dist2p = -2*v;
out->dist2p = -2*v;
dr[0] = r[0] - p->r[0];
dr[1] = r[1] - p->r[1];
if ( fabs(dr[0])+fabs(dr[1]) < tol)
{
new_flags |= CONVERGED_FLAG;
}
out_pt->r[0] = r[0], out_pt->r[1] = r[1];
out_pt->flags = new_flags | ((p->flags & FLAG_MASK)<<5);
out->r[0] = r[0], out->r[1] = r[1];
out->flags = new_flags | ((p->flags & FLAG_MASK)<<5);
}
static MFEM_HOST_DEVICE inline void newton_edge(findptsElementPoint_t *const
out_pt,
out,
const double jac[sDIM*rDIM],
const double rhes,
const double resid[sDIM],
@@ -520,10 +637,10 @@ newton_edge_fin:
{
new_flags |= CONVERGED_FLAG;
}
out_pt->r[de] = nr;
out_pt->r[dn] = p->r[dn];
out_pt->dist2p = -v;
out_pt->flags = flags | new_flags | ((p->flags & FLAG_MASK)<<5);
out->r[de] = nr;
out->r[dn] = p->r[dn];
out->dist2p = -v;
out->flags = flags | new_flags | ((p->flags & FLAG_MASK)<<5);
#undef EVAL
}
@@ -559,27 +676,26 @@ static MFEM_HOST_DEVICE void seed_j(const double *elx[sDIM],
// global memory access of element coordinates.
// Are the structs being stored in "local memory" or registers?
template<int T_D1D = 0>
static void FindPointsSurfLocal3DKernel(const int npt,
const double tol,
const double dist2tol,
const double *x,
const int point_pos_ordering,
const double *xElemCoord,
const int nel,
const double *wtend,
const double *boxinfo,
const bool obb_check,
const int hash_n,
const double *hashMin,
const double *hashFac,
unsigned int *hashOffset,
unsigned int *const code_base,
unsigned int *const el_base,
double *const r_base,
double *const dist2_base,
const double *gll1D,
const double *lagcoeff,
const int pN = 0)
static void FindPointsSurfLocal3D_Kernel(const int npt,
const double tol,
const double dist2tol,
const double *x,
const int point_pos_ordering,
const double *xElemCoord,
const int nel,
const double *wtend,
const double *boxinfo,
const int hash_n,
const double *hashMin,
const double *hashFac,
unsigned int *hashOffset,
unsigned int *const code_base,
unsigned int *const el_base,
double *const r_base,
double *const dist2_base,
const double *gll1D,
const double *lagcoeff,
const int pN = 0)
{
const int MD1 = T_D1D ? T_D1D : DofQuadLimits::MAX_D1D;
const int D1D = T_D1D ? T_D1D : pN;
@@ -637,36 +753,22 @@ static void FindPointsSurfLocal3DKernel(const int npt,
{
const unsigned int el = *elp;
const int n_box_ents = obb_check ? (3*sDIM + sDIM2) : (2*sDIM);
bool pass_bb = true;
// construct obbox on the fly
obbox_t box;
if (obb_check)
int n_box_ents = 3*sDIM + sDIM2;
for (int idx = 0; idx < sDIM; ++idx)
{
// construct obbox on the fly
for (int idx = 0; idx < sDIM; ++idx)
{
box.c0[idx] = boxinfo[n_box_ents*el + idx];
box.x[idx].min = boxinfo[n_box_ents*el + sDIM + idx];
box.x[idx].max = boxinfo[n_box_ents*el + 2*sDIM + idx];
}
for (int idx = 0; idx < sDIM2; ++idx)
{
box.A[idx] = boxinfo[n_box_ents*el + 3*sDIM + idx];
}
pass_bb = (bbox_test(&box, x_i) >= 0);
}
else
{
for (int d = 0; d < sDIM; ++d)
{
box.x[d].min = boxinfo[n_box_ents*el + d];
box.x[d].max = boxinfo[n_box_ents*el + sDIM + d];
}
pass_bb = (AABB_test(&box, x_i) >= 0);
box.c0[idx] = boxinfo[n_box_ents*el + idx];
box.x[idx].min = boxinfo[n_box_ents*el + sDIM + idx];
box.x[idx].max = boxinfo[n_box_ents*el + 2*sDIM + idx];
}
if (!pass_bb) { continue; }
for (int idx = 0; idx < sDIM2; ++idx)
{
box.A[idx] = boxinfo[n_box_ents*el + 3*sDIM + idx];
}
if (bbox_test(&box, x_i) < 0) { continue; }
//// findpts_local ////
{
@@ -866,19 +968,13 @@ static void FindPointsSurfLocal3DKernel(const int npt,
double *hes_T = jac + sDIM*rDIM;
double *hes = hes_T + hes_count*sDIM;
findptsElementGEdge_t edge;
for (int d=0; d<sDIM; ++d)
{
edge.x[d] = constraint_workspace + d*D1D;
edge.dxdn[d] = constraint_workspace + d*D1D
+ sDIM*D1D;
edge.d2xdn[d] = constraint_workspace + d*D1D
+ 2*sDIM*D1D;
}
MFEM_FOREACH_THREAD(j,x,D1D*sDIM)
{
// One thread per physical component and edge DOF.
get_edge(elx, wtend, ei, edge_init, j, D1D, edge);
// utilized first D1D threads
edge = get_edge(elx, wtend, ei,
constraint_workspace, edge_init, j,
D1D);
}
MFEM_SYNC_THREAD;
@@ -949,15 +1045,7 @@ static void FindPointsSurfLocal3DKernel(const int npt,
steep *= tmp->r[dn];
if (steep<0)
{
double face_hes[3] =
{
dn == 0 ? hes[2] : hes[0],
hes[1],
dn == 0 ? hes[0] : hes[2]
};
newton_face(fpt, jac, face_hes, resid,
tmp->flags & CONVERGED_FLAG,
tmp, tol);
newton_face( fpt,jac,hes,resid,tmp->flags&CONVERGED_FLAG,tmp,tol);
}
else
{
@@ -1123,42 +1211,29 @@ void FindPointsGSLIB::FindPointsSurfLocal3(const Vector &point_pos,
auto pgll1d = DEV.gll1d.ReadWrite(use_dev);
auto plc = DEV.lagcoeff.Read(use_dev);
double dist2tol = DEV.surf_dist_tol;
const bool obb_chk = obb_check;
switch (DEV.dof1d)
{
case 2:
FindPointsSurfLocal3DKernel<2>(npt, DEV.newt_tol, dist2tol,
pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, obb_chk,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc);
break;
return FindPointsSurfLocal3D_Kernel<2>(
npt, DEV.newt_tol, dist2tol, pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, DEV.lh_nx, plhm, plhf,
plho, pcode, pelem, pref, pdist, pgll1d, plc);
case 3:
FindPointsSurfLocal3DKernel<3>(npt, DEV.newt_tol, dist2tol,
pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, obb_chk,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc);
break;
return FindPointsSurfLocal3D_Kernel<3>(
npt, DEV.newt_tol, dist2tol, pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, DEV.lh_nx, plhm, plhf,
plho, pcode, pelem, pref, pdist, pgll1d, plc);
case 4:
FindPointsSurfLocal3DKernel<4>(npt, DEV.newt_tol, dist2tol,
pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, obb_chk,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc);
break;
return FindPointsSurfLocal3D_Kernel<4>(
npt, DEV.newt_tol, dist2tol, pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, DEV.lh_nx, plhm, plhf,
plho, pcode, pelem, pref, pdist, pgll1d, plc);
default:
FindPointsSurfLocal3DKernel(npt, DEV.newt_tol, dist2tol, pp,
point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, obb_chk,
DEV.lh_nx, plhm, plhf, plho,
pcode, pelem, pref, pdist,
pgll1d, plc, DEV.dof1d);
break;
return FindPointsSurfLocal3D_Kernel(
npt, DEV.newt_tol, dist2tol, pp, point_pos_ordering, pgslm,
NE_split_total, pwt, pbb, DEV.lh_nx, plhm, plhf,
plho, pcode, pelem, pref, pdist, pgll1d, plc, DEV.dof1d);
}
}
-190
View File
@@ -1,190 +0,0 @@
#ifndef MFEM_GSLIB_KERNEL_HELPERS_HPP
#define MFEM_GSLIB_KERNEL_HELPERS_HPP
#include "../../config/config.hpp"
#include <cmath>
namespace mfem
{
namespace gslib
{
struct dbl_range_t
{
double min, max;
};
template <int SDIM>
struct obbox_t
{
double c0[SDIM], A[SDIM * SDIM];
dbl_range_t x[SDIM];
};
template <int SDIM>
struct findptsLocalHashData_t
{
int hash_n;
dbl_range_t bnd[SDIM];
double fac[SDIM];
unsigned int *offset;
};
// Eval the ith Lagrange interpolant at x.
MFEM_HOST_DEVICE inline void lagrange_eval(double *p0, double x,
int i, int p_Nq,
double *z, double *lagrangeCoeff)
{
double p_i = (1 << (p_Nq - 1));
for (int j = 0; j < p_Nq; ++j)
{
const double d_j = x - z[j];
p_i *= j == i ? 1 : d_j;
}
p0[i] = lagrangeCoeff[i] * p_i;
}
// Eval the ith Lagrange interpolant and its first derivative at x.
MFEM_HOST_DEVICE inline void lag_eval_first_der(double *p0, double x,
int i, const double *z,
const double *lCoeff,
int pN)
{
double u0 = 1, u1 = 0;
for (int j = 0; j < pN; ++j)
{
if (i != j)
{
const double d_j = 2 * (x - z[j]);
u1 = d_j * u1 + u0;
u0 = d_j * u0;
}
}
p0[i] = lCoeff[i] * u0;
p0[pN + i] = 2.0 * lCoeff[i] * u1;
}
// Eval the ith Lagrange interpolant and its first and second derivative at x.
MFEM_HOST_DEVICE inline void lag_eval_second_der(double *p0, double x,
int i, const double *z,
const double *lCoeff,
int pN)
{
double u0 = 1, u1 = 0, u2 = 0;
for (int j = 0; j < pN; ++j)
{
if (i != j)
{
const double d_j = 2 * (x - z[j]);
u2 = d_j * u2 + u1;
u1 = d_j * u1 + u0;
u0 = d_j * u0;
}
}
p0[i] = lCoeff[i] * u0;
p0[pN + i] = 2.0 * lCoeff[i] * u1;
p0[2 * pN + i] = 8.0 * lCoeff[i] * u2;
}
// Solve Ax=y where A is a symmetric 2x2 matrix packed as {a00, a01, a11}.
MFEM_HOST_DEVICE inline void lin_solve_sym_2(double x[2],
const double A[3],
const double y[2])
{
const double idet = 1 / (A[0] * A[2] - A[1] * A[1]);
x[0] = idet * (A[2] * y[0] - A[1] * y[1]);
x[1] = idet * (A[0] * y[1] - A[1] * y[0]);
}
// Positive when the point is inside the axis-aligned bounding box.
template <int SDIM>
MFEM_HOST_DEVICE inline double AABB_test(const obbox_t<SDIM> *const b,
const double (&x)[SDIM])
{
double test = 1.0;
for (int d = 0; d < SDIM; ++d)
{
const double b_d = (x[d] - b->x[d].min) * (b->x[d].max - x[d]);
test = test < 0.0 ? test : b_d;
}
return test;
}
// Positive when the point is inside the oriented bounding box.
template <int SDIM>
MFEM_HOST_DEVICE inline double bbox_test(const obbox_t<SDIM> *const b,
const double (&x)[SDIM])
{
const double bxyz = AABB_test(b, x);
if (bxyz < 0.0)
{
return bxyz;
}
double dxyz[SDIM];
for (int d = 0; d < SDIM; ++d)
{
dxyz[d] = x[d] - b->c0[d];
}
double test = 1.0;
for (int d = 0; d < SDIM; ++d)
{
double rst = 0.0;
for (int e = 0; e < SDIM; ++e)
{
rst += b->A[d * SDIM + e] * dxyz[e];
}
const double brst = (rst + 1.0) * (1.0 - rst);
test = test < 0.0 ? test : brst;
}
return test;
}
// Hash index in the hash table for the point x.
template <int SDIM>
MFEM_HOST_DEVICE inline int hash_index(
const findptsLocalHashData_t<SDIM> *const p,
const double (&x)[SDIM])
{
const int n = p->hash_n;
int sum = 0;
for (int d = SDIM - 1; d >= 0; --d)
{
sum *= n;
const int i = (int)floor((x[d] - p->bnd[d].min) * p->fac[d]);
sum += i < 0 ? 0 : (n - 1 < i ? n - 1 : i);
}
return sum;
}
// Squared Euclidean norm.
template <int SDIM>
MFEM_HOST_DEVICE inline double l2norm2(const double (&x)[SDIM])
{
double sum = 0.0;
for (int d = 0; d < SDIM; ++d)
{
sum += x[d] * x[d];
}
return sum;
}
template <int SDIM>
MFEM_HOST_DEVICE inline double l2norm2(const double *x)
{
double sum = 0.0;
for (int d = 0; d < SDIM; ++d)
{
sum += x[d] * x[d];
}
return sum;
}
} // namespace gslib
} // namespace mfem
#endif
+27 -22
View File
@@ -11,7 +11,7 @@
#include "../gslib.hpp"
#include "../../general/forall.hpp"
#include "gslib_kernel_helpers.hpp"
#include "../../linalg/kernels.hpp"
#ifdef MFEM_USE_GSLIB
@@ -33,7 +33,17 @@ namespace mfem
#define CODE_BORDER 1
#define CODE_NOT_FOUND 2
using gslib::lagrange_eval;
static MFEM_HOST_DEVICE void lagrange_eval(double *p0, double x,
int i, int p_Nq,
double *z, double *lagrangeCoeff)
{
double p_i = (1 << (p_Nq - 1));
for (int j=0; j<p_Nq; ++j)
{
p_i *= j==i ? 1 : x-z[j];
}
p0[i] = lagrangeCoeff[i] * p_i;
}
template<int T_D1D = 0>
static void InterpolateLocal1DKernel(const double *const gf_in,
@@ -113,26 +123,21 @@ void FindPointsGSLIB::InterpolateLocal1( const Vector &field_in,
auto plcf = DEV.lagcoeff_sol.ReadWrite(use_dev);
switch (dof1Dsol)
{
case 2:
InterpolateLocal1DKernel<2>(pfin, pgsl, pgslr, pfout,
npt, ncomp, pgll, plcf);
break;
case 3:
InterpolateLocal1DKernel<3>(pfin, pgsl, pgslr, pfout,
npt, ncomp, pgll, plcf);
break;
case 4:
InterpolateLocal1DKernel<4>(pfin, pgsl, pgslr, pfout,
npt, ncomp, pgll, plcf);
break;
case 5:
InterpolateLocal1DKernel<5>(pfin, pgsl, pgslr, pfout,
npt, ncomp, pgll, plcf);
break;
default:
InterpolateLocal1DKernel(pfin, pgsl, pgslr, pfout,
npt, ncomp, pgll, plcf, dof1Dsol);
break;
case 2: return InterpolateLocal1DKernel<2>(pfin, pgsl, pgslr, pfout,
npt, ncomp,
pgll, plcf);
case 3: return InterpolateLocal1DKernel<3>(pfin, pgsl, pgslr, pfout,
npt, ncomp,
pgll, plcf);
case 4: return InterpolateLocal1DKernel<4>(pfin, pgsl, pgslr, pfout,
npt, ncomp,
pgll, plcf);
case 5: return InterpolateLocal1DKernel<5>(pfin, pgsl, pgslr, pfout,
npt, ncomp,
pgll, plcf);
default: return InterpolateLocal1DKernel(pfin, pgsl, pgslr, pfout,
npt, ncomp,
pgll, plcf, dof1Dsol);
}
}
#undef CODE_INTERNAL
+27 -22
View File
@@ -11,7 +11,6 @@
#include "../gslib.hpp"
#include "../../general/forall.hpp"
#include "gslib_kernel_helpers.hpp"
#ifdef MFEM_USE_GSLIB
@@ -33,7 +32,18 @@ namespace mfem
#define CODE_BORDER 1
#define CODE_NOT_FOUND 2
using gslib::lagrange_eval;
static MFEM_HOST_DEVICE void lagrange_eval(double *p0, double x,
int i, int p_Nq,
double *z, double *lagrangeCoeff)
{
double p_i = (1 << (p_Nq - 1));
for (int j = 0; j < p_Nq; ++j)
{
double d_j = x - z[j];
p_i *= j == i ? 1 : d_j;
}
p0[i] = lagrangeCoeff[i] * p_i;
}
template<int T_D1D = 0>
static void InterpolateLocal2DKernel(const double *const gf_in,
@@ -122,26 +132,21 @@ void FindPointsGSLIB::InterpolateLocal2(const Vector &field_in,
auto plcf = DEV.lagcoeff_sol.ReadWrite(use_dev);
switch (dof1Dsol)
{
case 2:
InterpolateLocal2DKernel<2>(pfin, pgsl, pgslr, pfout,
npt, ncomp, pgll, plcf);
break;
case 3:
InterpolateLocal2DKernel<3>(pfin, pgsl, pgslr, pfout,
npt, ncomp, pgll, plcf);
break;
case 4:
InterpolateLocal2DKernel<4>(pfin, pgsl, pgslr, pfout,
npt, ncomp, pgll, plcf);
break;
case 5:
InterpolateLocal2DKernel<5>(pfin, pgsl, pgslr, pfout,
npt, ncomp, pgll, plcf);
break;
default:
InterpolateLocal2DKernel(pfin, pgsl, pgslr, pfout,
npt, ncomp, pgll, plcf, dof1Dsol);
break;
case 2: return InterpolateLocal2DKernel<2>(pfin, pgsl, pgslr, pfout,
npt, ncomp,
pgll, plcf);
case 3: return InterpolateLocal2DKernel<3>(pfin, pgsl, pgslr, pfout,
npt, ncomp,
pgll, plcf);
case 4: return InterpolateLocal2DKernel<4>(pfin, pgsl, pgslr, pfout,
npt, ncomp,
pgll, plcf);
case 5: return InterpolateLocal2DKernel<5>(pfin, pgsl, pgslr, pfout,
npt, ncomp,
pgll, plcf);
default: return InterpolateLocal2DKernel(pfin, pgsl, pgslr, pfout,
npt, ncomp,
pgll, plcf, dof1Dsol);
}
}
+27 -22
View File
@@ -11,7 +11,6 @@
#include "../gslib.hpp"
#include "../../general/forall.hpp"
#include "gslib_kernel_helpers.hpp"
#ifdef MFEM_USE_GSLIB
@@ -33,7 +32,18 @@ namespace mfem
#define CODE_BORDER 1
#define CODE_NOT_FOUND 2
using gslib::lagrange_eval;
static MFEM_HOST_DEVICE void lagrange_eval(double *p0, double x,
int i, int p_Nq,
double *z, double *lagrangeCoeff)
{
double p_i = (1 << (p_Nq - 1));
for (int j = 0; j < p_Nq; ++j)
{
double d_j = x - z[j];
p_i *= j == i ? 1 : d_j;
}
p0[i] = lagrangeCoeff[i] * p_i;
}
template<int T_D1D = 0>
static void InterpolateLocal3DKernel(const double *const gf_in,
@@ -125,26 +135,21 @@ void FindPointsGSLIB::InterpolateLocal3(const Vector &field_in,
auto plcf = DEV.lagcoeff_sol.ReadWrite(use_dev);
switch (dof1Dsol)
{
case 2:
InterpolateLocal3DKernel<2>(pfin, pgsle, pgslr, pfout,
npt, ncomp, pgll, plcf);
break;
case 3:
InterpolateLocal3DKernel<3>(pfin, pgsle, pgslr, pfout,
npt, ncomp, pgll, plcf);
break;
case 4:
InterpolateLocal3DKernel<4>(pfin, pgsle, pgslr, pfout,
npt, ncomp, pgll, plcf);
break;
case 5:
InterpolateLocal3DKernel<5>(pfin, pgsle, pgslr, pfout,
npt, ncomp, pgll, plcf);
break;
default:
InterpolateLocal3DKernel(pfin, pgsle, pgslr, pfout,
npt, ncomp, pgll, plcf, dof1Dsol);
break;
case 2: return InterpolateLocal3DKernel<2>(pfin, pgsle, pgslr, pfout,
npt, ncomp,
pgll, plcf);
case 3: return InterpolateLocal3DKernel<3>(pfin, pgsle, pgslr, pfout,
npt, ncomp,
pgll, plcf);
case 4: return InterpolateLocal3DKernel<4>(pfin, pgsle, pgslr, pfout,
npt, ncomp,
pgll, plcf);
case 5: return InterpolateLocal3DKernel<5>(pfin, pgsle, pgslr, pfout,
npt, ncomp,
pgll, plcf);
default: return InterpolateLocal3DKernel(pfin, pgsle, pgslr, pfout,
npt, ncomp,
pgll, plcf, dof1Dsol);
}
}
+3 -3
View File
@@ -91,15 +91,15 @@ void ElasticityAddMultPA(const int dim, const int nDofs,
void ElasticityAssembleDiagonalPA(const int dim, const int nDofs,
const CoefficientVector &lambda,
const CoefficientVector &mu, const GeometricFactors &geom,
const DofToQuad &maps, const IntegrationRule &ir, Vector &diag)
const DofToQuad &maps, QuadratureFunction &QVec, Vector &diag)
{
switch (dim)
{
case 2:
ElasticityAssembleDiagonalPA_<2>(nDofs, lambda, mu, geom, maps, ir, diag);
ElasticityAssembleDiagonalPA_<2>(nDofs, lambda, mu, geom, maps, QVec, diag);
break;
case 3:
ElasticityAssembleDiagonalPA_<3>(nDofs, lambda, mu, geom, maps, ir, diag);
ElasticityAssembleDiagonalPA_<3>(nDofs, lambda, mu, geom, maps, QVec, diag);
break;
default:
MFEM_ABORT("Only dimensions 2 and 3 supported.");
+55 -44
View File
@@ -38,6 +38,7 @@
#include "../../linalg/vector.hpp"
#include "../../linalg/tensor.hpp"
#include "../quadinterpolator.hpp"
#include "../bilininteg.hpp"
#include "../coefficient.hpp"
#include "../qfunction.hpp"
@@ -132,12 +133,12 @@ void ElasticityAssembleEA(const int dim, const int i_block, const int j_block,
/// @param[in] mu Quadrature function for second Lame param.
/// @param[in] geom Geometric factors corresponding to fespace.
/// @param[in] maps DofToQuad maps for one element (assume elements all same).
/// @param[in] ir Integration rule.
/// @param QVec Scratch Q-Vector. nQuad x dim x dim x dim x dim x numEls.
/// @param[out] diag diagonal of A. nDofs x dim x numEls.
void ElasticityAssembleDiagonalPA(const int dim, const int nDofs,
const CoefficientVector &lambda,
const CoefficientVector &mu, const GeometricFactors &geom,
const DofToQuad &maps, const IntegrationRule &ir, Vector &diag);
const DofToQuad &maps, QuadratureFunction &QVec, Vector &diag);
/// Templated implementation of ElasticityAddMultPA.
template<int dim, int i_block = -1, int j_block = -1>
@@ -279,67 +280,77 @@ void ElasticityAddMultPA_(const int nDofs, const FiniteElementSpace &fespace,
template<int dim>
void ElasticityAssembleDiagonalPA_(const int nDofs,
const CoefficientVector &lambda,
const CoefficientVector &mu,
const GeometricFactors &geom,
const DofToQuad &maps,
const IntegrationRule &ir,
Vector &diag)
const CoefficientVector &mu, const GeometricFactors &geom,
const DofToQuad &maps, QuadratureFunction &QVec, Vector &diag)
{
using future::tensor;
using future::make_tensor;
using future::det;
using future::inv;
using future::make_tensor;
using future::tensor;
// Assuming all elements are the same
const auto &ir = QVec.GetIntRule(0);
static constexpr int d = dim;
const int numPoints = ir.GetNPoints();
const int numEls = lambda.Size() / numPoints;
const int numEls = lambda.Size()/numPoints;
const auto lamDev = Reshape(lambda.Read(), numPoints, numEls);
const auto muDev = Reshape(mu.Read(), numPoints, numEls);
const auto J = Reshape(geom.J.Read(), numPoints, d, d, numEls);
auto Q = Reshape(QVec.ReadWrite(), numPoints, d,d, d, numEls);
const real_t *ipWeights = ir.GetWeights().Read();
const auto G = Reshape(maps.G.Read(), numPoints, d, nDofs);
auto diagDev = Reshape(diag.Write(), nDofs, d, numEls);
mfem::forall_2D(numEls, numPoints,1, [=] MFEM_HOST_DEVICE (int e)
{
MFEM_FOREACH_THREAD(p, x,numPoints)
{
auto invJ = inv(make_tensor<d, d>(
[&](int i, int j) { return J(p, i, j, e); }));
const real_t w = ipWeights[p] /det(invJ);
for (int n = 0; n < d; n++)
{
for (int m = 0; m < d; m++)
{
for (int q = 0; q < d; q++)
{
// compute contraction of 4*sym(grad(u))sym(grad(v)) term.
// this contraction could be made slightly cheaper using Voigt
// notation, but repeated entries are summed for simplicity.
real_t contraction = 0.;
for (int a = 0; a < d; a++)
{
for (int b = 0; b < d; b++)
{
contraction += ((a == q)*invJ(m,b) + (b==q)*invJ(m,a))*((a == q)
*invJ(n, b) + (b==q)*invJ(n,a));
}
}
// lambda*div(u)*div(v) + 2*mu*sym(grad(u))*sym(grad(v))
// contraction = 4*sym(grad(u))sym(grad(v))
Q(p,m,n,q,e) = w*(lamDev(p, e)*invJ(m,q)*invJ(n,q)
+ 0.5*muDev(p, e)*contraction);
}
}
}
}
});
// Reduce quadrature function to an E-Vector
const auto QRead = Reshape(QVec.Read(), numPoints, d, d, d, numEls);
auto diagDev = Reshape(diag.Write(), nDofs, d, numEls);
const auto G = Reshape(maps.G.Read(), numPoints, d, nDofs);
mfem::forall_2D(numEls, d, nDofs, [=] MFEM_HOST_DEVICE (int e)
{
MFEM_FOREACH_THREAD_DIRECT(i, y, nDofs)
MFEM_FOREACH_THREAD(i, y, nDofs)
{
MFEM_FOREACH_THREAD_DIRECT(q, x, d)
MFEM_FOREACH_THREAD(q, x, d)
{
real_t sum = 0.0;
for (int p = 0; p < numPoints; p++)
real_t sum = 0.;
for (int n = 0; n < d; n++)
{
const auto invJ = inv(make_tensor<d, d>([&](int r, int c)
for (int m = 0; m < d; m++)
{
return J(p, r, c, e);
}));
const real_t w = ipWeights[p] / det(invJ);
for (int n = 0; n < d; n++)
{
for (int m = 0; m < d; m++)
for (int p = 0; p < numPoints; p++ )
{
// compute contraction of 4*sym(grad(u))sym(grad(v)) term.
// this contraction could be made slightly cheaper using Voigt
// notation, but repeated entries are summed for simplicity.
real_t contraction = 0.0;
for (int a = 0; a < d; a++)
{
for (int b = 0; b < d; b++)
{
contraction +=
((a == q) * invJ(m, b) + (b == q) * invJ(m, a)) *
((a == q) * invJ(n, b) + (b == q) * invJ(n, a));
}
}
// lambda*div(u)*div(v) + 2*mu*sym(grad(u))*sym(grad(v))
// contraction = 4*sym(grad(u))sym(grad(v))
const real_t Q =
w * (lamDev(p, e) * invJ(m, q) * invJ(n, q)
+ 0.5 * muDev(p, e) * contraction);
sum += Q * G(p, m, i) * G(p, n, i);
sum += QRead(p,m,n,q,e)*G(p,m,i)*G(p,n,i);
}
}
}
+3 -1
View File
@@ -10,6 +10,7 @@
// CONTRIBUTING.md for details.
#include "../bilininteg.hpp"
#include "../gridfunc.hpp"
#include "../qfunction.hpp"
#include "bilininteg_elasticity_kernels.hpp"
@@ -58,8 +59,9 @@ void ElasticityIntegrator::AssemblePA(const FiniteElementSpace &fes)
void ElasticityIntegrator::AssembleDiagonalPA(Vector &diag)
{
q_vec->SetVDim(vdim*vdim*vdim*vdim);
internal::ElasticityAssembleDiagonalPA(vdim, ndofs, *lambda_quad, *mu_quad,
*geom, *maps, *IntRule, diag);
*geom, *maps, *q_vec, diag);
}
void ElasticityIntegrator::AddMultPA(const Vector &x, Vector &y) const
+10 -12
View File
@@ -148,12 +148,11 @@ void PAHcurlMassAssembleDiagonal3D(const int D1D,
}
void PAHcurlMassApply2D(const int NE, const bool symmetric,
[[maybe_unused]] const bool scalar_coeff,
const Array<real_t> &bo, const Array<real_t> &bc,
const Array<real_t> &bot, const Array<real_t> &bct,
const Vector &pa_data, const Vector &x, Vector &y,
const int D1D, [[maybe_unused]] const int TestD1D,
const int Q1D)
const bool scalar_coeff, const Array<real_t> &bo,
const Array<real_t> &bc, const Array<real_t> &bot,
const Array<real_t> &bct, const Vector &pa_data,
const Vector &x, Vector &y, const int D1D,
const int TestD1D, const int Q1D)
{
MFEM_ASSERT(D1D == TestD1D,
"Trial and Test space must have the same number of dofs");
@@ -276,12 +275,11 @@ void PAHcurlMassApply2D(const int NE, const bool symmetric,
}
void PAHcurlMassApply3D(const int NE, const bool symmetric,
[[maybe_unused]] const bool scalar_coeff,
const Array<real_t> &bo, const Array<real_t> &bc,
const Array<real_t> &bot, const Array<real_t> &bct,
const Vector &pa_data, const Vector &x, Vector &y,
const int D1D, [[maybe_unused]] const int TestD1D,
const int Q1D)
const bool scalar_coeff, const Array<real_t> &bo,
const Array<real_t> &bc, const Array<real_t> &bot,
const Array<real_t> &bct, const Vector &pa_data,
const Vector &x, Vector &y, const int D1D,
const int TestD1D, const int Q1D)
{
MFEM_VERIFY(D1D == TestD1D,
"Trial and test spaces must have same number of dofs");
+9 -12
View File
@@ -190,22 +190,19 @@ void PAHcurlMassApply2D(const int NE, const bool symmetric,
// PA H(curl) Mass Apply 3D kernel
void PAHcurlMassApply3D(const int NE, const bool symmetric,
[[maybe_unused]] const bool scalar_coeff,
const Array<real_t> &bo, const Array<real_t> &bc,
const Array<real_t> &bot, const Array<real_t> &bct,
const Vector &pa_data, const Vector &x, Vector &y,
const int TrialD1D, [[maybe_unused]] const int TestD1D,
const int Q1D);
const bool scalar_coeff, const Array<real_t> &bo,
const Array<real_t> &bc, const Array<real_t> &bot,
const Array<real_t> &bct, const Vector &pa_data,
const Vector &x, Vector &y, const int TrialD1D,
const int TestD1D, const int Q1D);
// Shared memory PA H(curl) Mass Apply 3D kernel
template <int T_D1D = 0, int T_Q1D = 0, int TBATCH = 0, bool ACCUMULATE = true>
inline void SmemPAHcurlMassApply3D(
const int NE, const bool symmetric, [[maybe_unused]] const bool scalar_coeff,
const Array<real_t> &bo, const Array<real_t> &bc,
[[maybe_unused]] const Array<real_t> &bot,
[[maybe_unused]] const Array<real_t> &bct, const Vector &pa_data,
const Vector &x, Vector &y, const int d1d = 0,
[[maybe_unused]] const int test_d1d = 0, const int q1d = 0)
const int NE, const bool symmetric, const bool scalar_coeff,
const Array<real_t> &bo, const Array<real_t> &bc, const Array<real_t> &bot,
const Array<real_t> &bct, const Vector &pa_data, const Vector &x, Vector &y,
const int d1d = 0, const int = 0, const int q1d = 0)
{
const int D1D = T_D1D ? T_D1D : d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
+648
View File
@@ -864,8 +864,656 @@ inline void PAHcurlHdivApplyTranspose3D(const int d1d,
}); // end of element loop
}
namespace curlinterp
{
constexpr int NBZ3D(int ndof_o, int nquad_o, int mdq)
{
if (ndof_o <= 0 || nquad_o <= 0)
{
return 1;
}
int ndof_c = ndof_o + 1;
int nquad_c = nquad_o + 1;
// z dimension is capped at 64 on nvidia and amd gpus
int tmp =
std::min((128 + mdq * mdq * (mdq - 1) - 1) / (mdq * mdq * (mdq - 1)), 64);
int smem_req =
sizeof(mfem::real_t) *
((3 * ndof_c * ndof_c * ndof_o + 2 * 2 * mdq * mdq * mdq) * tmp +
ndof_c * nquad_o + ndof_c * nquad_c + ndof_o * nquad_o);
// assume GPU has at least 48k shared memory
return std::max(std::min(tmp, (48 * 1024 + smem_req - 1) / smem_req), 1);
}
}
template <int T_NDOF_O, int T_NQUAD_O>
void CurlInterpolatorApply3DSmem(const int ne, const int ndof_o,
const int nquad_o, const Vector &pa,
const Vector &x_, Vector &y_)
{
constexpr int mnd_o = T_NDOF_O ? T_NDOF_O : DofQuadLimits::HCURL_MAX_D1D - 1;
constexpr int mnq_o =
T_NQUAD_O ? T_NQUAD_O : DofQuadLimits::HDIV_MAX_D1D - 1;
constexpr int mndq = std::max(mnd_o + 1, mnq_o + 1);
constexpr int tbatch = curlinterp::NBZ3D(T_NDOF_O, T_NQUAD_O, mndq);
MFEM_VERIFY(ndof_o <= mnd_o, "Error: H(curl) order larger than supported");
MFEM_VERIFY(nquad_o <= mnq_o, "Error: H(div) order larger than supported");
int mnq = std::max(ndof_o + 1, nquad_o + 1);
auto pa_data = pa.Read();
auto x_d = x_.Read();
auto y_d = y_.ReadWrite();
mfem::forall_2D_batch<mndq * mndq * (mndq - 1) * tbatch>(
ne, mnq * mnq * (mnq - 1), 1, tbatch, [=] MFEM_HOST_DEVICE(int e)
{
constexpr int MND_O =
T_NDOF_O ? T_NDOF_O : DofQuadLimits::HCURL_MAX_D1D - 1;
constexpr int MNQ_O =
T_NQUAD_O ? T_NQUAD_O : DofQuadLimits::HDIV_MAX_D1D - 1;
constexpr int MNDQ = std::max(MND_O + 1, MNQ_O + 1);
#if defined(__CUDA_ARCH__) || defined(__HIP_DEVICE_COMPILE__)
constexpr int nbz = curlinterp::NBZ3D(T_NDOF_O, T_NQUAD_O, MNDQ);
int tidz = MFEM_THREAD_ID(z);
// Make mnq a local variable since capturing would result in different
// captures between host/device versions, and spuriously fails
int mnq = std::max(ndof_o + 1, nquad_o + 1);
#else
constexpr int nbz = 1;
constexpr int tidz = 0;
#endif
const int NDOF_O = T_NDOF_O ? T_NDOF_O : ndof_o;
const int NQUAD_O = T_NQUAD_O ? T_NQUAD_O : nquad_o;
const int NDOF_C = NDOF_O + 1;
const int NQUAD_C = NQUAD_O + 1;
MFEM_SHARED real_t
sBG[(MND_O + 1) * MNQ_O + (MND_O + 1) * (MNQ_O + 1) + MND_O * MNQ_O];
auto X_ = Reshape(x_d, 3 * NDOF_C * NDOF_C * NDOF_O, ne);
auto Y = Reshape(y_d, 3 * NQUAD_C * NQUAD_O * NQUAD_O, ne);
auto Gco = Reshape(sBG, NQUAD_O, NDOF_C);
auto Bcc = Reshape(sBG + NDOF_C * NQUAD_O, NQUAD_C, NDOF_C);
auto Boo =
Reshape(sBG + NDOF_C * NQUAD_O + NDOF_C * NQUAD_C, NQUAD_O, NDOF_O);
MFEM_SHARED real_t X[3][nbz][MND_O * (MND_O + 1) * (MND_O + 1)];
MFEM_SHARED real_t sm0[nbz * 2 * MNDQ * MNDQ * MNDQ];
MFEM_SHARED real_t sm1[nbz * 2 * MNDQ * MNDQ * MNDQ];
// shapes of buffers always use MNDQ to mitigate shared memory bank
// conflicts
real_t(*DDQ)[nbz][MNDQ][MNDQ][MNDQ] =
(real_t(*)[nbz][MNDQ][MNDQ][MNDQ])(sm0);
real_t(*DQQ)[nbz][MNDQ][MNDQ][MNDQ] =
(real_t(*)[nbz][MNDQ][MNDQ][MNDQ])(sm1);
real_t(*QQQ)[nbz][MNDQ][MNDQ][MNDQ] =
(real_t(*)[nbz][MNDQ][MNDQ][MNDQ])(sm0);
const int offset = NDOF_O * NDOF_C * NDOF_C;
const int offsetq = NQUAD_C * NQUAD_O * NQUAD_O;
MFEM_FOREACH_THREAD_DIRECT(ix, x, offset)
{
for (int dim = 0; dim < 3; ++dim)
{
X[dim][tidz][ix] = X_(ix + dim * offset, e);
}
}
// load basis functions data
if (tidz == 0)
{
auto npts = NDOF_C * NQUAD_O + NDOF_C * NQUAD_C + NDOF_O * NQUAD_O;
MFEM_FOREACH_THREAD(ix, x, npts) { sBG[ix] = pa_data[ix]; }
}
MFEM_SYNC_THREAD;
// x: Vz Bcc Gco Boo - Vy Bcc Boo Gco
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, dy, dz, x, NQUAD_C, NDOF_C,
NDOF_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int dx = 0; dx < NDOF_C; ++dx)
{
u += X[2][tidz][dx + (dy + dz * NDOF_C) * NDOF_C] * Bcc(qx, dx);
}
DDQ[0][tidz][dz][dy][qx] = u;
}
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, dy, dz, x, NQUAD_C, NDOF_O,
NDOF_C, mnq, mnq - 1, mnq)
{
real_t u = 0;
for (int dx = 0; dx < NDOF_C; ++dx)
{
u += X[1][tidz][dx + (dy + dz * NDOF_O) * NDOF_C] * Bcc(qx, dx);
}
DDQ[1][tidz][dz][dy][qx] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, qy, dz, x, NQUAD_C, NQUAD_O,
NDOF_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int dy = 0; dy < NDOF_C; ++dy)
{
u += DDQ[0][tidz][dz][dy][qx] * Gco(qy, dy);
}
DQQ[0][tidz][dz][qy][qx] = u;
}
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, qy, dz, x, NQUAD_C, NQUAD_O,
NDOF_C, mnq, mnq - 1, mnq)
{
real_t u = 0;
for (int dy = 0; dy < NDOF_O; ++dy)
{
u += DDQ[1][tidz][dz][dy][qx] * Boo(qy, dy);
}
DQQ[1][tidz][dz][qy][qx] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, qy, qz, x, NQUAD_C, NQUAD_O,
NQUAD_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int dz = 0; dz < NDOF_O; ++dz)
{
u += DQQ[0][tidz][dz][qy][qx] * Boo(qz, dz);
}
QQQ[0][tidz][qz][qy][qx] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, qy, qz, x, NQUAD_C, NQUAD_O,
NQUAD_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int dz = 0; dz < NDOF_C; ++dz)
{
u += DQQ[1][tidz][dz][qy][qx] * Gco(qz, dz);
}
Y(qx + (qy + qz * NQUAD_O) * NQUAD_C, e) =
QQQ[0][tidz][qz][qy][qx] - u;
}
MFEM_SYNC_THREAD;
// y: Vx Boo Bcc Gco - Vz Gco Bcc Boo
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, dy, dz, x, NQUAD_O, NDOF_C,
NDOF_C, mnq - 1, mnq, mnq)
{
real_t u = 0;
for (int dx = 0; dx < NDOF_O; ++dx)
{
u += X[0][tidz][dx + (dy + dz * NDOF_C) * NDOF_O] * Boo(qx, dx);
}
DDQ[0][tidz][dz][dy][qx] = u;
}
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, dy, dz, x, NQUAD_O, NDOF_C,
NDOF_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int dx = 0; dx < NDOF_C; ++dx)
{
u += X[2][tidz][dx + (dy + dz * NDOF_C) * NDOF_C] * Gco(qx, dx);
}
DDQ[1][tidz][dz][dy][qx] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, qy, dz, x, NQUAD_O, NQUAD_C,
NDOF_C, mnq - 1, mnq, mnq)
{
real_t u = 0;
for (int dy = 0; dy < NDOF_C; ++dy)
{
u += DDQ[0][tidz][dz][dy][qx] * Bcc(qy, dy);
}
DQQ[0][tidz][dz][qy][qx] = u;
}
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, qy, dz, x, NQUAD_O, NQUAD_C,
NDOF_O, mnq - 1, mnq, mnq)
{
real_t u = 0;
for (int dy = 0; dy < NDOF_C; ++dy)
{
u += DDQ[1][tidz][dz][dy][qx] * Bcc(qy, dy);
}
DQQ[1][tidz][dz][qy][qx] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, qy, qz, x, NQUAD_O, NQUAD_C,
NQUAD_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int dz = 0; dz < NDOF_C; ++dz)
{
u += DQQ[0][tidz][dz][qy][qx] * Gco(qz, dz);
}
QQQ[0][tidz][qz][qy][qx] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, qy, qz, x, NQUAD_O, NQUAD_C,
NQUAD_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int dz = 0; dz < NDOF_O; ++dz)
{
u += DQQ[1][tidz][dz][qy][qx] * Boo(qz, dz);
}
Y(qx + (qy + qz * NQUAD_C) * NQUAD_O + offsetq, e) =
QQQ[0][tidz][qz][qy][qx] - u;
}
MFEM_SYNC_THREAD;
// z: Vy Gco Boo Bcc - Vx Boo Gco Bcc
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, dy, dz, x, NQUAD_O, NDOF_O,
NDOF_C, mnq, mnq - 1, mnq)
{
real_t u = 0;
for (int dx = 0; dx < NDOF_C; ++dx)
{
u += X[1][tidz][dx + (dy + dz * NDOF_O) * NDOF_C] * Gco(qx, dx);
}
DDQ[0][tidz][dz][dy][qx] = u;
}
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, dy, dz, x, NQUAD_O, NDOF_C,
NDOF_C, mnq - 1, mnq, mnq)
{
real_t u = 0;
for (int dx = 0; dx < NDOF_O; ++dx)
{
u += X[0][tidz][dx + (dy + dz * NDOF_C) * NDOF_O] * Boo(qx, dx);
}
DDQ[1][tidz][dz][dy][qx] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, qy, dz, x, NQUAD_O, NQUAD_O,
NDOF_C, mnq, mnq - 1, mnq)
{
real_t u = 0;
for (int dy = 0; dy < NDOF_O; ++dy)
{
u += DDQ[0][tidz][dz][dy][qx] * Boo(qy, dy);
}
DQQ[0][tidz][dz][qy][qx] = u;
}
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, qy, dz, x, NQUAD_O, NQUAD_O,
NDOF_C, mnq, mnq - 1, mnq)
{
real_t u = 0;
for (int dy = 0; dy < NDOF_C; ++dy)
{
u += DDQ[1][tidz][dz][dy][qx] * Gco(qy, dy);
}
DQQ[1][tidz][dz][qy][qx] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, qy, qz, x, NQUAD_O, NQUAD_O,
NQUAD_C, mnq, mnq - 1, mnq)
{
real_t u = 0;
for (int dz = 0; dz < NDOF_C; ++dz)
{
u += DQQ[0][tidz][dz][qy][qx] * Bcc(qz, dz);
}
QQQ[0][tidz][qz][qy][qx] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(qx, qy, qz, x, NQUAD_O, NQUAD_O,
NQUAD_C, mnq, mnq - 1, mnq)
{
real_t u = 0;
for (int dz = 0; dz < NDOF_C; ++dz)
{
u += DQQ[1][tidz][dz][qy][qx] * Bcc(qz, dz);
}
Y(qx + (qy + qz * NQUAD_O) * NQUAD_O + 2 * offsetq, e) =
QQQ[0][tidz][qz][qy][qx] - u;
}
MFEM_SYNC_THREAD;
});
}
template <int T_NDOF_O, int T_NQUAD_O>
void CurlInterpolatorTApply3DSmem(const int ne, const int ndof_o,
const int nquad_o, const Vector &pa,
const Vector &x_, Vector &y_)
{
constexpr int mnd_o = T_NDOF_O ? T_NDOF_O : DofQuadLimits::HCURL_MAX_D1D - 1;
constexpr int mnq_o =
T_NQUAD_O ? T_NQUAD_O : DofQuadLimits::HDIV_MAX_D1D - 1;
constexpr int mndq = std::max(mnd_o + 1, mnq_o + 1);
constexpr int tbatch = curlinterp::NBZ3D(T_NDOF_O, T_NQUAD_O, mndq);
MFEM_VERIFY(ndof_o <= mnd_o, "Error: H(curl) order larger than supported");
MFEM_VERIFY(nquad_o <= mnq_o, "Error: H(div) order larger than supported");
int mnq = std::max(ndof_o + 1, nquad_o + 1);
auto pa_data = pa.Read();
auto x_d = x_.Read();
auto y_d = y_.ReadWrite();
mfem::forall_2D_batch<mndq * mndq * (mndq - 1) * tbatch>(
ne, mnq * mnq * (mnq - 1), 1, tbatch, [=] MFEM_HOST_DEVICE(int e)
{
constexpr int MND_O =
T_NDOF_O ? T_NDOF_O : DofQuadLimits::HCURL_MAX_D1D - 1;
constexpr int MNQ_O =
T_NQUAD_O ? T_NQUAD_O : DofQuadLimits::HDIV_MAX_D1D - 1;
constexpr int MNDQ = std::max(MND_O + 1, MNQ_O + 1);
#if defined(__CUDA_ARCH__) || defined(__HIP_DEVICE_COMPILE__)
constexpr int nbz = curlinterp::NBZ3D(T_NDOF_O, T_NQUAD_O, MNDQ);
int tidz = MFEM_THREAD_ID(z);
// Make mnq a local variable since capturing would result in different
// captures between host/device versions, and spuriously fails
int mnq = std::max(ndof_o + 1, nquad_o + 1);
#else
constexpr int nbz = 1;
constexpr int tidz = 0;
#endif
const int NDOF_O = T_NDOF_O ? T_NDOF_O : ndof_o;
const int NQUAD_O = T_NQUAD_O ? T_NQUAD_O : nquad_o;
const int NDOF_C = NDOF_O + 1;
const int NQUAD_C = NQUAD_O + 1;
MFEM_SHARED real_t
sBG[(MND_O + 1) * MNQ_O + (MND_O + 1) * (MNQ_O + 1) + MND_O * MNQ_O];
auto X_ = Reshape(x_d, 3 * NQUAD_C * NQUAD_O * NQUAD_O, ne);
auto Y = Reshape(y_d, 3 * NDOF_C * NDOF_C * NDOF_O, ne);
auto Gco = Reshape(sBG, NQUAD_O, NDOF_C);
auto Bcc = Reshape(sBG + NDOF_C * NQUAD_O, NQUAD_C, NDOF_C);
auto Boo =
Reshape(sBG + NDOF_C * NQUAD_O + NDOF_C * NQUAD_C, NQUAD_O, NDOF_O);
MFEM_SHARED real_t X[3][nbz][MNQ_O * MNQ_O * (MNQ_O + 1)];
MFEM_SHARED real_t sm0[nbz * 2 * MNDQ * MNDQ * MNDQ];
MFEM_SHARED real_t sm1[nbz * 2 * MNDQ * MNDQ * MNDQ];
// shapes of buffers always use MNDQ to mitigate shared memory bank
// conflicts
real_t(*QQD)[nbz][MNDQ][MNDQ][MNDQ] =
(real_t(*)[nbz][MNDQ][MNDQ][MNDQ])(sm0);
real_t(*QDD)[nbz][MNDQ][MNDQ][MNDQ] =
(real_t(*)[nbz][MNDQ][MNDQ][MNDQ])(sm1);
real_t(*DDD)[nbz][MNDQ][MNDQ][MNDQ] =
(real_t(*)[nbz][MNDQ][MNDQ][MNDQ])(sm0);
const int offset = NDOF_O * NDOF_C * NDOF_C;
const int offsetq = NQUAD_C * NQUAD_O * NQUAD_O;
MFEM_FOREACH_THREAD_DIRECT(ix, x, offsetq)
{
for (int dim = 0; dim < 3; ++dim)
{
X[dim][tidz][ix] = X_(ix + dim * offsetq, e);
}
}
// load basis functions data
if (tidz == 0)
{
auto npts = NDOF_C * NQUAD_O + NDOF_C * NQUAD_C + NDOF_O * NQUAD_O;
MFEM_FOREACH_THREAD(ix, x, npts) { sBG[ix] = pa_data[ix]; }
}
MFEM_SYNC_THREAD;
// x: Vy Boo Bcc Gco - Vz Boo Gco Bcc
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dz, qx, qy, x, NDOF_C, NQUAD_O,
NQUAD_C, mnq, mnq - 1, mnq)
{
real_t u = 0;
for (int qz = 0; qz < NQUAD_O; ++qz)
{
u += X[1][tidz][qx + (qy + qz * NQUAD_C) * NQUAD_O] * Gco(qz, dz);
}
QQD[0][tidz][qy][qx][dz] = u;
}
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dz, qx, qy, x, NDOF_C, NQUAD_O,
NQUAD_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int qz = 0; qz < NQUAD_C; ++qz)
{
u += X[2][tidz][qx + (qy + qz * NQUAD_O) * NQUAD_O] * Bcc(qz, dz);
}
QQD[1][tidz][qy][qx][dz] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dy, dz, qx, x, NDOF_C, NDOF_C,
NQUAD_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int qy = 0; qy < NQUAD_C; ++qy)
{
u += QQD[0][tidz][qy][qx][dz] * Bcc(qy, dy);
}
QDD[0][tidz][qx][dz][dy] = u;
}
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dy, dz, qx, x, NDOF_C, NDOF_C,
NQUAD_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int qy = 0; qy < NQUAD_O; ++qy)
{
u += QQD[1][tidz][qy][qx][dz] * Gco(qy, dy);
}
QDD[1][tidz][qx][dz][dy] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dx, dy, dz, x, NDOF_O, NDOF_C,
NDOF_C, mnq - 1, mnq, mnq)
{
real_t u = 0;
for (int qx = 0; qx < NQUAD_O; ++qx)
{
u += QDD[0][tidz][qx][dz][dy] * Boo(qx, dx);
}
DDD[0][tidz][dz][dy][dx] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dx, dy, dz, x, NDOF_O, NDOF_C,
NDOF_C, mnq - 1, mnq, mnq)
{
real_t u = 0;
for (int qx = 0; qx < NQUAD_O; ++qx)
{
u += QDD[1][tidz][qx][dz][dy] * Boo(qx, dx);
}
Y(dx + (dy + dz * NDOF_C) * NDOF_O, e) =
DDD[0][tidz][dz][dy][dx] - u;
}
MFEM_SYNC_THREAD;
// y: Vz Gco Boo Bcc - Vx Bcc Boo Gco
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dz, qx, qy, x, NDOF_C, NQUAD_O,
NQUAD_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int qz = 0; qz < NQUAD_C; ++qz)
{
u += X[2][tidz][qx + (qy + qz * NQUAD_O) * NQUAD_O] * Bcc(qz, dz);
}
QQD[0][tidz][qy][qx][dz] = u;
}
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dz, qx, qy, x, NDOF_C, NQUAD_C,
NQUAD_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int qz = 0; qz < NQUAD_O; ++qz)
{
u += X[0][tidz][qx + (qy + qz * NQUAD_O) * NQUAD_C] * Gco(qz, dz);
}
QQD[1][tidz][qy][qx][dz] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dy, dz, qx, x, NDOF_O, NDOF_C,
NQUAD_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int qy = 0; qy < NQUAD_O; ++qy)
{
u += QQD[0][tidz][qy][qx][dz] * Boo(qy, dy);
}
QDD[0][tidz][qx][dz][dy] = u;
}
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dy, dz, qx, x, NDOF_O, NDOF_C,
NQUAD_C, mnq - 1, mnq, mnq)
{
real_t u = 0;
for (int qy = 0; qy < NQUAD_O; ++qy)
{
u += QQD[1][tidz][qy][qx][dz] * Boo(qy, dy);
}
QDD[1][tidz][qx][dz][dy] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dx, dy, dz, x, NDOF_C, NDOF_O,
NDOF_C, mnq, mnq - 1, mnq)
{
real_t u = 0;
for (int qx = 0; qx < NQUAD_O; ++qx)
{
u += QDD[0][tidz][qx][dz][dy] * Gco(qx, dx);
}
DDD[0][tidz][dz][dy][dx] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dx, dy, dz, x, NDOF_C, NDOF_O,
NDOF_C, mnq, mnq - 1, mnq)
{
real_t u = 0;
for (int qx = 0; qx < NQUAD_C; ++qx)
{
u += QDD[1][tidz][qx][dz][dy] * Bcc(qx, dx);
}
Y(dx + (dy + dz * NDOF_O) * NDOF_C + offset, e) =
DDD[0][tidz][dz][dy][dx] - u;
}
MFEM_SYNC_THREAD;
// z: Vx Bcc Gco Boo - Vy Gco Bcc Boo
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dz, qx, qy, x, NDOF_O, NQUAD_C,
NQUAD_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int qz = 0; qz < NQUAD_O; ++qz)
{
u += X[0][tidz][qx + (qy + qz * NQUAD_O) * NQUAD_C] * Boo(qz, dz);
}
QQD[0][tidz][qy][qx][dz] = u;
}
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dz, qx, qy, x, NDOF_O, NQUAD_O,
NQUAD_C, mnq, mnq - 1, mnq)
{
real_t u = 0;
for (int qz = 0; qz < NQUAD_O; ++qz)
{
u += X[1][tidz][qx + (qy + qz * NQUAD_C) * NQUAD_O] * Boo(qz, dz);
}
QQD[1][tidz][qy][qx][dz] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dy, dz, qx, x, NDOF_C, NDOF_O,
NQUAD_C, mnq, mnq - 1, mnq)
{
real_t u = 0;
for (int qy = 0; qy < NQUAD_O; ++qy)
{
u += QQD[0][tidz][qy][qx][dz] * Gco(qy, dy);
}
QDD[0][tidz][qx][dz][dy] = u;
}
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dy, dz, qx, x, NDOF_C, NDOF_O,
NQUAD_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int qy = 0; qy < NQUAD_C; ++qy)
{
u += QQD[1][tidz][qy][qx][dz] * Bcc(qy, dy);
}
QDD[1][tidz][qx][dz][dy] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dx, dy, dz, x, NDOF_C, NDOF_C,
NDOF_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int qx = 0; qx < NQUAD_C; ++qx)
{
u += QDD[0][tidz][qx][dz][dy] * Bcc(qx, dx);
}
DDD[0][tidz][dz][dy][dx] = u;
}
MFEM_SYNC_THREAD;
// threads assigned to mitigate bank conflicts
MFEM_FOREACH_THREAD_DIRECT_3D_OFFSET(dx, dy, dz, x, NDOF_C, NDOF_C,
NDOF_O, mnq, mnq, mnq - 1)
{
real_t u = 0;
for (int qx = 0; qx < NQUAD_O; ++qx)
{
u += QDD[1][tidz][qx][dz][dy] * Gco(qx, dx);
}
Y(dx + (dy + dz * NDOF_C) * NDOF_C + 2 * offset, e) =
DDD[0][tidz][dz][dy][dx] - u;
}
MFEM_SYNC_THREAD;
});
}
} // namespace internal
template <int DIM, int NDOF_O, int NQUAD_O>
CurlInterpolator::ApplyKernelType
CurlInterpolator::ApplyPAKernels::Kernel()
{
if constexpr (DIM == 3)
{
return internal::CurlInterpolatorApply3DSmem<NDOF_O, NQUAD_O>;
}
MFEM_ABORT("Bad dimension!");
}
template <int DIM, int NDOF_O, int NQUAD_O>
CurlInterpolator::ApplyKernelType
CurlInterpolator::ApplyTPAKernels::Kernel()
{
if constexpr (DIM == 3)
{
return internal::CurlInterpolatorTApply3DSmem<NDOF_O, NQUAD_O>;
}
MFEM_ABORT("Bad dimension!");
}
} // namespace mfem
/// \endcond DO_NOT_DOCUMENT
+136
View File
@@ -14,6 +14,8 @@
#include "../gridfunc.hpp"
#include "../qfunction.hpp"
#include "bilininteg_hcurlhdiv_kernels.hpp"
namespace mfem
{
@@ -1950,4 +1952,138 @@ void IdentityInterpolator::AddMultTransposePA(const Vector &x, Vector &y) const
}
}
void CurlInterpolator::AssemblePA(const FiniteElementSpace &dom_fes,
const FiniteElementSpace &ran_fes)
{
// TODO: 1D and 2D meshes
Mesh *mesh = dom_fes.GetMesh();
const VectorTensorFiniteElement *dom_el =
dynamic_cast<const VectorTensorFiniteElement *>(dom_fes.GetTypicalFE());
const VectorTensorFiniteElement *ran_el =
dynamic_cast<const VectorTensorFiniteElement *>(ran_fes.GetTypicalFE());
MFEM_VERIFY(dom_el != NULL, "Only VectorTensorFiniteElement is supported!");
MFEM_VERIFY(ran_el != NULL, "Only VectorTensorFiniteElement is supported!");
// only supports H(curl) -> H(div) because of discontinuity requirements
MFEM_VERIFY(dom_el->GetDerivType() == FiniteElement::CURL,
"Domain space must be H(curl)");
MFEM_VERIFY(ran_el->GetDerivType() == FiniteElement::DIV,
"Range space must be H(div)");
const int dims = dom_el->GetDim();
MFEM_VERIFY(dims == 3, "");
dim = mesh->Dimension();
ne = dom_fes.GetNE();
ndof_o = dom_el->GetOrder();
int ndof_c = ndof_o + 1;
nquad_o = ran_el->GetOrder();
int nquad_c = nquad_o + 1;
// extract the tensor product range dof locations
std::vector<real_t> qc(nquad_c);
std::vector<real_t> qo(nquad_o);
{
const IntegrationRule &ran_nodes = ran_el->GetNodes();
const Array<int> &quad_map = ran_el->GetDofMap();
for (int i = 0; i < nquad_c; ++i)
{
int idx = UnsignIndex(quad_map[i]);
qc[i] = ran_nodes.IntPoint(idx).x;
}
int offset = ndof_c * ndof_o * ndof_o;
for (int i = 0; i < nquad_o; ++i)
{
int idx = UnsignIndex(quad_map[i + offset]);
qo[i] = ran_nodes.IntPoint(idx).x;
}
}
// evaluate closed/open 1D basis (and their derivatives) at closed and
// open quads
// storage order: GCO, BCC, BOO
pa_data.SetSize(ndof_c * nquad_o + ndof_c * nquad_c + ndof_o * nquad_o);
auto ptr = pa_data.HostWrite();
auto &cbasis1d = dom_el->GetBasis1D();
auto &obasis1d = dom_el->GetOpenBasis1D();
Vector b, g;
b.SetSize(ndof_c);
g.SetSize(ndof_c);
for (int j = 0; j < nquad_o; ++j)
{
cbasis1d.Eval(qo[j], b, g);
for (int i = 0; i < ndof_c; ++i)
{
ptr[j + i * nquad_o] = g[i];
}
}
ptr += nquad_o * ndof_c;
for (int j = 0; j < nquad_c; ++j)
{
cbasis1d.Eval(qc[j], b);
for (int i = 0; i < ndof_c; ++i)
{
ptr[j + i * nquad_c] = b[i];
}
}
ptr += ndof_c * nquad_c;
b.SetSize(ndof_o);
for (int j = 0; j < nquad_o; ++j)
{
obasis1d.Eval(qo[j], b);
for (int i = 0; i < ndof_o; ++i)
{
ptr[j + i * nquad_o] = b[i];
}
}
}
CurlInterpolator::Kernels::Kernels()
{
CurlInterpolator::AddSpecialization<3, 1, 1>();
CurlInterpolator::AddSpecialization<3, 2, 2>();
CurlInterpolator::AddSpecialization<3, 3, 3>();
CurlInterpolator::AddSpecialization<3, 4, 4>();
CurlInterpolator::AddSpecialization<3, 5, 5>();
}
CurlInterpolator::CurlInterpolator() { static Kernels kernels{}; }
void CurlInterpolator::AddMultPA(const Vector &x, Vector &y) const
{
ApplyPAKernels::Run(dim, ndof_o, nquad_o, ne, ndof_o, nquad_o, pa_data, x,
y);
}
void CurlInterpolator::AddMultTransposePA(const Vector &x, Vector &y) const
{
ApplyTPAKernels::Run(dim, ndof_o, nquad_o, ne, ndof_o, nquad_o, pa_data, x,
y);
}
/// \cond DO_NOT_DOCUMENT
CurlInterpolator::ApplyKernelType
CurlInterpolator::ApplyPAKernels::Fallback(int DIM, int, int)
{
if (DIM == 3)
{
return internal::CurlInterpolatorApply3DSmem<0, 0>;
}
MFEM_ABORT("Bad dimension!");
}
CurlInterpolator::ApplyKernelType
CurlInterpolator::ApplyTPAKernels::Fallback(int DIM, int, int)
{
if (DIM == 3)
{
return internal::CurlInterpolatorTApply3DSmem<0, 0>;
}
MFEM_ABORT("Bad dimension!");
}
/// \endcond DO_NOT_DOCUMENT
} // namespace mfem
+774
View File
@@ -18,6 +18,779 @@
namespace mfem
{
namespace
{
void PAHcurlDotSetup2D(const int q1d,
const int ne,
const bool test_map_integral,
const Array<real_t> &w,
const Vector &jacobians,
const Vector &coeff,
Vector &op)
{
auto W = Reshape(w.Read(), q1d, q1d);
auto J = Reshape(jacobians.Read(), q1d, q1d, 2, 2, ne);
auto C = Reshape(coeff.Read(), 2, q1d, q1d, ne);
auto O = Reshape(op.Write(), 2, q1d, q1d, ne);
mfem::forall_2D(ne, q1d, q1d, [=] MFEM_HOST_DEVICE (int e)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
const real_t J11 = J(qx, qy, 0, 0, e);
const real_t J12 = J(qx, qy, 1, 0, e);
const real_t J21 = J(qx, qy, 0, 1, e);
const real_t J22 = J(qx, qy, 1, 1, e);
const real_t detJ = (J11 * J22) - (J21 * J12);
const real_t scale = W(qx, qy) * (test_map_integral ? 1.0 / detJ : 1.0);
const real_t Vx = C(0, qx, qy, e);
const real_t Vy = C(1, qx, qy, e);
O(0, qx, qy, e) = scale * ( J22 * Vx - J12 * Vy);
O(1, qx, qy, e) = scale * (-J21 * Vx + J11 * Vy);
}
}
});
}
void PAHcurlDotSetup3D(const int q1d,
const int ne,
const bool test_map_integral,
const Array<real_t> &w,
const Vector &jacobians,
const Vector &coeff,
Vector &op)
{
auto W = Reshape(w.Read(), q1d, q1d, q1d);
auto J = Reshape(jacobians.Read(), q1d, q1d, q1d, 3, 3, ne);
auto C = Reshape(coeff.Read(), 3, q1d, q1d, q1d, ne);
auto O = Reshape(op.Write(), 3, q1d, q1d, q1d, ne);
mfem::forall_3D(ne, q1d, q1d, q1d, [=] MFEM_HOST_DEVICE (int e)
{
MFEM_FOREACH_THREAD(qz, z, q1d)
{
MFEM_FOREACH_THREAD(qy, y, q1d)
{
MFEM_FOREACH_THREAD(qx, x, q1d)
{
const real_t J11 = J(qx, qy, qz, 0, 0, e);
const real_t J12 = J(qx, qy, qz, 0, 1, e);
const real_t J13 = J(qx, qy, qz, 0, 2, e);
const real_t J21 = J(qx, qy, qz, 1, 0, e);
const real_t J22 = J(qx, qy, qz, 1, 1, e);
const real_t J23 = J(qx, qy, qz, 1, 2, e);
const real_t J31 = J(qx, qy, qz, 2, 0, e);
const real_t J32 = J(qx, qy, qz, 2, 1, e);
const real_t J33 = J(qx, qy, qz, 2, 2, e);
const real_t detJ = J11 * (J22 * J33 - J32 * J23)
- J21 * (J12 * J33 - J32 * J13)
+ J31 * (J12 * J23 - J22 * J13);
const real_t scale = W(qx, qy, qz) *
(test_map_integral ? 1.0 / detJ : 1.0);
const real_t Vx = C(0, qx, qy, qz, e);
const real_t Vy = C(1, qx, qy, qz, e);
const real_t Vz = C(2, qx, qy, qz, e);
O(0, qx, qy, qz, e) = scale *
((J22 * J33 - J23 * J32) * Vx +
(J13 * J32 - J12 * J33) * Vy +
(J12 * J23 - J13 * J22) * Vz);
O(1, qx, qy, qz, e) = scale *
((J23 * J31 - J21 * J33) * Vx +
(J11 * J33 - J13 * J31) * Vy +
(J13 * J21 - J11 * J23) * Vz);
O(2, qx, qy, qz, e) = scale *
((J21 * J32 - J22 * J31) * Vx +
(J12 * J31 - J11 * J32) * Vy +
(J11 * J22 - J12 * J21) * Vz);
}
}
}
});
}
void PAHcurlDotApply2D(const int d1d,
const int d1d_test,
const int q1d,
const int ne,
const Array<real_t> &bo,
const Array<real_t> &bc,
const Array<real_t> &bt,
const Vector &pa_data,
const Vector &x,
Vector &y)
{
MFEM_VERIFY(d1d <= DeviceDofQuadLimits::Get().HCURL_MAX_D1D, "");
MFEM_VERIFY(d1d_test <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(q1d <= DeviceDofQuadLimits::Get().HCURL_MAX_Q1D, "");
auto Bo = Reshape(bo.Read(), q1d, d1d - 1);
auto Bc = Reshape(bc.Read(), q1d, d1d);
auto Bt = Reshape(bt.Read(), d1d_test, q1d);
auto O = Reshape(pa_data.Read(), 2, q1d, q1d, ne);
auto X = Reshape(x.Read(), 2 * (d1d - 1) * d1d, ne);
auto Y = Reshape(y.ReadWrite(), d1d_test, d1d_test, ne);
mfem::forall(ne, [=] MFEM_HOST_DEVICE (int e)
{
constexpr int MAX_D1D = DofQuadLimits::MAX_D1D;
constexpr int MAX_Q1D = DofQuadLimits::HCURL_MAX_Q1D;
real_t u0[MAX_Q1D][MAX_Q1D];
real_t u1[MAX_Q1D][MAX_Q1D];
for (int qy = 0; qy < q1d; ++qy)
{
for (int qx = 0; qx < q1d; ++qx)
{
u0[qy][qx] = 0.0;
u1[qy][qx] = 0.0;
}
}
int osc = 0;
for (int dy = 0; dy < d1d; ++dy)
{
real_t mass_x[MAX_Q1D];
for (int qx = 0; qx < q1d; ++qx) { mass_x[qx] = 0.0; }
for (int dx = 0; dx < d1d - 1; ++dx)
{
const real_t t = X(dx + (dy * (d1d - 1)) + osc, e);
for (int qx = 0; qx < q1d; ++qx) { mass_x[qx] += t * Bo(qx, dx); }
}
for (int qy = 0; qy < q1d; ++qy)
{
const real_t wy = Bc(qy, dy);
for (int qx = 0; qx < q1d; ++qx) { u0[qy][qx] += mass_x[qx] * wy; }
}
}
osc += (d1d - 1) * d1d;
for (int dy = 0; dy < d1d - 1; ++dy)
{
real_t mass_x[MAX_Q1D];
for (int qx = 0; qx < q1d; ++qx) { mass_x[qx] = 0.0; }
for (int dx = 0; dx < d1d; ++dx)
{
const real_t t = X(dx + (dy * d1d) + osc, e);
for (int qx = 0; qx < q1d; ++qx) { mass_x[qx] += t * Bc(qx, dx); }
}
for (int qy = 0; qy < q1d; ++qy)
{
const real_t wy = Bo(qy, dy);
for (int qx = 0; qx < q1d; ++qx) { u1[qy][qx] += mass_x[qx] * wy; }
}
}
for (int qy = 0; qy < q1d; ++qy)
{
real_t sol_x[MAX_D1D];
for (int dx = 0; dx < d1d_test; ++dx) { sol_x[dx] = 0.0; }
for (int qx = 0; qx < q1d; ++qx)
{
const real_t s = O(0, qx, qy, e) * u0[qy][qx]
+ O(1, qx, qy, e) * u1[qy][qx];
for (int dx = 0; dx < d1d_test; ++dx)
{
sol_x[dx] += s * Bt(dx, qx);
}
}
for (int dy = 0; dy < d1d_test; ++dy)
{
const real_t wy = Bt(dy, qy);
for (int dx = 0; dx < d1d_test; ++dx)
{
Y(dx, dy, e) += sol_x[dx] * wy;
}
}
}
});
}
void PAHcurlDotApplyTranspose2D(const int d1d,
const int d1d_test,
const int q1d,
const int ne,
const Array<real_t> &bo,
const Array<real_t> &bc,
const Array<real_t> &b,
const Vector &pa_data,
const Vector &x,
Vector &y)
{
MFEM_VERIFY(d1d <= DeviceDofQuadLimits::Get().HCURL_MAX_D1D, "");
MFEM_VERIFY(d1d_test <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(q1d <= DeviceDofQuadLimits::Get().HCURL_MAX_Q1D, "");
auto Bo = Reshape(bo.Read(), q1d, d1d - 1);
auto Bc = Reshape(bc.Read(), q1d, d1d);
auto B = Reshape(b.Read(), q1d, d1d_test);
auto O = Reshape(pa_data.Read(), 2, q1d, q1d, ne);
auto X = Reshape(x.Read(), d1d_test, d1d_test, ne);
auto Y = Reshape(y.ReadWrite(), 2 * (d1d - 1) * d1d, ne);
mfem::forall(ne, [=] MFEM_HOST_DEVICE (int e)
{
constexpr int MAX_D1D = DofQuadLimits::MAX_D1D;
constexpr int MAX_Q1D = DofQuadLimits::HCURL_MAX_Q1D;
real_t mass[MAX_Q1D][MAX_Q1D];
for (int qy = 0; qy < q1d; ++qy)
{
for (int qx = 0; qx < q1d; ++qx)
{
mass[qy][qx] = 0.0;
}
}
for (int dy = 0; dy < d1d_test; ++dy)
{
real_t sol_x[MAX_Q1D];
for (int qx = 0; qx < q1d; ++qx) { sol_x[qx] = 0.0; }
for (int dx = 0; dx < d1d_test; ++dx)
{
const real_t t = X(dx, dy, e);
for (int qx = 0; qx < q1d; ++qx) { sol_x[qx] += t * B(qx, dx); }
}
for (int qy = 0; qy < q1d; ++qy)
{
const real_t wy = B(qy, dy);
for (int qx = 0; qx < q1d; ++qx) { mass[qy][qx] += sol_x[qx] * wy; }
}
}
int osc = 0;
for (int qy = 0; qy < q1d; ++qy)
{
real_t mass_x[MAX_D1D];
for (int dx = 0; dx < d1d - 1; ++dx) { mass_x[dx] = 0.0; }
for (int qx = 0; qx < q1d; ++qx)
{
const real_t s = O(0, qx, qy, e) * mass[qy][qx];
for (int dx = 0; dx < d1d - 1; ++dx) { mass_x[dx] += s * Bo(qx, dx); }
}
for (int dy = 0; dy < d1d; ++dy)
{
const real_t wy = Bc(qy, dy);
for (int dx = 0; dx < d1d - 1; ++dx)
{
Y(dx + (dy * (d1d - 1)) + osc, e) += mass_x[dx] * wy;
}
}
}
osc += (d1d - 1) * d1d;
for (int qy = 0; qy < q1d; ++qy)
{
real_t mass_x[MAX_D1D];
for (int dx = 0; dx < d1d; ++dx) { mass_x[dx] = 0.0; }
for (int qx = 0; qx < q1d; ++qx)
{
const real_t s = O(1, qx, qy, e) * mass[qy][qx];
for (int dx = 0; dx < d1d; ++dx) { mass_x[dx] += s * Bc(qx, dx); }
}
for (int dy = 0; dy < d1d - 1; ++dy)
{
const real_t wy = Bo(qy, dy);
for (int dx = 0; dx < d1d; ++dx)
{
Y(dx + (dy * d1d) + osc, e) += mass_x[dx] * wy;
}
}
}
});
}
void PAHcurlDotApply3D(const int d1d,
const int d1d_test,
const int q1d,
const int ne,
const Array<real_t> &bo,
const Array<real_t> &bc,
const Array<real_t> &bt,
const Vector &pa_data,
const Vector &x,
Vector &y)
{
MFEM_VERIFY(d1d <= DeviceDofQuadLimits::Get().HCURL_MAX_D1D, "");
MFEM_VERIFY(d1d_test <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(q1d <= DeviceDofQuadLimits::Get().HCURL_MAX_Q1D, "");
auto Bo = Reshape(bo.Read(), q1d, d1d - 1);
auto Bc = Reshape(bc.Read(), q1d, d1d);
auto Bt = Reshape(bt.Read(), d1d_test, q1d);
auto O = Reshape(pa_data.Read(), 3, q1d, q1d, q1d, ne);
auto X = Reshape(x.Read(), 3 * (d1d - 1) * d1d * d1d, ne);
auto Y = Reshape(y.ReadWrite(), d1d_test, d1d_test, d1d_test, ne);
mfem::forall(ne, [=] MFEM_HOST_DEVICE (int e)
{
constexpr int MAX_D1D = DofQuadLimits::MAX_D1D;
constexpr int MAX_Q1D = DofQuadLimits::HCURL_MAX_Q1D;
real_t u[MAX_Q1D][MAX_Q1D][MAX_Q1D][3];
for (int qz = 0; qz < q1d; ++qz)
{
for (int qy = 0; qy < q1d; ++qy)
{
for (int qx = 0; qx < q1d; ++qx)
{
for (int c = 0; c < 3; ++c) { u[qz][qy][qx][c] = 0.0; }
}
}
}
int osc = 0;
for (int dz = 0; dz < d1d; ++dz)
{
real_t mass_xy[MAX_Q1D][MAX_Q1D];
for (int qy = 0; qy < q1d; ++qy)
{
for (int qx = 0; qx < q1d; ++qx) { mass_xy[qy][qx] = 0.0; }
}
for (int dy = 0; dy < d1d; ++dy)
{
real_t mass_x[MAX_Q1D];
for (int qx = 0; qx < q1d; ++qx) { mass_x[qx] = 0.0; }
for (int dx = 0; dx < d1d - 1; ++dx)
{
const real_t t = X(dx + ((dy + (dz * d1d)) * (d1d - 1)) + osc, e);
for (int qx = 0; qx < q1d; ++qx) { mass_x[qx] += t * Bo(qx, dx); }
}
for (int qy = 0; qy < q1d; ++qy)
{
const real_t wy = Bc(qy, dy);
for (int qx = 0; qx < q1d; ++qx) { mass_xy[qy][qx] += mass_x[qx] * wy; }
}
}
for (int qz = 0; qz < q1d; ++qz)
{
const real_t wz = Bc(qz, dz);
for (int qy = 0; qy < q1d; ++qy)
{
for (int qx = 0; qx < q1d; ++qx) { u[qz][qy][qx][0] += mass_xy[qy][qx] * wz; }
}
}
}
osc += (d1d - 1) * d1d * d1d;
for (int dz = 0; dz < d1d; ++dz)
{
real_t mass_xy[MAX_Q1D][MAX_Q1D];
for (int qy = 0; qy < q1d; ++qy)
{
for (int qx = 0; qx < q1d; ++qx) { mass_xy[qy][qx] = 0.0; }
}
for (int dy = 0; dy < d1d - 1; ++dy)
{
real_t mass_x[MAX_Q1D];
for (int qx = 0; qx < q1d; ++qx) { mass_x[qx] = 0.0; }
for (int dx = 0; dx < d1d; ++dx)
{
const real_t t = X(dx + ((dy + (dz * (d1d - 1))) * d1d) + osc, e);
for (int qx = 0; qx < q1d; ++qx) { mass_x[qx] += t * Bc(qx, dx); }
}
for (int qy = 0; qy < q1d; ++qy)
{
const real_t wy = Bo(qy, dy);
for (int qx = 0; qx < q1d; ++qx) { mass_xy[qy][qx] += mass_x[qx] * wy; }
}
}
for (int qz = 0; qz < q1d; ++qz)
{
const real_t wz = Bc(qz, dz);
for (int qy = 0; qy < q1d; ++qy)
{
for (int qx = 0; qx < q1d; ++qx) { u[qz][qy][qx][1] += mass_xy[qy][qx] * wz; }
}
}
}
osc += (d1d - 1) * d1d * d1d;
for (int dz = 0; dz < d1d - 1; ++dz)
{
real_t mass_xy[MAX_Q1D][MAX_Q1D];
for (int qy = 0; qy < q1d; ++qy)
{
for (int qx = 0; qx < q1d; ++qx) { mass_xy[qy][qx] = 0.0; }
}
for (int dy = 0; dy < d1d; ++dy)
{
real_t mass_x[MAX_Q1D];
for (int qx = 0; qx < q1d; ++qx) { mass_x[qx] = 0.0; }
for (int dx = 0; dx < d1d; ++dx)
{
const real_t t = X(dx + ((dy + (dz * d1d)) * d1d) + osc, e);
for (int qx = 0; qx < q1d; ++qx) { mass_x[qx] += t * Bc(qx, dx); }
}
for (int qy = 0; qy < q1d; ++qy)
{
const real_t wy = Bc(qy, dy);
for (int qx = 0; qx < q1d; ++qx) { mass_xy[qy][qx] += mass_x[qx] * wy; }
}
}
for (int qz = 0; qz < q1d; ++qz)
{
const real_t wz = Bo(qz, dz);
for (int qy = 0; qy < q1d; ++qy)
{
for (int qx = 0; qx < q1d; ++qx) { u[qz][qy][qx][2] += mass_xy[qy][qx] * wz; }
}
}
}
for (int qz = 0; qz < q1d; ++qz)
{
real_t mass_xy[MAX_D1D][MAX_D1D];
for (int dy = 0; dy < d1d_test; ++dy)
{
for (int dx = 0; dx < d1d_test; ++dx) { mass_xy[dy][dx] = 0.0; }
}
for (int qy = 0; qy < q1d; ++qy)
{
real_t mass_x[MAX_D1D];
for (int dx = 0; dx < d1d_test; ++dx) { mass_x[dx] = 0.0; }
for (int qx = 0; qx < q1d; ++qx)
{
const real_t s = O(0, qx, qy, qz, e) * u[qz][qy][qx][0]
+ O(1, qx, qy, qz, e) * u[qz][qy][qx][1]
+ O(2, qx, qy, qz, e) * u[qz][qy][qx][2];
for (int dx = 0; dx < d1d_test; ++dx) { mass_x[dx] += s * Bt(dx, qx); }
}
for (int dy = 0; dy < d1d_test; ++dy)
{
const real_t wy = Bt(dy, qy);
for (int dx = 0; dx < d1d_test; ++dx) { mass_xy[dy][dx] += mass_x[dx] * wy; }
}
}
for (int dz = 0; dz < d1d_test; ++dz)
{
const real_t wz = Bt(dz, qz);
for (int dy = 0; dy < d1d_test; ++dy)
{
for (int dx = 0; dx < d1d_test; ++dx)
{
Y(dx, dy, dz, e) += mass_xy[dy][dx] * wz;
}
}
}
}
});
}
void PAHcurlDotApplyTranspose3D(const int d1d,
const int d1d_test,
const int q1d,
const int ne,
const Array<real_t> &bo,
const Array<real_t> &bc,
const Array<real_t> &b,
const Vector &pa_data,
const Vector &x,
Vector &y)
{
MFEM_VERIFY(d1d <= DeviceDofQuadLimits::Get().HCURL_MAX_D1D, "");
MFEM_VERIFY(d1d_test <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(q1d <= DeviceDofQuadLimits::Get().HCURL_MAX_Q1D, "");
auto Bo = Reshape(bo.Read(), q1d, d1d - 1);
auto Bc = Reshape(bc.Read(), q1d, d1d);
auto B = Reshape(b.Read(), q1d, d1d_test);
auto O = Reshape(pa_data.Read(), 3, q1d, q1d, q1d, ne);
auto X = Reshape(x.Read(), d1d_test, d1d_test, d1d_test, ne);
auto Y = Reshape(y.ReadWrite(), 3 * (d1d - 1) * d1d * d1d, ne);
mfem::forall(ne, [=] MFEM_HOST_DEVICE (int e)
{
constexpr int MAX_D1D = DofQuadLimits::MAX_D1D;
constexpr int MAX_Q1D = DofQuadLimits::HCURL_MAX_Q1D;
real_t mass[MAX_Q1D][MAX_Q1D][MAX_Q1D];
for (int qz = 0; qz < q1d; ++qz)
{
for (int qy = 0; qy < q1d; ++qy)
{
for (int qx = 0; qx < q1d; ++qx) { mass[qz][qy][qx] = 0.0; }
}
}
for (int dz = 0; dz < d1d_test; ++dz)
{
real_t mass_xy[MAX_Q1D][MAX_Q1D];
for (int qy = 0; qy < q1d; ++qy)
{
for (int qx = 0; qx < q1d; ++qx) { mass_xy[qy][qx] = 0.0; }
}
for (int dy = 0; dy < d1d_test; ++dy)
{
real_t mass_x[MAX_Q1D];
for (int qx = 0; qx < q1d; ++qx) { mass_x[qx] = 0.0; }
for (int dx = 0; dx < d1d_test; ++dx)
{
const real_t t = X(dx, dy, dz, e);
for (int qx = 0; qx < q1d; ++qx) { mass_x[qx] += t * B(qx, dx); }
}
for (int qy = 0; qy < q1d; ++qy)
{
const real_t wy = B(qy, dy);
for (int qx = 0; qx < q1d; ++qx) { mass_xy[qy][qx] += mass_x[qx] * wy; }
}
}
for (int qz = 0; qz < q1d; ++qz)
{
const real_t wz = B(qz, dz);
for (int qy = 0; qy < q1d; ++qy)
{
for (int qx = 0; qx < q1d; ++qx) { mass[qz][qy][qx] += mass_xy[qy][qx] * wz; }
}
}
}
int osc = 0;
for (int qz = 0; qz < q1d; ++qz)
{
real_t mass_xy[MAX_D1D][MAX_D1D];
for (int dy = 0; dy < d1d; ++dy)
{
for (int dx = 0; dx < d1d - 1; ++dx) { mass_xy[dy][dx] = 0.0; }
}
for (int qy = 0; qy < q1d; ++qy)
{
real_t mass_x[MAX_D1D];
for (int dx = 0; dx < d1d - 1; ++dx) { mass_x[dx] = 0.0; }
for (int qx = 0; qx < q1d; ++qx)
{
const real_t s = O(0, qx, qy, qz, e) * mass[qz][qy][qx];
for (int dx = 0; dx < d1d - 1; ++dx) { mass_x[dx] += s * Bo(qx, dx); }
}
for (int dy = 0; dy < d1d; ++dy)
{
const real_t wy = Bc(qy, dy);
for (int dx = 0; dx < d1d - 1; ++dx) { mass_xy[dy][dx] += mass_x[dx] * wy; }
}
}
for (int dz = 0; dz < d1d; ++dz)
{
const real_t wz = Bc(qz, dz);
for (int dy = 0; dy < d1d; ++dy)
{
for (int dx = 0; dx < d1d - 1; ++dx)
{
Y(dx + ((dy + (dz * d1d)) * (d1d - 1)) + osc, e) += mass_xy[dy][dx] * wz;
}
}
}
}
osc += (d1d - 1) * d1d * d1d;
for (int qz = 0; qz < q1d; ++qz)
{
real_t mass_xy[MAX_D1D][MAX_D1D];
for (int dy = 0; dy < d1d - 1; ++dy)
{
for (int dx = 0; dx < d1d; ++dx) { mass_xy[dy][dx] = 0.0; }
}
for (int qy = 0; qy < q1d; ++qy)
{
real_t mass_x[MAX_D1D];
for (int dx = 0; dx < d1d; ++dx) { mass_x[dx] = 0.0; }
for (int qx = 0; qx < q1d; ++qx)
{
const real_t s = O(1, qx, qy, qz, e) * mass[qz][qy][qx];
for (int dx = 0; dx < d1d; ++dx) { mass_x[dx] += s * Bc(qx, dx); }
}
for (int dy = 0; dy < d1d - 1; ++dy)
{
const real_t wy = Bo(qy, dy);
for (int dx = 0; dx < d1d; ++dx) { mass_xy[dy][dx] += mass_x[dx] * wy; }
}
}
for (int dz = 0; dz < d1d; ++dz)
{
const real_t wz = Bc(qz, dz);
for (int dy = 0; dy < d1d - 1; ++dy)
{
for (int dx = 0; dx < d1d; ++dx)
{
Y(dx + ((dy + (dz * (d1d - 1))) * d1d) + osc, e) += mass_xy[dy][dx] * wz;
}
}
}
}
osc += (d1d - 1) * d1d * d1d;
for (int qz = 0; qz < q1d; ++qz)
{
real_t mass_xy[MAX_D1D][MAX_D1D];
for (int dy = 0; dy < d1d; ++dy)
{
for (int dx = 0; dx < d1d; ++dx) { mass_xy[dy][dx] = 0.0; }
}
for (int qy = 0; qy < q1d; ++qy)
{
real_t mass_x[MAX_D1D];
for (int dx = 0; dx < d1d; ++dx) { mass_x[dx] = 0.0; }
for (int qx = 0; qx < q1d; ++qx)
{
const real_t s = O(2, qx, qy, qz, e) * mass[qz][qy][qx];
for (int dx = 0; dx < d1d; ++dx) { mass_x[dx] += s * Bc(qx, dx); }
}
for (int dy = 0; dy < d1d; ++dy)
{
const real_t wy = Bc(qy, dy);
for (int dx = 0; dx < d1d; ++dx) { mass_xy[dy][dx] += mass_x[dx] * wy; }
}
}
for (int dz = 0; dz < d1d - 1; ++dz)
{
const real_t wz = Bo(qz, dz);
for (int dy = 0; dy < d1d; ++dy)
{
for (int dx = 0; dx < d1d; ++dx)
{
Y(dx + ((dy + (dz * d1d)) * d1d) + osc, e) += mass_xy[dy][dx] * wz;
}
}
}
}
});
}
} // namespace
void MixedDotProductIntegrator::AssemblePA(const FiniteElementSpace &trial_fes,
const FiniteElementSpace &test_fes)
{
Mesh *mesh = trial_fes.GetMesh();
const FiniteElement *trial_fel = trial_fes.GetTypicalFE();
const FiniteElement *test_fel = test_fes.GetTypicalFE();
const VectorTensorFiniteElement *trial_el =
dynamic_cast<const VectorTensorFiniteElement*>(trial_fel);
MFEM_VERIFY(trial_el != NULL, "Only VectorTensorFiniteElement is supported!");
const TensorBasisElement *test_tensor_el =
dynamic_cast<const TensorBasisElement*>(test_fel);
MFEM_VERIFY(test_tensor_el != NULL,
"Only tensor-product scalar test elements are supported!");
MFEM_VERIFY(trial_el->GetDerivType() == mfem::FiniteElement::CURL,
"Only H(curl) trial spaces are supported!");
const IntegrationRule *ir = IntRule;
if (ir == nullptr)
{
const int order = trial_fel->GetOrder() + test_fel->GetOrder()
+ mesh->GetTypicalElementTransformation()->OrderW();
ir = &IntRules.Get(trial_fel->GetGeomType(), order);
}
dim = mesh->Dimension();
MFEM_VERIFY(dim == 2 || dim == 3, "Unsupported dimension!");
MFEM_VERIFY(trial_el->GetDim() == dim && test_fel->GetDim() == dim,
"Trial/test dimension mismatch.");
ne = trial_fes.GetNE();
MFEM_VERIFY(ne == test_fes.GetNE(),
"Different meshes for test and trial spaces");
geom = mesh->GetGeometricFactors(*ir, GeometricFactors::JACOBIANS);
mapsC = &trial_el->GetDofToQuad(*ir, DofToQuad::TENSOR);
mapsO = &trial_el->GetDofToQuadOpen(*ir, DofToQuad::TENSOR);
mapsTest = &test_fel->GetDofToQuad(*ir, DofToQuad::TENSOR);
dofs1D = mapsC->ndof;
dofs1Dtest = mapsTest->ndof;
quad1D = mapsC->nqpt;
test_map_integral = (test_fel->GetMapType() == FiniteElement::INTEGRAL);
MFEM_VERIFY(dofs1D == mapsO->ndof + 1 && quad1D == mapsO->nqpt, "");
MFEM_VERIFY(quad1D == mapsTest->nqpt, "Trial/test quadrature mismatch");
MFEM_VERIFY(dofs1D <= DeviceDofQuadLimits::Get().HCURL_MAX_D1D, "");
MFEM_VERIFY(dofs1Dtest <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(quad1D <= DeviceDofQuadLimits::Get().HCURL_MAX_Q1D, "");
const int nq = ir->GetNPoints();
if (dim == 2) { MFEM_VERIFY(nq == quad1D * quad1D, ""); }
else { MFEM_VERIFY(nq == quad1D * quad1D * quad1D, ""); }
QuadratureSpace qs(*mesh, *ir);
CoefficientVector coeff(*VQ, qs, CoefficientStorage::FULL);
MFEM_VERIFY(coeff.GetVDim() == dim, "Vector coefficient dimension mismatch.");
pa_data.SetSize(dim * nq * ne, Device::GetMemoryType());
if (dim == 2)
{
PAHcurlDotSetup2D(quad1D, ne, test_map_integral, ir->GetWeights(),
geom->J, coeff, pa_data);
}
else
{
PAHcurlDotSetup3D(quad1D, ne, test_map_integral, ir->GetWeights(),
geom->J, coeff, pa_data);
}
}
void MixedDotProductIntegrator::AddMultPA(const Vector &x, Vector &y) const
{
if (dim == 2)
{
PAHcurlDotApply2D(dofs1D, dofs1Dtest, quad1D, ne,
mapsO->B, mapsC->B, mapsTest->Bt, pa_data, x, y);
}
else if (dim == 3)
{
PAHcurlDotApply3D(dofs1D, dofs1Dtest, quad1D, ne,
mapsO->B, mapsC->B, mapsTest->Bt, pa_data, x, y);
}
else
{
MFEM_ABORT("Unsupported dimension!");
}
}
void MixedDotProductIntegrator::AddMultTransposePA(const Vector &x,
Vector &y) const
{
if (dim == 2)
{
PAHcurlDotApplyTranspose2D(dofs1D, dofs1Dtest, quad1D, ne,
mapsO->B, mapsC->B, mapsTest->B,
pa_data, x, y);
}
else if (dim == 3)
{
PAHcurlDotApplyTranspose3D(dofs1D, dofs1Dtest, quad1D, ne,
mapsO->B, mapsC->B, mapsTest->B,
pa_data, x, y);
}
else
{
MFEM_ABORT("Unsupported dimension!");
}
}
void MixedScalarCurlIntegrator::AssemblePA(const FiniteElementSpace &trial_fes,
const FiniteElementSpace &test_fes)
{
@@ -320,6 +1093,7 @@ void MixedVectorWeakCurlIntegrator::AssemblePA(const FiniteElementSpace
CoefficientVector coeff(qs, CoefficientStorage::FULL);
if (Q) { coeff.Project(*Q); }
else if (DQ) { coeff.Project(*DQ); }
else if (MQ) { MFEM_ABORT("Not implemented."); }
else { coeff.SetConstant(1.0); }
if (trialType == mfem::FiniteElement::CURL && dim == 3)
File diff suppressed because it is too large Load Diff
-365
View File
@@ -1,365 +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 "../../config/config.hpp"
#include "../../general/array.hpp"
#include "../../general/forall.hpp"
#include "../../linalg/dtensor.hpp"
#include "../../linalg/vector.hpp"
#include "../bilininteg.hpp"
#include "../kernels.hpp"
namespace mfem
{
/// \cond DO_NOT_DOCUMENT
namespace internal
{
// Shared memory PA Divergence Apply 2D kernel
template<int T_TR_D1D = 0, int T_TE_D1D = 0, int T_Q1D = 0>
inline void SmemPADivergenceApply2D(const int NE,
const Array<real_t> &b_,
const Array<real_t> &g_,
const Array<real_t> &bt_,
const Vector &q_,
const Vector &x_,
Vector &y_,
const int tr_d1d = 0,
const int te_d1d = 0,
const int q1d = 0)
{
const int TR_D1D = T_TR_D1D ? T_TR_D1D : tr_d1d;
const int TE_D1D = T_TE_D1D ? T_TE_D1D : te_d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
MFEM_VERIFY(TR_D1D <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(TE_D1D <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(Q1D <= DeviceDofQuadLimits::Get().MAX_Q1D, "");
const auto B = b_.Read(), G = g_.Read(), Bt = bt_.Read();
const auto Q = Reshape(q_.Read(), Q1D, Q1D, 2, 2, NE);
const auto X = Reshape(x_.Read(), TR_D1D, TR_D1D, 2, NE);
auto Y = Reshape(y_.ReadWrite(), TE_D1D, TE_D1D, 1, NE);
mfem::forall_2D<T_Q1D * T_Q1D>(NE, Q1D, Q1D, [=] MFEM_HOST_DEVICE (int e)
{
constexpr int MQ1 = T_Q1D ? T_Q1D : DofQuadLimits::MAX_Q1D;
MFEM_SHARED real_t smem[MQ1][MQ1];
MFEM_SHARED real_t sB[MQ1][MQ1], sG[MQ1][MQ1];
kernels::internal::vd_regs2d_t<2, 2, MQ1> g0, g1;
kernels::internal::v_regs2d_t<1, MQ1> r0, r1;
kernels::internal::LoadMatrix(TR_D1D, Q1D, B, sB);
kernels::internal::LoadMatrix(TR_D1D, Q1D, G, sG);
kernels::internal::LoadDofs2d(e, TR_D1D, X, g0);
kernels::internal::Grad2d(TR_D1D, Q1D, smem, sB, sG, g0, g1);
MFEM_FOREACH_THREAD_DIRECT(qy, y, Q1D)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, Q1D)
{
r0[0][qy][qx] =
g1[0][0][qy][qx] * Q(qx, qy, 0, 0, e) +
g1[0][1][qy][qx] * Q(qx, qy, 1, 0, e) +
g1[1][0][qy][qx] * Q(qx, qy, 0, 1, e) +
g1[1][1][qy][qx] * Q(qx, qy, 1, 1, e);
}
}
MFEM_SYNC_THREAD;
kernels::internal::LoadMatrix<MQ1,true>(TE_D1D, Q1D, Bt, sB);
kernels::internal::EvalTranspose2d(TE_D1D, Q1D, smem, sB, r0, r1);
kernels::internal::WriteDofs2d(e, TE_D1D, r1, Y);
});
}
// Shared memory PA Divergence Apply 2D kernel transpose
template<int T_TR_D1D = 0, int T_TE_D1D = 0, int T_Q1D = 0>
inline void SmemPADivergenceApplyTranspose2D(const int NE,
const Array<real_t> &bt,
const Array<real_t> &gt,
const Array<real_t> &b,
const Vector &q_,
const Vector &x_,
Vector &y_,
const int tr_d1d = 0,
const int te_d1d = 0,
const int q1d = 0)
{
const int TR_D1D = T_TR_D1D ? T_TR_D1D : tr_d1d;
const int TE_D1D = T_TE_D1D ? T_TE_D1D : te_d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
MFEM_VERIFY(TR_D1D <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(TE_D1D <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(Q1D <= DeviceDofQuadLimits::Get().MAX_Q1D, "");
const auto Bt = bt.Read(), Gt = gt.Read(), B = b.Read();
const auto Q = Reshape(q_.Read(), Q1D, Q1D, 2, 2, NE);
const auto X = Reshape(x_.Read(), TE_D1D, TE_D1D, 1, NE);
auto Y = Reshape(y_.ReadWrite(), TR_D1D, TR_D1D, 2, NE);
mfem::forall_2D<T_Q1D * T_Q1D>(NE, Q1D, Q1D, [=] MFEM_HOST_DEVICE (int e)
{
constexpr int MQ1 = T_Q1D ? T_Q1D : DofQuadLimits::MAX_Q1D;
MFEM_SHARED real_t smem[MQ1][MQ1];
MFEM_SHARED real_t sB[MQ1][MQ1], sG[MQ1][MQ1];
kernels::internal::v_regs2d_t<1, MQ1> r0, r1;
kernels::internal::vd_regs2d_t<2, 2, MQ1> g0, g1;
kernels::internal::LoadMatrix(TE_D1D, Q1D, B, sB);
kernels::internal::LoadDofs2d(e, TE_D1D, X, r0);
kernels::internal::Eval2d(TE_D1D, Q1D, smem, sB, r0, r1);
MFEM_FOREACH_THREAD_DIRECT(qy, y, Q1D)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, Q1D)
{
g0[0][0][qy][qx] = r1[0][qy][qx] * Q(qx, qy, 0, 0, e);
g0[0][1][qy][qx] = r1[0][qy][qx] * Q(qx, qy, 1, 0, e);
g0[1][0][qy][qx] = r1[0][qy][qx] * Q(qx, qy, 0, 1, e);
g0[1][1][qy][qx] = r1[0][qy][qx] * Q(qx, qy, 1, 1, e);
}
}
MFEM_SYNC_THREAD;
kernels::internal::LoadMatrix<MQ1,true>(TR_D1D, Q1D, Bt, sB);
kernels::internal::LoadMatrix<MQ1,true>(TR_D1D, Q1D, Gt, sG);
kernels::internal::GradTranspose2d(TR_D1D, Q1D, smem, sB, sG, g0, g1);
kernels::internal::WriteDofs2d(e, TR_D1D, g1, Y);
});
}
// Shared memory PA Divergence Apply 3D kernel transpose
template<int T_TR_D1D = 0, int T_TE_D1D = 0, int T_Q1D = 0>
inline void SmemPADivergenceApplyTranspose3D(const int NE,
const Array<real_t> &bt,
const Array<real_t> &gt,
const Array<real_t> &b,
const Vector &q_,
const Vector &x_,
Vector &y_,
int tr_d1d = 0,
int te_d1d = 0,
int q1d = 0)
{
const int TR_D1D = T_TR_D1D ? T_TR_D1D : tr_d1d;
const int TE_D1D = T_TE_D1D ? T_TE_D1D : te_d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
MFEM_VERIFY(TR_D1D <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(TE_D1D <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(Q1D <= DeviceDofQuadLimits::Get().MAX_Q1D, "");
const auto Bt = bt.Read(), Gt = gt.Read(), B = b.Read();
const auto Q = Reshape(q_.Read(), Q1D, Q1D, Q1D, 3, 3, NE);
const auto X = Reshape(x_.Read(), TE_D1D, TE_D1D, TE_D1D, 1, NE);
auto Y = Reshape(y_.ReadWrite(), TR_D1D, TR_D1D, TR_D1D, 3, NE);
mfem::forall_2D<T_Q1D * T_Q1D>(NE, Q1D, Q1D, [=] MFEM_HOST_DEVICE (int e)
{
constexpr int MQ1 = T_Q1D ? T_Q1D : DofQuadLimits::MAX_Q1D;
MFEM_SHARED real_t smem[MQ1][MQ1];
MFEM_SHARED real_t sB[MQ1][MQ1], sG[MQ1][MQ1];
kernels::internal::v_regs3d_t<1, MQ1> r0, r1;
kernels::internal::vd_regs3d_t<3, 3, MQ1> g0, g1;
kernels::internal::LoadMatrix(TE_D1D, Q1D, B, sB);
kernels::internal::LoadDofs3d(e, TE_D1D, X, r0);
kernels::internal::Eval3d(TE_D1D, Q1D, smem, sB, r0, r1);
for (int qz = 0; qz < Q1D; qz++)
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, Q1D)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, Q1D)
{
const auto r = r1[0][qz][qy][qx];
g0[0][0][qz][qy][qx] = r * Q(qx, qy, qz, 0, 0, e);
g0[0][1][qz][qy][qx] = r * Q(qx, qy, qz, 1, 0, e);
g0[0][2][qz][qy][qx] = r * Q(qx, qy, qz, 2, 0, e);
g0[1][0][qz][qy][qx] = r * Q(qx, qy, qz, 0, 1, e);
g0[1][1][qz][qy][qx] = r * Q(qx, qy, qz, 1, 1, e);
g0[1][2][qz][qy][qx] = r * Q(qx, qy, qz, 2, 1, e);
g0[2][0][qz][qy][qx] = r * Q(qx, qy, qz, 0, 2, e);
g0[2][1][qz][qy][qx] = r * Q(qx, qy, qz, 1, 2, e);
g0[2][2][qz][qy][qx] = r * Q(qx, qy, qz, 2, 2, e);
}
}
}
MFEM_SYNC_THREAD;
kernels::internal::LoadMatrix<MQ1,true>(TR_D1D, Q1D, Bt, sB);
kernels::internal::LoadMatrix<MQ1,true>(TR_D1D, Q1D, Gt, sG);
kernels::internal::GradTranspose3d(TR_D1D, Q1D, smem, sB, sG, g0, g1);
kernels::internal::WriteDofs3d(e, TR_D1D, g1, Y);
});
}
// Shared memory PA Divergence Apply 3D kernel
template<int T_TR_D1D = 0, int T_TE_D1D = 0, int T_Q1D = 0>
inline void SmemPADivergenceApply3D(const int NE,
const Array<real_t> &b_,
const Array<real_t> &g_,
const Array<real_t> &bt_,
const Vector &q_,
const Vector &x_,
Vector &y_,
const int tr_d1d = 0,
const int te_d1d = 0,
const int q1d = 0)
{
const int TR_D1D = T_TR_D1D ? T_TR_D1D : tr_d1d;
const int TE_D1D = T_TE_D1D ? T_TE_D1D : te_d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
MFEM_VERIFY(TR_D1D <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(TE_D1D <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(Q1D <= DeviceDofQuadLimits::Get().MAX_Q1D, "");
const auto B = b_.Read(), G = g_.Read(), Bt = bt_.Read();
const auto Q = Reshape(q_.Read(), Q1D, Q1D, Q1D, 3,3, NE);
const auto X = Reshape(x_.Read(), TR_D1D, TR_D1D, TR_D1D, 3, NE);
auto Y = Reshape(y_.ReadWrite(), TE_D1D, TE_D1D, TE_D1D, 1, NE);
mfem::forall_2D<T_Q1D*T_Q1D>(NE, Q1D, Q1D, [=] MFEM_HOST_DEVICE(int e)
{
constexpr int MQ1 = T_Q1D ? T_Q1D : DofQuadLimits::MAX_Q1D;
MFEM_SHARED real_t smem[MQ1][MQ1];
MFEM_SHARED real_t sB[MQ1][MQ1], sG[MQ1][MQ1];
kernels::internal::vd_regs3d_t<3, 3, MQ1> g0, g1;
kernels::internal::v_regs3d_t<1, MQ1> r0, r1;
kernels::internal::LoadMatrix(TR_D1D, Q1D, B, sB);
kernels::internal::LoadMatrix(TR_D1D, Q1D, G, sG);
kernels::internal::LoadDofs3d(e, TR_D1D, X, g0);
kernels::internal::Grad3d(TR_D1D, Q1D, smem, sB, sG, g0, g1);
for (int qz = 0; qz < Q1D; qz++)
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, Q1D)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, Q1D)
{
r0[0][qz][qy][qx] =
// c = 0
g1[0][0][qz][qy][qx] * Q(qx, qy, qz, 0, 0, e) +
g1[0][1][qz][qy][qx] * Q(qx, qy, qz, 1, 0, e) +
g1[0][2][qz][qy][qx] * Q(qx, qy, qz, 2, 0, e) +
// c = 1
g1[1][0][qz][qy][qx] * Q(qx, qy, qz, 0, 1, e) +
g1[1][1][qz][qy][qx] * Q(qx, qy, qz, 1, 1, e) +
g1[1][2][qz][qy][qx] * Q(qx, qy, qz, 2, 1, e) +
// c = 2
g1[2][0][qz][qy][qx] * Q(qx, qy, qz, 0, 2, e) +
g1[2][1][qz][qy][qx] * Q(qx, qy, qz, 1, 2, e) +
g1[2][2][qz][qy][qx] * Q(qx, qy, qz, 2, 2, e);
}
}
}
MFEM_SYNC_THREAD;
kernels::internal::LoadMatrix<MQ1, true>(TE_D1D, Q1D, Bt, sB);
kernels::internal::EvalTranspose3d(TE_D1D, Q1D, smem, sB, r0, r1);
kernels::internal::WriteDofs3d(e, TE_D1D, r1, Y);
});
}
} // namespace internal
template<int DIM, int T_TR_D1D, int T_TE_D1D, int T_Q1D>
VectorDivergenceIntegrator::VectorDivergenceAddMultPAType
VectorDivergenceIntegrator::VectorDivergenceAddMultPA::Kernel()
{
static_assert(T_TR_D1D <= T_Q1D && T_TE_D1D <= T_Q1D);
if constexpr (DIM == 2)
{
return internal::SmemPADivergenceApply2D<T_TR_D1D, T_TE_D1D, T_Q1D>;
}
else if constexpr (DIM == 3)
{
return internal::SmemPADivergenceApply3D<T_TR_D1D, T_TE_D1D, T_Q1D>;
}
MFEM_ABORT("Unsupported kernel");
}
inline VectorDivergenceIntegrator::VectorDivergenceAddMultPAType
VectorDivergenceIntegrator::VectorDivergenceAddMultPA::Fallback
(int dim, int tr_d1d, int te_d1d, int q1d)
{
MFEM_VERIFY(tr_d1d <= q1d && te_d1d <= q1d, "");
MFEM_VERIFY(tr_d1d <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(te_d1d <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(q1d <= DeviceDofQuadLimits::Get().MAX_Q1D, "");
if (dim == 2)
{
return internal::SmemPADivergenceApply2D;
}
else if (dim == 3)
{
return internal::SmemPADivergenceApply3D;
}
MFEM_ABORT("Unsupported kernel");
}
template<int DIM, int T_TR_D1D, int T_TE_D1D, int T_Q1D>
VectorDivergenceIntegrator::VectorDivergenceAddMultTransposePAType
VectorDivergenceIntegrator::VectorDivergenceAddMultTransposePA::Kernel()
{
static_assert(T_TR_D1D <= T_Q1D && T_TE_D1D <= T_Q1D);
if constexpr (DIM == 2)
{
return internal::SmemPADivergenceApplyTranspose2D<T_TR_D1D, T_TE_D1D, T_Q1D>;
}
else if constexpr (DIM == 3)
{
return internal::SmemPADivergenceApplyTranspose3D<T_TR_D1D, T_TE_D1D, T_Q1D>;
}
MFEM_ABORT("Unsupported kernel");
}
inline VectorDivergenceIntegrator::VectorDivergenceAddMultTransposePAType
VectorDivergenceIntegrator::VectorDivergenceAddMultTransposePA::Fallback
(int dim, int tr_d1d, int te_d1d, int q1d)
{
MFEM_VERIFY(tr_d1d <= q1d && te_d1d <= q1d, "");
MFEM_VERIFY(tr_d1d <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(te_d1d <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(q1d <= DeviceDofQuadLimits::Get().MAX_Q1D, "");
if (dim == 2)
{
return internal::SmemPADivergenceApplyTranspose2D;
}
else if (dim == 3)
{
return internal::SmemPADivergenceApplyTranspose3D;
}
MFEM_ABORT("Unsupported kernel");
}
/// \endcond DO_NOT_DOCUMENT
} // namespace mfem
+149 -32
View File
@@ -205,40 +205,157 @@ void VectorMassIntegrator::AddMultPA(const Vector &x, Vector &y) const
}
template <const int T_D1D = 0, const int T_Q1D = 0>
static void PAVectorMassAssembleDiagonal2D(const int NE,
const Array<real_t> &b,
const Vector &pa_data, Vector &diag,
const int d1d = 0, const int q1d = 0)
{
constexpr int VDIM = 2;
const int D1D = T_D1D ? T_D1D : d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
MFEM_VERIFY(D1D <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(Q1D <= DeviceDofQuadLimits::Get().MAX_Q1D, "");
const auto B = Reshape(b.Read(), Q1D, D1D);
const auto D = Reshape(pa_data.Read(), Q1D, Q1D, NE);
auto Y = Reshape(diag.ReadWrite(), D1D, D1D, VDIM, NE);
mfem::forall(NE, [=] MFEM_HOST_DEVICE(int e)
{
const int D1D = T_D1D ? T_D1D : d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
constexpr int max_D1D = T_D1D ? T_D1D : DofQuadLimits::MAX_D1D;
constexpr int max_Q1D = T_Q1D ? T_Q1D : DofQuadLimits::MAX_Q1D;
real_t temp[max_Q1D][max_D1D];
for (int qx = 0; qx < Q1D; ++qx)
{
for (int dy = 0; dy < D1D; ++dy)
{
temp[qx][dy] = 0.0;
for (int qy = 0; qy < Q1D; ++qy)
{
temp[qx][dy] += B(qy, dy) * B(qy, dy) * D(qx, qy, e);
}
}
}
for (int dy = 0; dy < D1D; ++dy)
{
for (int dx = 0; dx < D1D; ++dx)
{
real_t temp1 = 0.0;
for (int qx = 0; qx < Q1D; ++qx)
{
temp1 += B(qx, dx) * B(qx, dx) * temp[qx][dy];
}
Y(dx, dy, 0, e) = temp1;
Y(dx, dy, 1, e) = temp1;
}
}
});
}
template <const int T_D1D = 0, const int T_Q1D = 0>
static void PAVectorMassAssembleDiagonal3D(const int NE,
const Array<real_t> &B_,
const Vector &pa_data, Vector &diag,
const int d1d = 0, const int q1d = 0)
{
constexpr int VDIM = 3;
const int D1D = T_D1D ? T_D1D : d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
MFEM_VERIFY(D1D <= DeviceDofQuadLimits::Get().MAX_D1D, "");
MFEM_VERIFY(Q1D <= DeviceDofQuadLimits::Get().MAX_Q1D, "");
const auto B = Reshape(B_.Read(), Q1D, D1D);
MFEM_VERIFY(pa_data.Size() == Q1D * Q1D * Q1D * NE, "pa_data size error");
const auto D = Reshape(pa_data.Read(), Q1D, Q1D, Q1D, NE);
auto Y = Reshape(diag.ReadWrite(), D1D, D1D, D1D, VDIM, NE);
mfem::forall(NE, [=] MFEM_HOST_DEVICE(int e)
{
const int D1D = T_D1D ? T_D1D : d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
// the following variables are evaluated at compile time
constexpr int max_D1D = T_D1D ? T_D1D : DofQuadLimits::MAX_D1D;
constexpr int max_Q1D = T_Q1D ? T_Q1D : DofQuadLimits::MAX_Q1D;
real_t temp[max_Q1D][max_Q1D][max_D1D];
for (int qx = 0; qx < Q1D; ++qx)
{
for (int qy = 0; qy < Q1D; ++qy)
{
for (int dz = 0; dz < D1D; ++dz)
{
temp[qx][qy][dz] = 0.0;
for (int qz = 0; qz < Q1D; ++qz)
{
temp[qx][qy][dz] +=
B(qz, dz) * B(qz, dz) * D(qx, qy, qz, e);
}
}
}
}
real_t temp2[max_Q1D][max_D1D][max_D1D];
for (int qx = 0; qx < Q1D; ++qx)
{
for (int dz = 0; dz < D1D; ++dz)
{
for (int dy = 0; dy < D1D; ++dy)
{
temp2[qx][dy][dz] = 0.0;
for (int qy = 0; qy < Q1D; ++qy)
{
temp2[qx][dy][dz] +=
B(qy, dy) * B(qy, dy) * temp[qx][qy][dz];
}
}
}
}
for (int dz = 0; dz < D1D; ++dz)
{
for (int dy = 0; dy < D1D; ++dy)
{
for (int dx = 0; dx < D1D; ++dx)
{
real_t temp3 = 0.0;
for (int qx = 0; qx < Q1D; ++qx)
{
temp3 += B(qx, dx) * B(qx, dx) * temp2[qx][dy][dz];
}
Y(dx, dy, dz, 0, e) = temp3;
Y(dx, dy, dz, 1, e) = temp3;
Y(dx, dy, dz, 2, e) = temp3;
}
}
}
});
}
static void PAVectorMassAssembleDiagonal(const int dim, const int D1D,
const int Q1D, const int NE,
const Array<real_t> &B,
const Vector &pa_data,
Vector &diag)
{
if (dim == 2)
{
return PAVectorMassAssembleDiagonal2D(NE, B, pa_data, diag, D1D, Q1D);
}
else if (dim == 3)
{
return PAVectorMassAssembleDiagonal3D(NE, B, pa_data, diag, D1D, Q1D);
}
MFEM_ABORT("Dimension not implemented.");
}
void VectorMassIntegrator::AssembleDiagonalPA(Vector &diag)
{
if (DeviceCanUseCeed()) { return ceedOp->GetDiagonal(diag); }
MFEM_VERIFY(coeff_vdim == 1, "coeff_vdim != 1");
MFEM_VERIFY(!VQ && !MQ, "VQ and MQ not supported");
// Add the VectorMassAssembleDiagonalPA specializations
static const auto vector_mass_assemble_diagonal_kernel_specializations =
( // 2D
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Specialization<2, 2>::Add(),
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Specialization<2, 3>::Add(),
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Specialization<2, 4>::Add(),
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Specialization<2, 5>::Add(),
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Specialization<2, 6>::Add(),
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Specialization<2, 7>::Add(),
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Specialization<2, 8>::Add(),
// 3D
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Specialization<3, 2>::Add(),
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Specialization<3, 3>::Add(),
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Specialization<3, 4>::Add(),
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Specialization<3, 5>::Add(),
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Specialization<3, 6>::Add(),
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Specialization<3, 7>::Add(),
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Specialization<3, 8>::Add(),
true);
MFEM_CONTRACT_VAR(vector_mass_assemble_diagonal_kernel_specializations);
VectorMassAssembleDiagonalPA::Run(dim, quad1D, // templated arguments
ne, dofs1D, quad1D,
maps->B.Read(),
pa_data.Read(),
diag.ReadWrite());
if (DeviceCanUseCeed()) { ceedOp->GetDiagonal(diag); }
else
{
MFEM_VERIFY(coeff_vdim == 1, "coeff_vdim != 1");
MFEM_VERIFY(!VQ && !MQ, "VQ and MQ not supported");
PAVectorMassAssembleDiagonal(dim, dofs1D, quad1D, ne, maps->B, pa_data, diag);
}
}
} // namespace mfem
+2 -170
View File
@@ -176,146 +176,8 @@ void SmemPAVectorMassApply3D(const int NE,
});
}
template <int T_Q1D = 0, int T_MDQ = 16>
static void SmemPAVectorMassAssembleDiagonal2D(const int ne,
const int d1d,
const int q1d,
const real_t *b_r,
const real_t *d_r,
real_t *y_rw)
{
constexpr int VDIM = 2;
const int D1D = d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
MFEM_VERIFY(Q1D <= T_MDQ && D1D <= Q1D, "");
const auto B = Reshape(b_r, Q1D, D1D);
const auto D = Reshape(d_r, Q1D, Q1D, ne);
auto Y = Reshape(y_rw, D1D, D1D, VDIM, ne);
mfem::forall_2D<T_Q1D*T_Q1D>(
ne, Q1D, Q1D, [=] MFEM_HOST_DEVICE(int e)
{
constexpr int MQ1 = T_Q1D ? T_Q1D : T_MDQ;
MFEM_SHARED real_t sm[MQ1][MQ1];
MFEM_FOREACH_THREAD_DIRECT(qx, x, Q1D)
{
MFEM_FOREACH_THREAD_DIRECT(dy, y, D1D)
{
real_t u = 0.0;
for (int qy = 0; qy < Q1D; ++qy)
{
u += B(qy, dy) * B(qy, dy) * D(qx, qy, e);
}
sm[qx][dy] = u;
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD_DIRECT(dy, y, D1D)
{
MFEM_FOREACH_THREAD_DIRECT(dx, x, D1D)
{
real_t u = 0.0;
for (int qx = 0; qx < Q1D; ++qx)
{
u += B(qx, dx) * B(qx, dx) * sm[qx][dy];
}
Y(dx, dy, 0, e) += u;
Y(dx, dy, 1, e) += u;
}
}
});
}
// T_MDQ <= 10 so the Q1D^3 thread block stays within the 1024/block GPU limit
template <int T_Q1D = 0, int T_MDQ = 10>
static void SmemPAVectorMassAssembleDiagonal3D(const int ne,
const int d1d,
const int q1d,
const real_t *b_r,
const real_t *d_r,
real_t *y_rw)
{
constexpr int VDIM = 3;
const int D1D = d1d;
const int Q1D = T_Q1D ? T_Q1D : q1d;
MFEM_VERIFY(Q1D <= T_MDQ && D1D <= Q1D, "");
const auto B = Reshape(b_r, Q1D, D1D);
const auto D = Reshape(d_r, Q1D, Q1D, Q1D, ne);
auto Y = Reshape(y_rw, D1D, D1D, D1D, VDIM, ne);
mfem::forall_3D<T_Q1D*T_Q1D*T_Q1D>(
ne, Q1D, Q1D, Q1D, [=] MFEM_HOST_DEVICE(int e)
{
constexpr int MQ1 = T_Q1D ? T_Q1D : T_MDQ;
MFEM_SHARED real_t sm[2][MQ1][MQ1][MQ1];
MFEM_FOREACH_THREAD_DIRECT(dz, z, D1D)
{
MFEM_FOREACH_THREAD_DIRECT(qy, y, Q1D)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, Q1D)
{
real_t u = 0.0;
for (int qz = 0; qz < Q1D; ++qz)
{
u += B(qz, dz) * B(qz, dz) * D(qx, qy, qz, e);
}
sm[0][dz][qy][qx] = u;
}
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD_DIRECT(dz, z, D1D)
{
MFEM_FOREACH_THREAD_DIRECT(qx, x, Q1D)
{
MFEM_FOREACH_THREAD_DIRECT(dy, y, D1D)
{
real_t u = 0.0;
for (int qy = 0; qy < Q1D; ++qy)
{
u += B(qy, dy) * B(qy, dy) * sm[0][dz][qy][qx];
}
sm[1][dz][dy][qx] = u;
}
}
}
MFEM_SYNC_THREAD;
MFEM_FOREACH_THREAD_DIRECT(dz, z, D1D)
{
MFEM_FOREACH_THREAD_DIRECT(dy, y, D1D)
{
MFEM_FOREACH_THREAD_DIRECT(dx, x, D1D)
{
real_t u = 0.0;
for (int qx = 0; qx < Q1D; ++qx)
{
u += B(qx, dx) * B(qx, dx) * sm[1][dz][dy][qx];
}
Y(dx, dy, dz, 0, e) += u;
Y(dx, dy, dz, 1, e) += u;
Y(dx, dy, dz, 2, e) += u;
}
}
}
});
}
} // namespace internal
// AddMultPA kernels
template<int DIM, int T_D1D, int T_Q1D>
VectorMassIntegrator::VectorMassAddMultPAType
VectorMassIntegrator::VectorMassAddMultPA::Kernel()
@@ -332,7 +194,7 @@ VectorMassIntegrator::VectorMassAddMultPA::Kernel()
}
inline VectorMassIntegrator::VectorMassAddMultPAType
VectorMassIntegrator::VectorMassAddMultPA::Fallback(int dim, int, int)
VectorMassIntegrator::VectorMassAddMultPA::Fallback(int dim, int d1d, int q1d)
{
if (dim == 2)
{
@@ -342,37 +204,7 @@ VectorMassIntegrator::VectorMassAddMultPA::Fallback(int dim, int, int)
{
return internal::SmemPAVectorMassApply3D;
}
MFEM_ABORT("Unsupported kernel");
}
// DiagonalPA kernels
template<int DIM, int T_Q1D>
VectorMassIntegrator::VectorMassAssembleDiagonalPAType
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Kernel()
{
if constexpr (DIM == 2)
{
return internal::SmemPAVectorMassAssembleDiagonal2D<T_Q1D>;
}
else if constexpr (DIM == 3)
{
return internal::SmemPAVectorMassAssembleDiagonal3D<T_Q1D>;
}
MFEM_ABORT("Unsupported kernel");
}
inline VectorMassIntegrator::VectorMassAssembleDiagonalPAType
VectorMassIntegrator::VectorMassAssembleDiagonalPA::Fallback(int dim, int)
{
if (dim == 2)
{
return internal::SmemPAVectorMassAssembleDiagonal2D;
}
else if (dim == 3)
{
return internal::SmemPAVectorMassAssembleDiagonal3D;
}
MFEM_ABORT("Unsupported kernel");
else { MFEM_ABORT("Unsupported kernel"); }
}
/// \endcond DO_NOT_DOCUMENT

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