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Author SHA1 Message Date
camierjs de1fb677b3 Cleanup 2025-04-05 13:09:03 -07:00
camierjs e475646fa5 Pre cleanup 2025-04-05 11:38:30 -07:00
camierjs c626ee6d5e dOp Mult with y residual_l tvectors 2025-04-05 11:22:20 -07:00
camierjs b09b2374fc WIP R, P, use tvectors 2025-04-05 10:14:54 -07:00
camierjs 57097c1591 Bring back rho 2025-04-04 18:53:46 -07:00
camierjs 93fde1d263 First dFEM MF sync 2025-04-04 18:47:56 -07:00
camierjs 4b110894fc Add domain attr size check
Serial DFEM diffusion tests
2025-04-04 13:25:30 -07:00
camierjs de7b80ce67 Merge branch 'dfem-phase1-dev' of github.com:mfem/mfem into dfem-phase1-dev 2025-04-03 18:29:34 -07:00
camierjs 5c7503466c Add FunctionCoefficient to dfem diffusion tests 2025-04-03 18:29:09 -07:00
Julian Andrej 6b2658bb7b fixed a few bugs in parallel implicit 2025-04-03 14:47:18 -07:00
camierjs c319b8fa04 Add dfem unit test diffusion 2025-04-03 14:22:00 -07:00
Julian Andrej 8ba1f17f72 add nonlinear solver options to command line arguments 2025-04-03 11:01:31 -07:00
Julian Andrej e5f5a79e66 attempt to fix parametric function transfers 2025-04-03 08:19:53 -07:00
Julian Andrej 43f1b19767 switch to 2d by default 2025-04-03 08:19:32 -07:00
Julian Andrej 7bebe4528f stop printing dependency maps 2025-04-03 08:19:16 -07:00
camierjs da63657cdd GCC warning fixes 2025-04-02 18:40:57 -07:00
camierjs ee7d9726df Warnings & fixes 2025-04-02 18:34:08 -07:00
Julian Andrej 5657f6ebe8 Merge branch 'dfem-phase1-dev' of github.com:mfem/mfem into dfem-phase1-dev 2025-04-02 17:44:22 -07:00
Julian Andrej 19543b6b16 more device stuff 2025-04-02 17:41:57 -07:00
camierjs b56e994ecd Copyright header, includes trim & warning fixes 2025-04-02 17:20:29 -07:00
Julian Andrej ae8e5aa88d some device stuff 2025-04-02 16:21:18 -07:00
Julian Andrej 08f3c86b8a make attributes device compatible 2025-04-02 15:46:19 -07:00
camierjs 52bc915120 Few fixes to run on device and removed warnings 2025-04-02 12:07:57 -07:00
Julian Andrej e66a61c198 add build instructions 2025-03-31 17:23:33 -07:00
Julian Andrej f8b3c78b19 tensor additions 2025-03-31 14:28:29 -07:00
Julian Andrej 4749746171 add laghos 2025-03-31 14:28:10 -07:00
Julian Andrej 11fce4235b revert width determination 2025-03-28 08:16:26 -07:00
Julian Andrej fd341e07da example 2025-03-21 15:54:58 -07:00
Julian Andrej d59e2a229c phase 1 skeleton 2025-03-21 15:54:18 -07:00
24 changed files with 9044 additions and 15 deletions
+7 -2
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@@ -526,9 +526,11 @@ if (MFEM_USE_TRIBOL)
endif()
endif()
# Enzyme
if (MFEM_USE_ENZYME)
find_package(ENZYME REQUIRED)
find_package(Enzyme REQUIRED HINTS ${ENZYME_DIR})
message(STATUS "Enzyme found in ${ENZYME_DIR}.")
set(ENZYME_INCLUDE_DIRS ${ENZYME_DIR}/include)
set(ENZYME_FOUND 1)
endif()
# MFEM_TIMER_TYPE
@@ -680,6 +682,9 @@ if (MFEM_USE_MPI)
target_link_libraries(mfem PUBLIC ${MPI_CXX_LINK_FLAGS})
endif()
endif()
if (MFEM_USE_ENZYME)
target_link_libraries(mfem PUBLIC ClangEnzymeFlags)
endif()
set_target_properties(mfem PROPERTIES VERSION "${mfem_VERSION}")
set_target_properties(mfem PROPERTIES SOVERSION "${mfem_VERSION}")
+2
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@@ -249,3 +249,5 @@ endif()
if(MFEM_USE_MOONOLITH)
add_subdirectory(moonolith)
endif()
add_subdirectory(dfem)
+116
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@@ -0,0 +1,116 @@
# 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.
set(DFEM_EXAMPLES_SRCS)
if (MFEM_USE_MPI)
list(APPEND DFEM_EXAMPLES_SRCS
plasticity.cpp
laghos.cpp
)
endif()
# Include the source directory where mfem.hpp and mfem-performance.hpp are.
include_directories(BEFORE ${PROJECT_BINARY_DIR})
# Add "test_dfem" target, see below.
add_custom_target(test_dfem
${CMAKE_CTEST_COMMAND} -R dfem USES_TERMINAL)
# Add one executable per cpp file, adding "dfem_" as prefix so the CMake
# target is unique from those in the non-dFEM examples. Also sets
# "test_dfem" as a target that depends on the given dFEM examples.
set(PFX dfem_)
add_mfem_examples(DFEM_EXAMPLES_SRCS ${PFX} "" test_dfem)
# Remove "dfem_" prefix from exectuable name for consistency with GNU build
# system.
foreach(SRC_FILE ${DFEM_EXAMPLES_SRCS})
get_filename_component(SRC_FILENAME ${SRC_FILE} NAME)
string(REPLACE ".cpp" "" TARGET_NAME "${PFX}${SRC_FILENAME}")
string(REPLACE ${PFX} "" EXE_NAME ${TARGET_NAME})
set_target_properties(${TARGET_NAME} PROPERTIES OUTPUT_NAME ${EXE_NAME})
endforeach()
# Testing.
# The dFEM tests can be run separately using the target "test_dfem"
# which builds the examples and runs:
# ctest -R dfem
if (MFEM_ENABLE_TESTING)
# Command line options for the tests.
# Example 9: test CVODE with CV_ADAMS (non-stiff implicit) time stepping
# set(EX9_COMMON_OPTS -m ../../data/periodic-hexagon.mesh -p 0 -s 7)
# set(EX9_TEST_OPTS ${EX9_COMMON_OPTS} -r 2 -dt 0.0018 -vs 25)
# set(EX9P_TEST_OPTS ${EX9_COMMON_OPTS} -rp 1 -dt 0.0009 -vs 50)
# Example 10: test CVODE with CV_BDF (stiff implicit) time stepping
# set(EX10_COMMON_OPTS -m ../../data/beam-quad.mesh -o 2 -s 5 -dt 0.15 -tf 6 -vs 10)
# set(EX10_TEST_OPTS ${EX10_COMMON_OPTS} -r 2)
# set(EX10P_TEST_OPTS ${EX10_COMMON_OPTS} -rp 1)
# Example 16: test ARKODE with implicit time stepping using mass form
# set(EX16_COMMON_OPTS -s 15)
# set(EX16_TEST_OPTS ${EX16_COMMON_OPTS})
# set(EX16P_TEST_OPTS ${EX16_COMMON_OPTS})
# Add the tests: one test per source file.
foreach(SRC_FILE ${DFEM_EXAMPLES_SRCS})
get_filename_component(SRC_FILENAME ${SRC_FILE} NAME)
string(REPLACE ".cpp" "" TEST_NAME ${SRC_FILENAME})
string(TOUPPER ${TEST_NAME} UP_TEST_NAME)
set(TEST_NAME ${PFX}${TEST_NAME})
set(THIS_TEST_OPTIONS "-no-vis")
list(APPEND THIS_TEST_OPTIONS ${${UP_TEST_NAME}_TEST_OPTS})
# message(STATUS "Test ${TEST_NAME} options: ${THIS_TEST_OPTIONS}")
if (NOT (${TEST_NAME} MATCHES ".*p$"))
add_test(NAME ${TEST_NAME}_ser
COMMAND ${TEST_NAME} ${THIS_TEST_OPTIONS})
else()
add_test(NAME ${TEST_NAME}_np=${MFEM_MPI_NP}
COMMAND ${MPIEXEC} ${MPIEXEC_NUMPROC_FLAG} ${MFEM_MPI_NP}
${MPIEXEC_PREFLAGS}
$<TARGET_FILE:${TEST_NAME}> ${THIS_TEST_OPTIONS}
${MPIEXEC_POSTFLAGS})
endif()
endforeach()
# Add CUDA/HIP tests.
set(DEVICE_EXAMPLES
# parallel examples with device support:
# ex9p
)
set(MFEM_TEST_DEVICE)
if (MFEM_USE_CUDA)
set(MFEM_TEST_DEVICE "cuda")
elseif (MFEM_USE_HIP)
set(MFEM_TEST_DEVICE "hip")
endif()
if (MFEM_TEST_DEVICE)
foreach(TEST_NAME ${DEVICE_EXAMPLES})
string(TOUPPER ${TEST_NAME} UP_TEST_NAME)
set(THIS_TEST_OPTIONS "-no-vis" "-d" "${MFEM_TEST_DEVICE}")
list(APPEND THIS_TEST_OPTIONS ${${UP_TEST_NAME}_TEST_OPTS})
if (NOT (${TEST_NAME} MATCHES ".*p$"))
add_test(NAME ${PFX}${TEST_NAME}_${MFEM_TEST_DEVICE}_ser
COMMAND ${PFX}${TEST_NAME} ${THIS_TEST_OPTIONS})
else()
add_test(NAME ${PFX}${TEST_NAME}_${MFEM_TEST_DEVICE}_np=${MFEM_MPI_NP}
COMMAND ${MPIEXEC} ${MPIEXEC_NUMPROC_FLAG} ${MFEM_MPI_NP}
${MPIEXEC_PREFLAGS}
$<TARGET_FILE:${PFX}${TEST_NAME}> ${THIS_TEST_OPTIONS}
${MPIEXEC_POSTFLAGS})
endif()
endforeach()
endif(MFEM_TEST_DEVICE)
endif(MFEM_ENABLE_TESTING)
File diff suppressed because it is too large Load Diff
+587
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@@ -0,0 +1,587 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include <mfem.hpp>
// TODO: Do we want this to be included from mfem.hpp automatically now?
#include <fem/dfem/doperator.hpp>
#include <linalg/tensor.hpp>
#include <fstream>
using namespace mfem;
using mfem::internal::tensor;
constexpr int DIMENSION = 2;
template <typename T, int dim>
MFEM_HOST_DEVICE inline
tensor<T, 3, 3> tensor_to_3D(const tensor<T, dim, dim>& A)
{
tensor<T, 3, 3> A3D{};
for (int i = 0; i < dim; i++)
{
for (int j = 0; j < dim; j++)
{
A3D[i][j] = A[i][j];
}
}
return A3D;
}
template <typename Material, int dim = DIMENSION>
struct InternalStateQFunction
{
InternalStateQFunction() = default;
MFEM_HOST_DEVICE inline
auto operator()(
const tensor<real_t, dim, dim> &dudxi,
const tensor<real_t, dim, dim> &J,
const tensor<real_t, 10> &internal_state,
const double &w) const
{
auto invJ = inv(J);
auto dudX = dudxi * invJ;
auto dudX3D = tensor_to_3D(dudX);
//auto internal_state_new = get<1>(material(dudX3D, internal_state));
auto [stress, internal_state_new] = material(dudX3D, internal_state);
// real_t vm = sqrt(1.5)*norm(dev(stress));
// out << vm << " " << internal_state_new[9] << std::endl;
return mfem::tuple{internal_state_new};
}
Material material;
};
template <typename Material, int dim = DIMENSION>
struct MomentumRefStateQFunction
{
MomentumRefStateQFunction() = default;
MFEM_HOST_DEVICE inline
auto operator()(
const tensor<real_t, dim, dim> &dudxi,
const tensor<real_t, dim, dim> &J,
const tensor<real_t, 10> &internal_state,
const double &w) const
{
auto invJ = inv(J);
auto dudX = dudxi * invJ;
auto dudX3D = tensor_to_3D(dudX);
auto [P3D, Qnew] = material(dudX3D, internal_state);
auto P = mfem::internal::make_tensor<dim, dim>([&P3D](int i, int j) { return P3D[i][j]; });
auto JxW = det(J) * w * transpose(invJ);
return mfem::tuple{P * JxW};
}
Material material;
};
struct J2SmallStrain
{
static constexpr int dim = 3; ///< spatial dimension
static constexpr int n_internal_states = 10;
static constexpr double tol =
1e-10; ///< relative tolerance on residual mag to judge convergence of return map
real_t E; ///< Young's modulus
real_t nu; ///< Poisson's ratio
real_t sigma_y; ///< Yield strength
real_t Hi; ///< Isotropic hardening modulus
real_t density; ///< Mass density
/// @brief variables required to characterize the hysteresis response
struct InternalState
{
tensor<double, dim, dim> plastic_strain; ///< plastic strain
double accumulated_plastic_strain; ///< uniaxial equivalent plastic strain
};
MFEM_HOST_DEVICE inline
InternalState unpack_internal_state(const tensor<real_t, n_internal_states> &
packed_state) const
{
// we could use type punning here to avoid copies
auto plastic_strain = mfem::internal::make_tensor<dim, dim>(
[&packed_state](int i, int j) { return packed_state[dim*i + j]; });
real_t accumulated_plastic_strain = packed_state[n_internal_states - 1];
return {plastic_strain, accumulated_plastic_strain};
}
MFEM_HOST_DEVICE inline
tensor<real_t, n_internal_states> pack_internal_state(const
tensor<real_t, dim, dim> & plastic_strain,
real_t accumulated_plastic_strain) const
{
tensor<real_t, n_internal_states> packed_state{};
for (int i = 0, ij = 0; i < dim; i++)
{
for (int j = 0; j < dim; j++, ij++)
{
packed_state[ij] = plastic_strain[i][j];
}
}
packed_state[n_internal_states - 1] = accumulated_plastic_strain;
return packed_state;
}
MFEM_HOST_DEVICE inline
tuple<tensor<real_t, dim, dim>, tensor<real_t, n_internal_states>>
operator()(const tensor<real_t, dim, dim> & dudX,
const tensor<real_t, n_internal_states> & internal_state) const
{
auto I = mfem::internal::Identity<dim>();
const real_t K = E / (3.0 * (1.0 - 2.0 * nu));
const real_t G = 0.5 * E / (1.0 + nu);
auto [plastic_strain, accumulated_plastic_strain] = unpack_internal_state(
internal_state);
// (i) elastic predictor
auto el_strain = sym(dudX) - plastic_strain;
auto p = K * tr(el_strain);
auto s = 2.0 * G * dev(el_strain);
auto q = sqrt(1.5) * norm(s);
[[maybe_unused]] real_t delta_eqps = 0.0;
[[maybe_unused]] auto flow_strength = [this](real_t eqps) { return this->sigma_y + this->Hi*eqps; };
// (ii) admissibility
if (q - (sigma_y + Hi*accumulated_plastic_strain) > tol*sigma_y)
{
// (iii) return mapping
real_t delta_eqps = (q - sigma_y - Hi*accumulated_plastic_strain)/(3*G + Hi);
auto Np = 1.5 * s / q;
s -= 2.0 * G * delta_eqps * Np;
plastic_strain += delta_eqps * Np;
accumulated_plastic_strain += delta_eqps;
}
auto stress = s + p * I;
auto internal_state_new = pack_internal_state(plastic_strain,
accumulated_plastic_strain);
return {stress, internal_state_new};
}
};
class ElasticityOperator : public Operator
{
static constexpr int Displacement = 0;
static constexpr int Coordinates = 1;
static constexpr int InternalState = 2;
public:
class ElasticityJacobianOperator : public Operator
{
public:
ElasticityJacobianOperator(const ElasticityOperator *elasticity,
const Vector &x) :
Operator(elasticity->Height()),
elasticity(elasticity),
z(elasticity->Height())
{
ParGridFunction u(&elasticity->displacement_fes);
u.SetFromTrueDofs(x);
auto mesh_nodes = static_cast<ParGridFunction*>
(elasticity->displacement_fes.GetParMesh()->GetNodes());
momentum_du = elasticity->momentum->GetDerivative(Displacement, {&u}, {mesh_nodes, &elasticity->internal_state});
}
void Mult(const Vector &x, Vector &y) const override
{
z = x;
z.SetSubVector(elasticity->displacement_ess_tdof, 0.0);
momentum_du->Mult(z, y);
for (int i = 0; i < elasticity->displacement_ess_tdof.Size(); i++)
{
y[elasticity->displacement_ess_tdof[i]] =
x[elasticity->displacement_ess_tdof[i]];
}
}
const ElasticityOperator *elasticity;
std::shared_ptr<DerivativeOperator> momentum_du;
mutable Vector z;
};
template <typename Material>
ElasticityOperator(ParFiniteElementSpace &displacement_fes,
Array<int> &vel_ess_tdofs,
const IntegrationRule &displacement_ir,
ParametricFunction &internal_state,
Material material) :
Operator(displacement_fes.GetTrueVSize()),
density(1.0e3),
body_force(displacement_fes.GetTrueVSize()),
displacement_ess_tdof(vel_ess_tdofs),
displacement_fes(displacement_fes),
displacement_ir(displacement_ir),
internal_state(internal_state)
{
auto mesh = displacement_fes.GetParMesh();
mesh_nodes = static_cast<ParGridFunction*>(mesh->GetNodes());
ParFiniteElementSpace& mesh_fes = *mesh_nodes->ParFESpace();
{
auto solutions = std::vector
{
FieldDescriptor{Displacement, &displacement_fes},
};
auto parameters = std::vector
{
FieldDescriptor{Coordinates, &mesh_fes},
FieldDescriptor{InternalState, &internal_state.space}
};
momentum =
std::make_shared<DifferentiableOperator>(solutions, parameters, *mesh);
momentum->DisableTensorProductStructure();
mfem::tuple inputs{Gradient<Displacement>{}, Gradient<Coordinates>{}, None<InternalState>{}, Weight{}};
mfem::tuple outputs{Gradient<Displacement>{}};
auto momentum_qf = MomentumRefStateQFunction<Material, DIMENSION> {.material = material};
auto derivatives = std::integer_sequence<size_t, Displacement> {};
Array<int> solid_domain_attr(mesh->attributes.Max());
solid_domain_attr[0] = 1;
momentum->AddDomainIntegrator(
momentum_qf, inputs, outputs, displacement_ir, solid_domain_attr, derivatives);
}
{
Vector g(DIMENSION);
g = 0.0;
ParLinearForm body_force_lf(&displacement_fes);
body_force_coef = new VectorConstantCoefficient(g);
auto integ = new VectorDomainLFIntegrator(*body_force_coef);
integ->SetIntRule(&displacement_ir);
body_force_lf.AddDomainIntegrator(integ);
body_force_lf.Assemble();
body_force_lf.ParallelAssemble(body_force);
}
}
void Mult(const Vector &displacement, Vector &r) const override
{
momentum->SetParameters({mesh_nodes, &internal_state});
momentum->Mult(displacement, r);
r -= body_force;
r.SetSubVector(displacement_ess_tdof, 0.0);
}
void Reaction(const Vector &displacement, Vector &r) const
{
momentum->SetParameters({mesh_nodes, &internal_state});
momentum->Mult(displacement, r);
r -= body_force;
r.Neg();
}
Operator &GetGradient(const Vector &x) const override
{
jacobian_operator = std::make_shared<ElasticityJacobianOperator>(this, x);
return *jacobian_operator;
// fd_jacobian = std::make_shared<FDJacobian>(*this, x);
// return *fd_jacobian;
}
real_t density;
std::shared_ptr<DifferentiableOperator> momentum;
mutable std::shared_ptr<HypreParMatrix> A;
VectorConstantCoefficient *body_force_coef = nullptr;
Vector body_force;
ParGridFunction *mesh_nodes;
const Array<int> displacement_ess_tdof;
ParFiniteElementSpace &displacement_fes;
IntegrationRule displacement_ir;
ParametricFunction& internal_state;
mutable std::shared_ptr<ElasticityJacobianOperator> jacobian_operator;
mutable std::shared_ptr<FDJacobian> fd_jacobian;
};
class InternalStateUpdater : public Operator
{
public:
static constexpr int Displacement = 0;
static constexpr int Coordinates = 1;
static constexpr int InternalState = 2;
template <typename Material>
InternalStateUpdater(ParFiniteElementSpace &displacement_fes,
const IntegrationRule &displacement_ir,
ParametricFunction &internal_state,
Material material) :
Operator(displacement_fes.GetTrueVSize()),
displacement_fes(displacement_fes),
displacement_ir(displacement_ir),
internal_state(internal_state)
{
auto mesh = displacement_fes.GetParMesh();
mesh_nodes = static_cast<ParGridFunction*>(mesh->GetNodes());
ParFiniteElementSpace& mesh_fes = *mesh_nodes->ParFESpace();
auto solutions = std::vector
{
FieldDescriptor{Displacement, &displacement_fes}
};
auto parameters = std::vector
{
FieldDescriptor{Coordinates, &mesh_fes},
FieldDescriptor{InternalState, &internal_state.space}
};
op = std::make_shared<DifferentiableOperator>(solutions, parameters, *mesh);
op->DisableTensorProductStructure();
mfem::tuple inputs{Gradient<Displacement>{}, Gradient<Coordinates>{}, None<InternalState>{}, Weight{}};
mfem::tuple outputs{None<InternalState>{}};
auto qfunction = InternalStateQFunction<Material, DIMENSION> {.material = material};
// just a placeholder for now. We want vjps wrt both displacement and old internal state eventually
auto derivatives = std::integer_sequence<size_t, Displacement> {};
Array<int> solid_domain_attr(mesh->attributes.Max());
solid_domain_attr[0] = 1;
op->AddDomainIntegrator(
qfunction, inputs, outputs, displacement_ir, solid_domain_attr, derivatives);
}
void Mult(const Vector &displacement, Vector& internal_state_new) const override
{
op->SetParameters({mesh_nodes, &internal_state});
op->Mult(displacement, internal_state_new);
}
void VjpDisplacement(ParGridFunction &u, Vector& internal_state_old,
Vector& internal_state_new_bar, Vector& displacement_bar) const
{
// u, internal_state_old, internal_state_new_bar should be const
out << "Sizes " << "u " << u.Size() << ", qold " << internal_state_old.Size() <<
", qbar " << internal_state_new_bar.Size() << ", ubar " <<
displacement_bar.Size() << std::endl;
auto grad_op = op->GetDerivative(Displacement, {&u}, {mesh_nodes, &internal_state_old});
out << "grad_op " << grad_op->Height() << " " << grad_op->Width() << std::endl;
out << "grad_op^T " << grad_op->Width() << " " << grad_op->Height() <<
std::endl;
grad_op->MultTranspose(internal_state_new_bar, displacement_bar);
}
ParGridFunction *mesh_nodes;
ParFiniteElementSpace &displacement_fes;
std::shared_ptr<DifferentiableOperator> op;
IntegrationRule displacement_ir;
ParametricFunction& internal_state;
};
int main(int argc, char* argv[])
{
constexpr int dim = 2;
Mpi::Init();
const char* device_config = "cpu";
int polynomial_order = 1;
int ir_order = 2;
int refinements = 0;
int nonlinear_solver_type = 0;
OptionsParser args(argc, argv);
args.AddOption(&polynomial_order, "-o", "--order", "");
args.AddOption(&refinements, "-r", "--refinements", "");
args.AddOption(&ir_order, "-iro", "--integration-rule-order", "");
args.AddOption(&device_config, "-d", "--device",
"Device configuration string, see Device::Configure().");
args.AddOption(&nonlinear_solver_type, "-nls", "--nonlinear-solver", "");
args.ParseCheck();
Device device(device_config);
if (Mpi::Root() == 0)
{
device.Print();
}
out << std::setprecision(8);
Mesh mesh_serial = Mesh::MakeCartesian2D(1, 1, Element::QUADRILATERAL,
false, 1.0, 0.1);
mesh_serial.EnsureNodes();
auto mesh_beam = ParMesh(MPI_COMM_WORLD, mesh_serial);
out << "#el: " << mesh_beam.GetNE() << "\n";
H1_FECollection displacement_fec(polynomial_order, dim);
ParFiniteElementSpace displacement_fes(&mesh_beam, &displacement_fec, dim);
HYPRE_BigInt global_size = displacement_fes.GlobalTrueVSize();
if (Mpi::Root())
{
out << "Number of unknowns: " << global_size << "\n";
}
const IntegrationRule &displacement_ir =
IntRules.Get(displacement_fes.GetFE(0)->GetGeomType(),
2 * ir_order + displacement_fes.GetFE(0)->GetOrder());
constexpr int n_internal_state_variables = 10;
ParametricSpace internal_state_space(dim, n_internal_state_variables,
displacement_ir.GetNPoints(),
n_internal_state_variables*displacement_ir.GetNPoints()*mesh_beam.GetNE());
ParametricFunction internal_state(internal_state_space);
internal_state = 0.0;
ParametricFunction internal_state_old(internal_state_space);
internal_state_old = 0.0;
Array<int> bdr_attr_is_ess(mesh_beam.bdr_attributes.Max());
Array<int> displacement_ess_tdof;
Array<int> bc_tdof;
bdr_attr_is_ess = 0;
bdr_attr_is_ess[0] = 1;
displacement_fes.GetEssentialTrueDofs(bdr_attr_is_ess, bc_tdof, 1);
for (auto td : bc_tdof) { displacement_ess_tdof.Append(td); };
bdr_attr_is_ess = 0;
bdr_attr_is_ess[3] = 1;
displacement_fes.GetEssentialTrueDofs(bdr_attr_is_ess, bc_tdof, 0);
for (auto td : bc_tdof) { displacement_ess_tdof.Append(td); };
bdr_attr_is_ess = 0;
bdr_attr_is_ess[1] = 1;
displacement_fes.GetEssentialTrueDofs(bdr_attr_is_ess, bc_tdof, 0);
for (auto td : bc_tdof) { displacement_ess_tdof.Append(td); };
ParGridFunction u(&displacement_fes);
u = 0.0;
using Material = J2SmallStrain; // StVenantKirchhoff
Material material{.E = 1000.0, .nu = 0.25, .sigma_y = 0.53333, .Hi = 40.0, .density = 1.0};
// Material material{.mu = 0.5e6, .nu = 0.4};
ElasticityOperator elasticity(displacement_fes, displacement_ess_tdof,
displacement_ir, internal_state, material);
CGSolver solver(MPI_COMM_WORLD);
solver.SetAbsTol(0.0);
solver.SetRelTol(1e-10);
solver.SetMaxIter(1000);
solver.SetPrintLevel(2);
std::shared_ptr<NewtonSolver> nonlinear_solver;
if (nonlinear_solver_type == 0)
{
nonlinear_solver = std::make_shared<NewtonSolver>(MPI_COMM_WORLD);
}
// else if (nonlinear_solver_type == 1)
// {
// nonlinear_solver = std::make_shared<KINSolver>(MPI_COMM_WORLD, KIN_LINESEARCH);
// }
else
{
MFEM_ABORT("invalid nonlinear solver type");
}
nonlinear_solver->SetOperator(elasticity);
nonlinear_solver->SetRelTol(1e-9);
nonlinear_solver->SetMaxIter(25);
nonlinear_solver->SetSolver(solver);
nonlinear_solver->SetPrintLevel(1);
// variables for output
QuadratureSpace output_internal_state_space(mesh_beam, displacement_ir);
QuadratureFunction output_internal_state(&output_internal_state_space,
internal_state.GetData(), material.n_internal_states);
Vector r(displacement_fes.GetTrueVSize());
ParGridFunction reaction(&displacement_fes);
Vector end_forces_x(bc_tdof.Size());
ParaViewDataCollection dc("dfem_plasticity", &mesh_beam);
dc.SetHighOrderOutput(true);
dc.SetLevelsOfDetail(1);
dc.RegisterField("displacement", &u);
dc.RegisterField("reaction", &reaction);
dc.RegisterQField("internal_state", &output_internal_state);
dc.SetCycle(0);
dc.Save();
InternalStateUpdater internal_state_update(displacement_fes, displacement_ir,
internal_state, material);
//Vector q(internal_state_space.GetTotalSize());
auto applied_displacement = [](double t) { return 1.2e-2*t; };
real_t time = 0.0;
std::ofstream history_file("history_output.csv");
history_file << applied_displacement(time) << " " << 0.0 << std::endl;
Vector zero, x(displacement_fes.GetTrueVSize());
constexpr int max_cycles = 3;
const real_t dt = 1.0/(max_cycles - 1);
for (int cycle = 1; cycle < max_cycles; cycle++)
{
time += dt;
out << "-------------------------------------------" << std::endl;
out << "TIME STEP " << cycle << std::endl;
out << "t = " << time << std::endl;
real_t ubc = applied_displacement(time);
u.SetSubVector(bc_tdof, ubc);
u.GetTrueDofs(x);
nonlinear_solver->Mult(zero, x);
u.SetFromTrueDofs(x);
// update internal variables
internal_state_old.Set(1.0, internal_state);
internal_state_update.Mult(u, internal_state);
// Compute reactions
elasticity.Reaction(x, r);
reaction.SetFromTrueDofs(r);
reaction.GetSubVector(bc_tdof, end_forces_x);
real_t force = -end_forces_x.Sum();
out << "u = " << applied_displacement(time) << ", Force = " << force <<
std::endl;
history_file << applied_displacement(time) << " " << force << std::endl;
output_internal_state = internal_state;
dc.SetCycle(cycle);
dc.SetTime(time);
dc.Save();
}
// try to use the derivative to see if it works
ParametricFunction internal_state_bar(internal_state_space);
internal_state_bar = 1.0;
//ParGridFunction u_bar(displacement_fes);
Vector u_bar(displacement_fes.GetTrueVSize());
internal_state_update.VjpDisplacement(u, internal_state_old, internal_state_bar,
u_bar);
pretty_print(u_bar);
history_file.close();
return 0;
}
+7
View File
@@ -175,6 +175,13 @@ set(HDRS
dgmassinv.hpp
dgmassinv_kernels.hpp
doftrans.hpp
dfem/doperator.hpp
dfem/fieldoperator.hpp
dfem/integrate.hpp
dfem/parametricspace.hpp
dfem/qfunction.hpp
dfem/tuple.hpp
dfem/util.hpp
eltrans.hpp
estimators.hpp
fe.hpp
+776
View File
@@ -0,0 +1,776 @@
// 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 <type_traits>
#include <utility>
#include "util.hpp"
#include "interpolate.hpp"
#include "qfunction.hpp"
#include "integrate.hpp"
#undef NVTX_COLOR
#define NVTX_COLOR nvtx::kOrchid
#include "general/nvtx.hpp"
namespace mfem
{
using action_t =
std::function<void(std::vector<Vector> &, const std::vector<Vector> &, Vector &)>;
using derivative_action_t =
std::function<void(std::vector<Vector> &, const Vector &, Vector &)>;
using restriction_callback_t =
std::function<void(std::vector<Vector> &,
const std::vector<Vector> &,
std::vector<Vector> &)>;
class DerivativeOperator : public Operator
{
public:
DerivativeOperator(
const int &height,
const int &width,
const std::vector<derivative_action_t> &derivative_actions,
const FieldDescriptor &direction,
const int &daction_l_size,
const std::vector<derivative_action_t> &derivative_actions_transpose,
const FieldDescriptor &transpose_direction,
const int &daction_transpose_l_size,
const std::vector<Vector *> &solutions_l,
const std::vector<Vector *> &parameters_l,
const restriction_callback_t &restriction_callback,
const std::function<void(Vector &, Vector &)> &prolongation_transpose) :
Operator(height, width),
derivative_actions(derivative_actions),
direction(direction),
daction_l(daction_l_size),
derivative_actions_transpose(derivative_actions_transpose),
transpose_direction(transpose_direction),
daction_transpose_l(daction_transpose_l_size),
prolongation_transpose(prolongation_transpose)
{
std::vector<Vector> s_l(solutions_l.size());
for (size_t i = 0; i < s_l.size(); i++)
{
s_l[i] = *solutions_l[i];
}
std::vector<Vector> p_l(parameters_l.size());
for (size_t i = 0; i < p_l.size(); i++)
{
p_l[i] = *parameters_l[i];
}
fields_e.resize(solutions_l.size() + parameters_l.size());
restriction_callback(s_l, p_l, fields_e);
}
void Mult(const Vector &direction_t, Vector &y) const override
{
// daction_l.SetSize(height);
daction_l = 0.0;
prolongation(direction, direction_t, direction_l);
for (size_t i = 0; i < derivative_actions.size(); i++)
{
derivative_actions[i](fields_e, direction_l, daction_l);
}
prolongation_transpose(daction_l, y);
};
void MultTranspose(const Vector &direction_t, Vector &y) const override
{
// daction_l.SetSize(width);
daction_l = 0.0;
prolongation(transpose_direction, direction_t, direction_l);
for (size_t i = 0; i < derivative_actions_transpose.size(); i++)
{
derivative_actions_transpose[i](fields_e, direction_l, daction_l);
}
prolongation_transpose(daction_l, y);
};
private:
std::vector<derivative_action_t> derivative_actions;
FieldDescriptor direction;
mutable Vector daction_l;
std::vector<derivative_action_t> derivative_actions_transpose;
FieldDescriptor transpose_direction;
mutable Vector daction_transpose_l;
mutable std::vector<Vector> fields_e;
mutable Vector direction_l;
std::function<void(Vector &, Vector &)> prolongation_transpose;
};
class DifferentiableOperator : public Operator
{
public:
DifferentiableOperator(
const std::vector<FieldDescriptor> &solutions,
const std::vector<FieldDescriptor> &parameters,
const ParMesh &mesh);
void Mult(const Vector &solutions_t, Vector &y) const override
{
MFEM_ASSERT(!action_callbacks.empty(), "no integrators have been set");
prolongation(solutions, solutions_t, solutions_l);
for (auto &action : action_callbacks)
{
action(solutions_l, parameters_l, residual_l);
}
prolongation_transpose(residual_l, y);
}
void Mult(ParGridFunction &x, ParGridFunction &y) const
{
MFEM_ASSERT(!action_callbacks.empty(), "no integrators have been set");
MFEM_VERIFY(y.Size() == residual_l.Size(), "output size mismatch");
prolongation(solutions, x.GetTrueVector(), solutions_l);
for (auto &action : action_callbacks)
{
action(solutions_l, parameters_l, residual_l);
}
y = residual_l;
}
template <
typename func_t,
typename... input_ts,
typename... output_ts,
typename derivative_indices_t>
void AddDomainIntegrator(
func_t &qfunc,
mfem::tuple<input_ts...> inputs,
mfem::tuple<output_ts...> outputs,
const IntegrationRule &integration_rule,
const Array<int> domain_attributes,
const derivative_indices_t derivative_indices = {});
void SetParameters(std::vector<Vector *> p) const;
void DisableTensorProductStructure(bool disable = true)
{
use_tensor_product_structure = !disable;
}
std::shared_ptr<DerivativeOperator> GetDerivative(
size_t derivative_id,
std::vector<Vector *> solutions_l,
std::vector<Vector *> parameters_l)
{
MFEM_ASSERT(derivative_action_callbacks.find(derivative_id) !=
derivative_action_callbacks.end(),
"no derivative action has been found for ID " << derivative_id);
MFEM_ASSERT(solutions_l.size() == solutions.size(),
"wrong number of solutions");
MFEM_ASSERT(parameters_l.size() == parameters.size(),
"wrong number of parameters");
const size_t derivative_idx = FindIdx(derivative_id, fields);
return std::make_shared<DerivativeOperator>(
height,
GetTrueVSize(fields[derivative_idx]),
derivative_action_callbacks[derivative_id],
fields[derivative_idx],
residual_l.Size(),
daction_transpose_callbacks[derivative_id],
fields[test_space_field_idx],
GetTrueVSize(fields[test_space_field_idx]),
solutions_l,
parameters_l,
restriction_callback,
prolongation_transpose);
}
private:
const ParMesh &mesh;
std::vector<action_t> action_callbacks;
std::map<size_t,
std::vector<derivative_action_t>> derivative_action_callbacks;
std::map<size_t,
std::vector<derivative_action_t>> daction_transpose_callbacks;
std::vector<FieldDescriptor> solutions;
std::vector<FieldDescriptor> parameters;
// solutions and parameters
std::vector<FieldDescriptor> fields;
mutable std::vector<Vector> solutions_l;
mutable std::vector<Vector> parameters_l;
mutable Vector residual_l;
mutable std::vector<Vector> fields_e;
mutable Vector residual_e;
std::function<void(Vector &, Vector &)> prolongation_transpose;
std::function<void(Vector &, Vector &)> output_restriction_transpose;
restriction_callback_t restriction_callback;
std::map<size_t, size_t> assembled_vector_sizes;
bool use_tensor_product_structure = true;
size_t test_space_field_idx = SIZE_MAX;
};
void DifferentiableOperator::SetParameters(std::vector<Vector *> p) const
{
MFEM_ASSERT(parameters.size() == p.size(),
"number of parameters doesn't match descriptors");
for (size_t i = 0; i < parameters.size(); i++)
{
p[i]->Read();
parameters_l[i] = *p[i];
}
}
DifferentiableOperator::DifferentiableOperator(
const std::vector<FieldDescriptor> &solutions,
const std::vector<FieldDescriptor> &parameters,
const ParMesh &mesh) :
mesh(mesh),
solutions(solutions),
parameters(parameters)
{
fields.resize(solutions.size() + parameters.size());
fields_e.resize(fields.size());
solutions_l.resize(solutions.size());
parameters_l.resize(parameters.size());
for (size_t i = 0; i < solutions.size(); i++)
{
fields[i] = solutions[i];
}
for (size_t i = 0; i < parameters.size(); i++)
{
fields[i + solutions.size()] = parameters[i];
}
}
template <
typename qfunc_t,
typename... input_ts,
typename... output_ts,
typename derivative_ids_t = std::make_index_sequence<0>>
void DifferentiableOperator::AddDomainIntegrator(
qfunc_t &qfunc,
mfem::tuple<input_ts...> inputs,
mfem::tuple<output_ts...> outputs,
const IntegrationRule &integration_rule,
const Array<int> domain_attributes,
derivative_ids_t derivative_ids)
{
using entity_t = Entity::Element;
static constexpr size_t num_inputs =
mfem::tuple_size<decltype(inputs)>::value;
static constexpr size_t num_outputs =
mfem::tuple_size<decltype(outputs)>::value;
using qf_signature =
typename create_function_signature<decltype(&qfunc_t::operator())>::type;
using qf_param_ts = typename qf_signature::parameter_ts;
using qf_output_t = typename qf_signature::return_t;
// Consistency checks
if constexpr (num_outputs > 1)
{
static_assert(always_false<qfunc_t>,
"more than one output per quadrature functions is not supported right now");
}
if constexpr (std::is_same_v<qf_output_t, void>)
{
static_assert(always_false<qfunc_t>, "quadrature function has no return value");
}
constexpr size_t num_qfinputs = mfem::tuple_size<qf_param_ts>::value;
static_assert(num_qfinputs == num_inputs,
"quadrature function inputs and descriptor inputs have to match");
constexpr size_t num_qf_outputs = mfem::tuple_size<qf_output_t>::value;
static_assert(num_qf_outputs == num_outputs,
"quadrature function outputs and descriptor outputs have to match");
constexpr auto inout_tuple = std::tuple_cat(std::tuple<input_ts...> {},
std::tuple<output_ts...> {});
constexpr auto filtered_inout_tuple = filter_fields(inout_tuple);
constexpr size_t num_fields = count_unique_field_ids(filtered_inout_tuple);
MFEM_ASSERT(num_fields == solutions.size() + parameters.size(),
"Total number of fields doesn't match sum of solutions and parameters."
" This indicates that some fields are not used in the integrator,"
" which currently is not supported.");
auto dependency_map = make_dependency_map(mfem::tuple<input_ts...> {});
// pretty_print(dependency_map);
auto input_to_field =
create_descriptors_to_fields_map<entity_t>(fields, inputs);
auto output_to_field =
create_descriptors_to_fields_map<entity_t>(fields, outputs);
// TODO: factor out
std::vector<int> inputs_vdim(num_inputs);
for_constexpr<num_inputs>([&](auto i)
{
inputs_vdim[i] = mfem::get<i>(inputs).vdim;
});
const int NE = mesh.GetNE();
if (NE == 0)
{
// use of GetElement(0), GetFE(0) in GetDofToQuad assume that NE > 0
MFEM_ABORT("Mesh with no elements is not yet supported!");
}
Array<int> elem_attributes;
if (NE > 0)
{
elem_attributes.SetSize(NE);
for (int i = 0; i < NE; ++i)
{
elem_attributes[i] = mesh.GetAttribute(i);
}
}
const auto output_fop = mfem::get<0>(outputs);
test_space_field_idx = FindIdx(output_fop.GetFieldId(), fields);
bool use_sum_factorization = false;
auto entity_element_type = mesh.GetElement(0)->GetType();
if ((entity_element_type == Element::QUADRILATERAL ||
entity_element_type == Element::HEXAHEDRON) &&
use_tensor_product_structure == true)
{
use_sum_factorization = true;
}
ElementDofOrdering element_dof_ordering = ElementDofOrdering::NATIVE;
DofToQuad::Mode doftoquad_mode = DofToQuad::Mode::FULL;
if (use_sum_factorization)
{
element_dof_ordering = ElementDofOrdering::LEXICOGRAPHIC;
doftoquad_mode = DofToQuad::Mode::TENSOR;
}
auto [output_rt,
output_e_sz] = get_restriction_transpose<entity_t>
(fields[test_space_field_idx],
element_dof_ordering, output_fop);
auto &output_e_size = output_e_sz;
output_restriction_transpose = output_rt;
residual_e.SetSize(output_e_size);
// The explicit captures are necessary to avoid dependency on
// the specific instance of this class (this pointer).
restriction_callback =
[=, solutions = this->solutions, parameters = this->parameters]
(std::vector<Vector> &solutions_l,
const std::vector<Vector> &parameters_l,
std::vector<Vector> &fields_e)
{
restriction<entity_t>(solutions, solutions_l, fields_e,
element_dof_ordering);
restriction<entity_t>(parameters, parameters_l, fields_e,
element_dof_ordering,
solutions.size());
};
prolongation_transpose = get_prolongation_transpose(
fields[test_space_field_idx], output_fop, mesh.GetComm());
const int dimension = mesh.Dimension();
[[maybe_unused]] const int num_elements = GetNumEntities<Entity::Element>(mesh);
const int num_entities = GetNumEntities<entity_t>(mesh);
const int num_qp = integration_rule.GetNPoints();
if constexpr (is_one_fop<decltype(output_fop)>::value)
{
residual_l.SetSize(1);
height = 1;
}
else
{
const int residual_lsize = GetVSize(fields[test_space_field_idx]);
residual_l.SetSize(residual_lsize);
height = GetTrueVSize(fields[test_space_field_idx]);
}
// TODO: Is this a hack?
width = GetTrueVSize(fields[0]);
std::vector<const DofToQuad*> dtq;
for (const auto &field : fields)
{
dtq.emplace_back(GetDofToQuad<entity_t>(
field,
integration_rule,
doftoquad_mode));
}
const int q1d = (int)floor(pow(num_qp, 1.0/dimension) + 0.5);
const int residual_size_on_qp =
GetSizeOnQP<entity_t>(output_fop,
fields[test_space_field_idx]);
auto input_dtq_maps = create_dtq_maps<entity_t>(inputs, dtq, input_to_field);
auto output_dtq_maps = create_dtq_maps<entity_t>(outputs, dtq, output_to_field);
const int test_vdim = output_fop.vdim;
const int test_op_dim = output_fop.size_on_qp / output_fop.vdim;
MFEM_VERIFY(num_entities > 0,
"The number of entities must be greater than zero");
const int num_test_dof = output_e_size / output_fop.vdim /
num_entities;
auto ir_weights = Reshape(integration_rule.GetWeights().Read(), num_qp);
auto input_size_on_qp =
get_input_size_on_qp(inputs, std::make_index_sequence<num_inputs> {});
auto action_shmem_info =
get_shmem_info<entity_t, num_fields, num_inputs, num_outputs>
(input_dtq_maps, output_dtq_maps, fields, num_entities, inputs, num_qp,
input_size_on_qp, residual_size_on_qp, element_dof_ordering);
Vector shmem_cache(action_shmem_info.total_size);
// print_shared_memory_info(action_shmem_info);
ThreadBlocks thread_blocks;
if (dimension == 3)
{
if (use_sum_factorization)
{
thread_blocks.x = q1d;
thread_blocks.y = q1d;
thread_blocks.z = q1d;
}
}
else if (dimension == 2)
{
if (use_sum_factorization)
{
thread_blocks.x = q1d;
thread_blocks.y = q1d;
thread_blocks.z = 1;
}
}
action_callbacks.push_back(
[=, restriction_callback = this->restriction_callback]
(std::vector<Vector> &solutions_l,
const std::vector<Vector> &parameters_l,
Vector &residual_l) mutable
{
restriction_callback(solutions_l, parameters_l, fields_e);
residual_e = 0.0;
auto ye = Reshape(residual_e.ReadWrite(), test_vdim, num_test_dof, num_entities);
auto wrapped_fields_e = wrap_fields(fields_e,
action_shmem_info.field_sizes,
num_entities);
const bool has_attr = domain_attributes.Size() > 0;
const auto d_domain_attr = domain_attributes.Read();
const auto d_elem_attr = elem_attributes.Read();
forall([=] MFEM_HOST_DEVICE (int e, void *shmem)
{
if (has_attr && !d_domain_attr[d_elem_attr[e] - 1]) { return; }
auto [input_dtq_shmem, output_dtq_shmem, fields_shmem, input_shmem,
residual_shmem, scratch_shmem] =
unpack_shmem(shmem, action_shmem_info, input_dtq_maps, output_dtq_maps,
wrapped_fields_e, num_qp, e);
map_fields_to_quadrature_data(
input_shmem, fields_shmem, input_dtq_shmem, input_to_field, inputs, ir_weights,
scratch_shmem, dimension, use_sum_factorization);
call_qfunction<qf_param_ts>(
qfunc, input_shmem, residual_shmem,
residual_size_on_qp, num_qp, q1d, dimension, use_sum_factorization);
auto fhat = Reshape(&residual_shmem(0, 0), test_vdim, test_op_dim, num_qp);
auto y = Reshape(&ye(0, 0, e), num_test_dof, test_vdim);
map_quadrature_data_to_fields(
y, fhat, output_fop, output_dtq_shmem[0],
scratch_shmem, dimension, use_sum_factorization);
}, num_entities, thread_blocks, action_shmem_info.total_size, shmem_cache.ReadWrite());
output_restriction_transpose(residual_e, residual_l);
});
// Create the action of the derivatives
for_constexpr([&](auto derivative_id)
{
const size_t d_field_idx = FindIdx(derivative_id, fields);
const auto direction = fields[d_field_idx];
const int da_size_on_qp = GetSizeOnQP<entity_t>(output_fop,
fields[test_space_field_idx]);
auto shmem_info =
get_shmem_info<entity_t, num_fields, num_inputs, num_outputs>
(input_dtq_maps, output_dtq_maps, fields, num_entities, inputs, num_qp,
input_size_on_qp, residual_size_on_qp, element_dof_ordering, d_field_idx);
Vector shmem_cache(shmem_info.total_size);
// print_shared_memory_info(shmem_info);
Vector direction_e;
Vector derivative_action_e(output_e_size);
derivative_action_e = 0.0;
const auto input_is_dependent = dependency_map[derivative_id];
derivative_action_callbacks[derivative_id].push_back(
[=, output_restriction_transpose = this->output_restriction_transpose](
std::vector<Vector> &fields_e, const Vector &direction_l,
Vector &derivative_action_l) mutable
{
restriction<entity_t>(direction, direction_l, direction_e, element_dof_ordering);
auto ye = Reshape(derivative_action_e.ReadWrite(), num_test_dof, test_vdim, num_entities);
auto wrapped_fields_e = wrap_fields(fields_e, shmem_info.field_sizes, num_entities);
auto wrapped_direction_e = Reshape(direction_e.ReadWrite(), shmem_info.direction_size, num_entities);
derivative_action_e = 0.0;
forall([=] MFEM_HOST_DEVICE (int e, double *shmem)
{
auto [input_dtq_shmem, output_dtq_shmem, fields_shmem, direction_shmem,
input_shmem, shadow_shmem_, residual_shmem, scratch_shmem] =
unpack_shmem(shmem, shmem_info, input_dtq_maps,
output_dtq_maps, wrapped_fields_e, wrapped_direction_e, num_qp, e);
auto &shadow_shmem = shadow_shmem_;
map_fields_to_quadrature_data(
input_shmem, fields_shmem, input_dtq_shmem, input_to_field, inputs, ir_weights,
scratch_shmem, dimension, use_sum_factorization);
// TODO: Probably redundant
set_zero(shadow_shmem);
map_direction_to_quadrature_data_conditional(
shadow_shmem, direction_shmem, input_dtq_shmem, inputs, ir_weights,
scratch_shmem, input_is_dependent, dimension, use_sum_factorization);
call_qfunction_derivative_action<qf_param_ts>(
qfunc, input_shmem, shadow_shmem, residual_shmem,
da_size_on_qp, num_qp, q1d, dimension, use_sum_factorization);
auto fhat = Reshape(&residual_shmem(0, 0), test_vdim, test_op_dim, num_qp);
auto y = Reshape(&ye(0, 0, e), num_test_dof, test_vdim);
map_quadrature_data_to_fields(
y, fhat, output_fop, output_dtq_shmem[0],
scratch_shmem, dimension, use_sum_factorization);
}, num_entities, thread_blocks, shmem_info.total_size, shmem_cache.ReadWrite());
output_restriction_transpose(derivative_action_e, derivative_action_l);
});
}, derivative_ids);
// Create the transpose action of the derivatives
if (!use_sum_factorization)
{
for_constexpr([&](auto derivative_id)
{
const size_t d_field_idx = FindIdx(derivative_id, fields);
const auto direction = fields[test_space_field_idx];
const int da_size_on_qp = GetSizeOnQP<entity_t>(output_fop,
fields[test_space_field_idx]);
auto shmem_info =
get_shmem_info<entity_t, num_fields, num_inputs, num_outputs>
(input_dtq_maps, output_dtq_maps, fields, num_entities, inputs, num_qp,
input_size_on_qp, residual_size_on_qp, element_dof_ordering,
test_space_field_idx);
Vector shmem_cache(shmem_info.total_size);
// print_shared_memory_info(shmem_info);
auto [RT, e_size] = get_restriction_transpose<entity_t>(
fields[d_field_idx],
element_dof_ordering,
mfem::get<0>(inputs)); // TODO
Vector direction_e;
Vector daction_transpose_e(e_size);
daction_transpose_e = 0.0;
const auto input_is_dependent = dependency_map[derivative_id];
const int trial_vdim = GetVDim(fields[0]);
int total_trial_op_dim = 0;
for_constexpr<num_inputs>([&](auto s)
{
if (!input_is_dependent[s])
{
return;
}
auto B = is_value_fop<decltype(mfem::get<s>(inputs))>::value ?
input_dtq_maps[s].B : input_dtq_maps[s].G;
total_trial_op_dim += B.GetShape()[DofToQuadMap::Index::DIM];
});
daction_transpose_callbacks[derivative_id].push_back(
[=, restriction_transpose = RT](
std::vector<Vector> &fields_e, const Vector &direction_l,
Vector &daction_l) mutable
{
auto shmem = shmem_cache.ReadWrite();
restriction<entity_t>(direction, direction_l, direction_e, element_dof_ordering);
auto ye = Reshape(daction_transpose_e.ReadWrite(), num_test_dof, trial_vdim, num_entities);
auto wrapped_fields_e = wrap_fields(fields_e, shmem_info.field_sizes, num_entities);
auto wrapped_direction_e = Reshape(direction_e.ReadWrite(), shmem_info.direction_size, num_entities);
Vector a_qp_mem(test_vdim * test_op_dim * trial_vdim * total_trial_op_dim);
auto a_qp = Reshape(a_qp_mem.ReadWrite(), test_vdim, test_op_dim,
trial_vdim, total_trial_op_dim);
Vector dir_mem(shmem_info.shadow_sizes[test_space_field_idx]);
auto dir = Reshape(dir_mem.ReadWrite(), input_size_on_qp[test_space_field_idx], num_qp);
daction_transpose_e = 0.0;
for (int e = 0; e < num_entities; e++)
{
auto [input_dtq_shmem, output_dtq_shmem, fields_shmem, direction_shmem,
input_shmem_, shadow_shmem_, residual_shmem_, scratch_shmem] =
unpack_shmem(shmem, shmem_info, input_dtq_maps,
output_dtq_maps, wrapped_fields_e, wrapped_direction_e, num_qp, e);
// avoid captured structured bindings
auto &input_shmem = input_shmem_;
auto &shadow_shmem = shadow_shmem_;
auto &residual_shmem = residual_shmem_;
map_fields_to_quadrature_data(
input_shmem, fields_shmem, input_dtq_shmem, input_to_field, inputs, ir_weights,
scratch_shmem, dimension, use_sum_factorization);
set_zero(shadow_shmem);
std::array<bool, num_inputs> direction_is_dependent{false};
direction_is_dependent[test_space_field_idx] = true;
map_direction_to_quadrature_data_conditional(
shadow_shmem, direction_shmem, input_dtq_shmem, inputs, ir_weights,
scratch_shmem, direction_is_dependent, use_sum_factorization);
copy(shadow_shmem[test_space_field_idx], dir);
set_zero(shadow_shmem);
// pretty_print(dir_mem);
for (int q = 0; q < num_qp; q++)
{
for (int j = 0; j < trial_vdim; j++)
{
size_t m_offset = 0;
for_constexpr<num_inputs>([&](auto s)
{
if (!input_is_dependent[s])
{
return;
}
auto B = is_value_fop<std::decay_t<decltype(mfem::get<s>(inputs))>>::value ?
input_dtq_maps[s].B : input_dtq_maps[s].G;
auto trial_op_dim = B.GetShape()[DofToQuadMap::Index::DIM];
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), da_size_on_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
MFEM_ABORT("Native dual support is not enabled!");
// 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++)
{
a_qp(i, k, j, m + m_offset) = f(i, k);
}
}
}
m_offset += trial_op_dim;
});
}
// pretty_print(a_qp_mem);
// Multiply transpose of a_qp with direction
// auto fhat = Reshape(&residual_shmem(0, 0), test_vdim, test_op_dim, num_qp);
// auto dir_qp = Reshape(&dir[0], trial_vdim, total_trial_op_dim, num_qp);
auto fhat = Reshape(&residual_shmem(0, 0), trial_vdim, total_trial_op_dim,
num_qp);
auto dir_qp = Reshape(&dir(0, 0), test_vdim, test_op_dim, num_qp);
for (int i = 0; i < trial_vdim; i++)
{
for (int k = 0; k < total_trial_op_dim; k++)
{
fhat(i, k, q) = 0.0;
for (int j = 0; j < test_vdim; j++)
{
for (int m = 0; m < test_op_dim; m++)
{
fhat(i, k, q) += a_qp(j, m, i, k) * dir_qp(j, m, q);
}
}
}
}
}
auto fhat = Reshape(&residual_shmem(0, 0), trial_vdim, total_trial_op_dim,
num_qp);
int num_trial_dof = input_dtq_shmem[0].B.GetShape()[DofToQuadMap::Index::DOF];
auto y = Reshape(&ye(0, 0, e), num_trial_dof, trial_vdim);
map_quadrature_data_to_fields(
y, fhat, mfem::get<0>(inputs), input_dtq_shmem[0],
scratch_shmem, dimension, use_sum_factorization);
}
restriction_transpose(daction_transpose_e, daction_l);
});
}, derivative_ids);
}
}
} // namespace mfem
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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
namespace mfem
{
template <int FIELD_ID = -1>
class FieldOperator
{
public:
constexpr FieldOperator(int size_on_qp = 0) :
size_on_qp(size_on_qp) {};
static constexpr int GetFieldId() { return FIELD_ID; }
int size_on_qp = -1;
int dim = -1;
int vdim = -1;
};
template <int FIELD_ID = -1>
class None : public FieldOperator<FIELD_ID>
{
public:
constexpr None() : FieldOperator<FIELD_ID>() {}
};
template< typename T >
struct is_none_fop
{
static const bool value = false;
};
template <int FIELD_ID>
struct is_none_fop<None<FIELD_ID>>
{
static const bool value = true;
};
template <typename T>
struct DisableAD
{
T& operator()() const { return fop; }
T fop;
};
class Weight : public FieldOperator<-1>
{
public:
constexpr Weight() : FieldOperator<-1>() {};
};
template< typename T >
struct is_weight_fop
{
static const bool value = false;
};
template <>
struct is_weight_fop<Weight>
{
static const bool value = true;
};
template <int FIELD_ID = -1>
class Value : public FieldOperator<FIELD_ID>
{
public:
constexpr Value() : FieldOperator<FIELD_ID>() {};
};
template< typename T >
struct is_value_fop
{
static const bool value = false;
};
template <int FIELD_ID>
struct is_value_fop<Value<FIELD_ID>>
{
static const bool value = true;
};
template <typename T>
struct is_value_fop<DisableAD<T>>
{
static const bool value = is_value_fop<T>::value;
};
template <int FIELD_ID = -1>
class Gradient : public FieldOperator<FIELD_ID>
{
public:
constexpr Gradient() : FieldOperator<FIELD_ID>() {};
};
template< typename T >
struct is_gradient_fop
{
static const bool value = false;
};
template <int FIELD_ID>
struct is_gradient_fop<Gradient<FIELD_ID>>
{
static const bool value = true;
};
template <int FIELD_ID = -1>
class One : public FieldOperator<FIELD_ID>
{
public:
constexpr One() : FieldOperator<FIELD_ID>() {};
};
template< typename T >
struct is_one_fop
{
static const bool value = false;
};
template <int FIELD_ID>
struct is_one_fop<One<FIELD_ID>>
{
static const bool value = true;
};
} // namespace mfem
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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 "util.hpp"
namespace mfem
{
template <typename output_t>
MFEM_HOST_DEVICE
void map_quadrature_data_to_fields_impl(
DeviceTensor<2, double> &y,
const DeviceTensor<3, double> &f,
const output_t &output,
const DofToQuadMap &dtq)
{
auto B = dtq.B;
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++)
{
double 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++)
{
double 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_one_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_none_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("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_2d(
DeviceTensor<2, double> &y,
const DeviceTensor<3, double> &f,
const output_t &output,
const DofToQuadMap &dtq,
std::array<DeviceTensor<1>, 6> &scratch_mem)
{
auto B = dtq.B;
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)
{
double 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)
{
double 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_none_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("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, double> &y,
const DeviceTensor<3, double> &f,
const output_t &output,
const DofToQuadMap &dtq,
std::array<DeviceTensor<1>, 6> &scratch_mem)
{
auto B = dtq.B;
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)
{
double 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)
{
double 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)
{
double 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_none_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("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, double> &y,
const DeviceTensor<3, double> &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 == 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
{
map_quadrature_data_to_fields_impl(y, f, output, dtq);
}
}
}
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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 "util.hpp"
namespace mfem
{
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 double> &integration_weights,
const std::array<DeviceTensor<1>, 6> &scratch_mem)
{
auto B = dtq.B;
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)
{
double 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)
{
double 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)
{
double 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(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_none_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(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 double> &integration_weights,
const std::array<DeviceTensor<1>, 6> &scratch_mem)
{
auto B = dtq.B;
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)
{
double 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)
{
double 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(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_none_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(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 double> &integration_weights)
{
auto B = dtq.B;
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++)
{
double 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++)
{
double 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, FaceNormal>)
// {
// auto normal = geometric_factors.normal;
// auto [num_qp, dim, num_entities] = normal.GetShape();
// auto f = Reshape(&field_qp[0], dim, num_qp);
// for (int qp = 0; qp < num_qp; qp++)
// {
// for (int d = 0; d < dim; d++)
// {
// f(d, qp) = normal(qp, d, entity_idx);
// }
// }
// }
// TODO: Create separate function for clarity
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_none_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(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<int, num_inputs> &input_to_field,
const field_operator_ts &fops,
const DeviceTensor<1, const double> &integration_weights,
const std::array<DeviceTensor<1>, 6> &scratch_mem,
const int &dimension,
const bool &use_sum_factorization = false)
{
for_constexpr<num_inputs>([&](auto i)
{
if (use_sum_factorization)
{
if (dimension == 2)
{
map_field_to_quadrature_data_tensor_product_2d(
fields_qp[i], dtqmaps[i], fields_e[input_to_field[i]], mfem::get<i>(fops),
integration_weights, scratch_mem);
}
else if (dimension == 3)
{
map_field_to_quadrature_data_tensor_product_3d(
fields_qp[i], dtqmaps[i], fields_e[input_to_field[i]], mfem::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], fields_e[input_to_field[i]], mfem::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 double> &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 == 2)
{
map_field_to_quadrature_data_tensor_product_3d(
field_qp, dtqmap, field_e, fop, integration_weights, scratch_mem);
}
else if (dimension == 3)
{
map_field_to_quadrature_data_tensor_product_2d(
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 double>, num_fields> &fields_e,
const std::array<DofToQuadMap, num_inputs> &dtqmaps,
field_operator_ts fops,
const DeviceTensor<1, const double> &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], mfem::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 double> &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 = false)
{
for_constexpr<num_inputs>([&](auto i)
{
if (conditions[i])
{
if (use_sum_factorization)
{
if (dimension == 2)
{
map_field_to_quadrature_data_tensor_product_2d(
directions_qp[i], dtqmaps[i], direction_e, mfem::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, mfem::get<i>(fops),
integration_weights, scratch_mem);
}
}
else
{
map_field_to_quadrature_data(
directions_qp[i], dtqmaps[i], direction_e, mfem::get<i>(fops),
integration_weights);
}
}
});
}
}
+126
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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 "../fe/fe_base.hpp"
namespace mfem
{
class ParametricSpace
{
public:
/// spatial_dim is the dimension of the spatial domain (e.g. 2 for 2D)
/// local_size is the size of the data on a single quadrature point
/// element_size is the size of the data on an element divided by vdim
/// total_size is the size of the data for all elements
ParametricSpace(int spatial_dim, int local_size, int element_size,
int total_size) :
spatial_dim(spatial_dim),
local_size(local_size),
element_size(element_size),
total_size(total_size),
identity(total_size)
{
// dtq.ndof = (int)floor(pow(element_size, 1.0/spatial_dim) + 0.5);
dtq.ndof = element_size;
dtq.nqpt = dtq.ndof;
}
ParametricSpace(int local_size) :
local_size(local_size),
element_size(local_size),
total_size(local_size),
identity(local_size)
{
dtq.ndof = (int)floor(pow(element_size, 1.0/spatial_dim) + 0.5);
dtq.nqpt = dtq.ndof;
}
ParametricSpace(int spatial_dim, int local_size, int element_size,
int total_size, int d1d, int q1d) :
spatial_dim(spatial_dim),
local_size(local_size),
element_size(element_size),
total_size(total_size),
identity(total_size)
{
dtq.ndof = d1d;
dtq.nqpt = q1d;
}
int Dimension() const
{
return spatial_dim;
}
int GetLocalSize() const
{
return local_size;
}
int GetElementSize() const
{
return element_size;
}
int GetTotalSize() const
{
return total_size;
}
const DofToQuad &GetDofToQuad() const
{
return dtq;
}
const Operator *GetProlongation() const
{
return &identity;
}
const Operator *GetRestriction() const
{
return &identity;
}
private:
int spatial_dim;
// Hint for the local dimension. E.g. the size on the quadrature point or vdim.
int local_size;
// Size of the data on an element
int element_size;
int total_size;
IdentityOperator identity;
DofToQuad dtq;
};
class ParametricFunction : public Vector
{
public:
ParametricFunction(ParametricSpace &space) :
Vector(space.GetTotalSize()),
space(space)
{}
ParametricSpace &space;
using Vector::operator=;
};
}
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@@ -0,0 +1,272 @@
// 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
{
template <typename func_t, typename... arg_ts>
MFEM_HOST_DEVICE inline
auto qfunction_wrapper(const func_t &f, arg_ts &&...args)
{
return f(args...);
}
template <typename T0, typename T1>
MFEM_HOST_DEVICE inline
void process_kf_arg(const T0 &, T1 &)
{
static_assert(always_false<T0, T1>,
"process_kf_arg not implemented for arg type");
}
template <typename T>
MFEM_HOST_DEVICE inline
void process_kf_arg(
const DeviceTensor<1, T> &u,
T &arg)
{
arg = u(0);
}
template <typename T>
MFEM_HOST_DEVICE inline
void process_kf_arg(
const DeviceTensor<1, T> &u,
internal::tensor<T> &arg)
{
arg(0) = u(0);
}
template <typename T, int n>
MFEM_HOST_DEVICE inline
void process_kf_arg(
const DeviceTensor<1> &u,
internal::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_kf_arg(
const DeviceTensor<1> &u,
internal::tensor<T, n, m> &arg)
{
for (int i = 0; i < m; i++)
{
for (int j = 0; j < n; j++)
{
arg(j, i) = u((i * m) + j);
}
}
}
template <typename arg_type>
MFEM_HOST_DEVICE inline
void process_kf_arg(const DeviceTensor<2> &u, arg_type &arg, int qp)
{
const auto u_qp = Reshape(&u(0, qp), u.GetShape()[0]);
process_kf_arg(u_qp, arg);
}
template <size_t num_fields, typename kf_args>
MFEM_HOST_DEVICE inline
void process_kf_args(
const std::array<DeviceTensor<2>, num_fields> &u,
kf_args &args,
const int &qp)
{
for_constexpr<mfem::tuple_size<kf_args>::value>([&](auto i)
{
process_kf_arg(u[i], mfem::get<i>(args), qp);
// out << mfem::get<i>(args) << ", ";
});
}
template <typename T0, typename T1>
MFEM_HOST_DEVICE inline
Vector process_kf_result(T0, T1)
{
static_assert(always_false<T0, T1>,
"process_kf_result not implemented for result type");
return Vector{};
}
template <typename T>
MFEM_HOST_DEVICE inline
void process_kf_result(
DeviceTensor<1, T> &r,
const double &x)
{
r(0) = x;
}
template <typename T>
MFEM_HOST_DEVICE inline
void process_kf_result(
DeviceTensor<1, T> &r,
const internal::tensor<T> &x)
{
r(0) = x(0);
}
template <typename T, int n>
MFEM_HOST_DEVICE inline
void process_kf_result(
DeviceTensor<1, T> &r,
const internal::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_kf_result(
DeviceTensor<1, T> &r,
const internal::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>
MFEM_HOST_DEVICE inline
void process_kf_arg(
const DeviceTensor<1> &u,
const DeviceTensor<1> &v,
double &arg)
{
arg = u(0);
}
template <int n, int m>
MFEM_HOST_DEVICE inline
void process_kf_arg(
const DeviceTensor<1> &u,
const DeviceTensor<1> &v,
internal::tensor<double, n, m> &arg)
{
for (int i = 0; i < m; i++)
{
for (int j = 0; j < n; j++)
{
arg(j, i) = u((i * m) + j);
}
}
}
template <typename qfunc_t, typename args_ts, size_t num_args>
MFEM_HOST_DEVICE inline
void apply_kernel(
DeviceTensor<1, double> &f_qp,
const qfunc_t &qfunc,
args_ts &args,
const std::array<DeviceTensor<2>, num_args> &u,
int qp)
{
process_kf_args(u, args, qp);
process_kf_result(f_qp, mfem::get<0>(mfem::apply(qfunc, args)));
}
#ifdef MFEM_USE_ENZYME
// 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(mfem::get<Is>(args))...>, enzyme_const,
(void *)&qfunc, enzyme_dup, &mfem::get<Is>(args)..., enzyme_interleave,
&mfem::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(mfem::get<Is>(args))...,
decltype(mfem::get<Js>(inactive_args))...>,
enzyme_const, (void *)&qfunc, enzyme_dup, &mfem::get<Is>(args)...,
enzyme_const, &mfem::get<Js>(inactive_args)..., enzyme_interleave,
&mfem::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<
mfem::tuple_size<std::remove_reference_t<arg_ts>>::value> {};
auto inactive_arg_indices = std::make_index_sequence<
mfem::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, double> &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)
{
// out << "\nargs: ";
process_kf_args(u, args, qp_idx);
// out << "\nshadow args: ";
process_kf_args(v, shadow_args, qp_idx);
// out << "\n";
process_kf_result(f_qp,
mfem::get<0>(fwddiff_apply_enzyme(qfunc, args, shadow_args, mfem::tuple<> {})));
}
#endif // MFEM_USE_ENZYME
} // namespace mfem
@@ -0,0 +1,49 @@
export LC_USER=andrej1
module load rocmcc/6.3.1-cce-19.0.0-magic cmake/3.29.2
export MPICH_CC=amdclang
export MPICH_CXX=amdclang++
export ROCM_PATH=/opt/rocm-6.3.1
export LLVM_DIR=$ROCM_PATH/lib/llvm
export MPI_DIR=/usr/tce/packages/cray-mpich/cray-mpich-8.1.32-rocmcc-6.3.1-cce-19.0.0-magic
export CMAKE_PREFIX_PATH=$CMAKE_PREFIX_PATH:$ROCM_PATH/lib/cmake/hip:$ROCM_PATH/lib/cmake/hipblas:$ROCM_PATH/lib/cmake/hipblas-common:$ROCM_PATH/lib/cmake/hipsparse:$ROCM_PATH/lib/cmake/rocsparse:$ROCM_PATH/lib/cmake/rocrand
export BASE_DIR=/usr/workspace/$LC_USER/dfem-tuo-magic
export LOCAL_DIR=/usr/workspace/$LC_USER/dfem-tuo-magic/local
mkdir -p $LOCAL_DIR
export PATH=$LOCAL_DIR/bin:$PATH
cd $BASE_DIR
## Enzyme
git clone --depth 1 https://github.com/EnzymeAD/Enzyme.git
pushd Enzyme/enzyme
CC=amdclang CXX=amdclang++ cmake -B build -DLLVM_DIR=$LLVM_DIR -DCMAKE_INSTALL_PREFIX=$LOCAL_DIR
cmake --build build -j && cmake --install build
popd
## hypre
curl https://github.com/hypre-space/hypre/archive/refs/tags/v2.32.0.tar.gz -o hypre-v2.32.0.tar.gz -L
tar xzf hypre-v2.32.0.tar.gz
pushd hypre-2.32.0/src
CC=mpicc CXX=mpicxx CXXFLAGS="std=c++17 -fPIC" CFLAGS="-fPIC" ROCM_PATH=$ROCM_PATH ./configure --disable-fortran --prefix=$LOCAL_DIR --with-MPI-libs="mpi mpich" --with-MPI-lib-dirs=$MPI_DIR/lib --with-MPI-include=$MPI_DIR/include --enable-shared --with-hip
make -j install
popd
## metis
curl -OL https://github.com/mfem/tpls/raw/gh-pages/parmetis-4.0.3.tar.gz
tar xzf parmetis-4.0.3.tar.gz
pushd parmetis-4.0.3
cmake -B build -DCMAKE_CXX_FLAGS="-fPIC" -DCMAKE_C_FLAGS="-fPIC" -DGKLIB_PATH=$BASE_DIR/parmetis-4.0.3/metis/GKlib -DMETIS_PATH=$BASE_DIR/parmetis-4.0.3/metis -DCMAKE_INSTALL_PREFIX=$LOCAL_DIR -DSHARED=1 -DCMAKE_C_COMPILER=mpicc -DCMAKE_CXX_COMPILER=mpicxx
cmake --build build -j && cmake --install build
popd
pushd parmetis-4.0.3/metis
cmake -B build -DCMAKE_CXX_FLAGS="-fPIC" -DCMAKE_C_FLAGS="-fPIC" -DGKLIB_PATH=$BASE_DIR/parmetis-4.0.3/metis/GKlib -DCMAKE_INSTALL_PREFIX=$LOCAL_DIR -DSHARED=1 -DCMAKE_C_COMPILER=mpicc -DCMAKE_CXX_COMPILER=mpicxx
cmake --build build -j && cmake --install build
popd
git clone https://github.com/mfem/mfem.git
git switch dfem-phase1-dev
pushd mfem
CXX=mpicxx cmake -B build-opt -DCMAKE_BUILD_TYPE=Release -DMFEM_USE_HIP=ON -DCMAKE_HIP_ARCHITECTURES="gfx942" -DCMAKE_HIP_PLATFORM="amd"
cmake --build build-opt -j
+31
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@@ -0,0 +1,31 @@
if (NOT CMAKE_BUILD_TYPE)
set(CMAKE_BUILD_TYPE "Release" CACHE STRING
"Build type: Debug, Release, RelWithDebInfo, or MinSizeRel." FORCE)
endif()
set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
set(CMAKE_CXX_STANDARD 17)
# set(CMAKE_CXX_FLAGS "--save-temps -Rpass-analysis=kernel-resource-usage -mllvm -amdgpu-early-inline-all=true -mllvm -amdgpu-function-calls=false")
set(MFEM_PRECISION "double" CACHE STRING
"Floating-point precision to use: single, or double")
option(BUILD_SHARED_LIBS "Enable shared library build of MFEM" ON)
option(MFEM_USE_MPI "Enable MPI parallel build" ON)
option(MFEM_USE_METIS "Enable METIS usage" ${MFEM_USE_MPI})
option(MFEM_USE_ENZYME "Enable Enzyme" ON)
option(MFEM_USE_HIP "Enable HIP" ON)
set(MFEM_MPI_NP 4 CACHE STRING "Number of processes used for MPI tests")
option(MFEM_ENABLE_TESTING ON)
set(HIP_ARCH "gfx942" CACHE STRING "Target HIP architecture.")
# Make sure all dirs are absolute
set(ENZYME_DIR "/usr/workspace/andrej1/dfem-tuo-magic/local/cmake/Enzyme" CACHE PATH "Path to the Enzyme library.")
set(HYPRE_DIR "/usr/workspace/andrej1/dfem-tuo-magic/local" CACHE PATH "Path to the hypre library.")
set(METIS_DIR "/usr/workspace/andrej1/dfem-tuo-magic/local" CACHE PATH "Path to the METIS library.")
set(CMAKE_SKIP_PREPROCESSED_SOURCE_RULES ON) # Skip *.i rules
set(CMAKE_SKIP_ASSEMBLY_SOURCE_RULES ON) # Skip *.s rules
+853
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@@ -0,0 +1,853 @@
// 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
// This is serac's tuple implementation
#include <utility>
#include <mfem.hpp>
namespace mfem
{
/**
* @tparam T the types stored in the tuple
* @brief This is a class that mimics most of std::tuple's interface,
* except that it is usable in CUDA kernels and admits some arithmetic operator overloads.
*
* see https://en.cppreference.com/w/cpp/utility/tuple for more information about std::tuple
*/
template <typename... T>
struct tuple
{
};
/**
* @brief Type that mimics std::tuple
*
* @tparam T0 The first type stored in the tuple
*/
template <typename T0>
struct tuple<T0>
{
T0 v0; ///< The first member of the tuple
};
/**
* @brief Type that mimics std::tuple
*
* @tparam T0 The first type stored in the tuple
* @tparam T1 The second type stored in the tuple
*/
template <typename T0, typename T1>
struct tuple<T0, T1>
{
T0 v0; ///< The first member of the tuple
T1 v1; ///< The second member of the tuple
};
/**
* @brief Type that mimics std::tuple
*
* @tparam T0 The first type stored in the tuple
* @tparam T1 The second type stored in the tuple
* @tparam T2 The third type stored in the tuple
*/
template <typename T0, typename T1, typename T2>
struct tuple<T0, T1, T2>
{
T0 v0; ///< The first member of the tuple
T1 v1; ///< The second member of the tuple
T2 v2; ///< The third member of the tuple
};
/**
* @brief Type that mimics std::tuple
*
* @tparam T0 The first type stored in the tuple
* @tparam T1 The second type stored in the tuple
* @tparam T2 The third type stored in the tuple
* @tparam T3 The fourth type stored in the tuple
*/
template <typename T0, typename T1, typename T2, typename T3>
struct tuple<T0, T1, T2, T3>
{
T0 v0; ///< The first member of the tuple
T1 v1; ///< The second member of the tuple
T2 v2; ///< The third member of the tuple
T3 v3; ///< The fourth member of the tuple
};
/**
* @brief Type that mimics std::tuple
*
* @tparam T0 The first type stored in the tuple
* @tparam T1 The second type stored in the tuple
* @tparam T2 The third type stored in the tuple
* @tparam T3 The fourth type stored in the tuple
* @tparam T4 The fifth type stored in the tuple
*/
template <typename T0, typename T1, typename T2, typename T3, typename T4>
struct tuple<T0, T1, T2, T3, T4>
{
T0 v0; ///< The first member of the tuple
T1 v1; ///< The second member of the tuple
T2 v2; ///< The third member of the tuple
T3 v3; ///< The fourth member of the tuple
T4 v4; ///< The fifth member of the tuple
};
/**
* @brief Type that mimics std::tuple
*
* @tparam T0 The first type stored in the tuple
* @tparam T1 The second type stored in the tuple
* @tparam T2 The third type stored in the tuple
* @tparam T3 The fourth type stored in the tuple
* @tparam T4 The fifth type stored in the tuple
* @tparam T5 The sixth type stored in the tuple
*/
template <typename T0, typename T1, typename T2, typename T3, typename T4, typename T5>
struct tuple<T0, T1, T2, T3, T4, T5>
{
T0 v0; ///< The first member of the tuple
T1 v1; ///< The second member of the tuple
T2 v2; ///< The third member of the tuple
T3 v3; ///< The fourth member of the tuple
T4 v4; ///< The fifth member of the tuple
T5 v5; ///< The sixth member of the tuple
};
/**
* @brief Type that mimics std::tuple
*
* @tparam T0 The first type stored in the tuple
* @tparam T1 The second type stored in the tuple
* @tparam T2 The third type stored in the tuple
* @tparam T3 The fourth type stored in the tuple
* @tparam T4 The fifth type stored in the tuple
* @tparam T5 The sixth type stored in the tuple
* @tparam T6 The seventh type stored in the tuple
*/
template <typename T0, typename T1, typename T2, typename T3, typename T4, typename T5, typename T6>
struct tuple<T0, T1, T2, T3, T4, T5, T6>
{
T0 v0; ///< The first member of the tuple
T1 v1; ///< The second member of the tuple
T2 v2; ///< The third member of the tuple
T3 v3; ///< The fourth member of the tuple
T4 v4; ///< The fifth member of the tuple
T5 v5; ///< The sixth member of the tuple
T6 v6; ///< The seventh member of the tuple
};
/**
* @brief Type that mimics std::tuple
*
* @tparam T0 The first type stored in the tuple
* @tparam T1 The second type stored in the tuple
* @tparam T2 The third type stored in the tuple
* @tparam T3 The fourth type stored in the tuple
* @tparam T4 The fifth type stored in the tuple
* @tparam T5 The sixth type stored in the tuple
* @tparam T6 The seventh type stored in the tuple
* @tparam T7 The eighth type stored in the tuple
*/
template <typename T0, typename T1, typename T2, typename T3, typename T4, typename T5, typename T6, typename T7>
struct tuple<T0, T1, T2, T3, T4, T5, T6, T7>
{
T0 v0; ///< The first member of the tuple
T1 v1; ///< The second member of the tuple
T2 v2; ///< The third member of the tuple
T3 v3; ///< The fourth member of the tuple
T4 v4; ///< The fifth member of the tuple
T5 v5; ///< The sixth member of the tuple
T6 v6; ///< The seventh member of the tuple
T7 v7; ///< The eighth member of the tuple
};
template <typename T0, typename T1, typename T2, typename T3, typename T4, typename T5, typename T6, typename T7, typename T8>
struct tuple<T0, T1, T2, T3, T4, T5, T6, T7, T8>
{
T0 v0; ///< The first member of the tuple
T1 v1; ///< The second member of the tuple
T2 v2; ///< The third member of the tuple
T3 v3; ///< The fourth member of the tuple
T4 v4; ///< The fifth member of the tuple
T5 v5; ///< The sixth member of the tuple
T6 v6; ///< The seventh member of the tuple
T7 v7; ///< The eighth member of the tuple
T8 v8;
};
/**
* @brief Class template argument deduction rule for tuples
* @tparam T The variadic template parameter for tuple types
*/
template <typename... T>
MFEM_HOST_DEVICE
tuple(T...) -> tuple<T...>;
/**
* @brief helper function for combining a list of values into a tuple
* @tparam T types of the values to be tuple-d
* @param args the actual values to be put into a tuple
*/
template <typename... T>
MFEM_HOST_DEVICE tuple<T...> make_tuple(const T&... args)
{
return tuple<T...> {args...};
}
template <class... Types>
struct tuple_size
{
};
template <class... Types>
struct tuple_size<mfem::tuple<Types...>> :
std::integral_constant<std::size_t, sizeof...(Types)>
{
};
/**
* @tparam i the tuple index to access
* @tparam T the types stored in the tuple
* @brief return a reference to the ith tuple entry
*/
template <int i, typename... T>
MFEM_HOST_DEVICE constexpr auto& get(tuple<T...>& values)
{
static_assert(i < sizeof...(T), "");
if constexpr (i == 0)
{
return values.v0;
}
if constexpr (i == 1)
{
return values.v1;
}
if constexpr (i == 2)
{
return values.v2;
}
if constexpr (i == 3)
{
return values.v3;
}
if constexpr (i == 4)
{
return values.v4;
}
if constexpr (i == 5)
{
return values.v5;
}
if constexpr (i == 6)
{
return values.v6;
}
if constexpr (i == 7)
{
return values.v7;
}
if constexpr (i == 8)
{
return values.v8;
}
}
/**
* @tparam i the tuple index to access
* @tparam T the types stored in the tuple
* @brief return a copy of the ith tuple entry
*/
template <int i, typename... T>
MFEM_HOST_DEVICE constexpr const auto& get(const tuple<T...>& values)
{
static_assert(i < sizeof...(T), "");
if constexpr (i == 0)
{
return values.v0;
}
if constexpr (i == 1)
{
return values.v1;
}
if constexpr (i == 2)
{
return values.v2;
}
if constexpr (i == 3)
{
return values.v3;
}
if constexpr (i == 4)
{
return values.v4;
}
if constexpr (i == 5)
{
return values.v5;
}
if constexpr (i == 6)
{
return values.v6;
}
if constexpr (i == 7)
{
return values.v7;
}
if constexpr (i == 8)
{
return values.v8;
}
}
/**
* @brief a function intended to be used for extracting the ith type from a tuple.
*
* @note type<i>(my_tuple) returns a value, whereas get<i>(my_tuple) returns a reference
*
* @tparam i the index of the tuple to query
* @tparam T the types stored in the tuple
* @param values the tuple of values
* @return a copy of the ith entry of the input
*/
template <int i, typename... T>
MFEM_HOST_DEVICE constexpr auto type(const tuple<T...>& values)
{
static_assert(i < sizeof...(T), "");
if constexpr (i == 0)
{
return values.v0;
}
if constexpr (i == 1)
{
return values.v1;
}
if constexpr (i == 2)
{
return values.v2;
}
if constexpr (i == 3)
{
return values.v3;
}
if constexpr (i == 4)
{
return values.v4;
}
if constexpr (i == 5)
{
return values.v5;
}
if constexpr (i == 6)
{
return values.v6;
}
if constexpr (i == 7)
{
return values.v7;
}
if constexpr (i == 8)
{
return values.v8;
}
}
/**
* @brief A helper function for the + operator of tuples
*
* @tparam S the types stored in the tuple x
* @tparam T the types stored in the tuple y
* @tparam i The integer sequence to i
* @param x tuple of values
* @param y tuple of values
* @return the returned tuple sum
*/
template <typename... S, typename... T, int... i>
MFEM_HOST_DEVICE constexpr auto plus_helper(const tuple<S...>& x,
const tuple<T...>& y,
std::integer_sequence<int, i...>)
{
return tuple{get<i>(x) + get<i>(y)...};
}
/**
* @tparam S the types stored in the tuple x
* @tparam T the types stored in the tuple y
* @param x a tuple of values
* @param y a tuple of values
* @brief return a tuple of values defined by elementwise sum of x and y
*/
template <typename... S, typename... T>
MFEM_HOST_DEVICE constexpr auto operator+(const tuple<S...>& x,
const tuple<T...>& y)
{
static_assert(sizeof...(S) == sizeof...(T));
return plus_helper(x, y,
std::make_integer_sequence<int, static_cast<int>(sizeof...(S))>());
}
/**
* @brief A helper function for the += operator of tuples
*
* @tparam T the types stored in the tuples x and y
* @tparam i integer sequence used to index the tuples
* @param x tuple of values to be incremented
* @param y tuple of increment values
*/
template <typename... T, int... i>
MFEM_HOST_DEVICE constexpr void plus_equals_helper(tuple<T...>& x,
const tuple<T...>& y,
std::integer_sequence<int, i...>)
{
((get<i>(x) += get<i>(y)), ...);
}
/**
* @tparam T the types stored in the tuples x and y
* @param x a tuple of values
* @param y a tuple of values
* @brief add values contained in y, to the tuple x
*/
template <typename... T>
MFEM_HOST_DEVICE constexpr auto operator+=(tuple<T...>& x,
const tuple<T...>& y)
{
return plus_equals_helper(x, y,
std::make_integer_sequence<int, static_cast<int>(sizeof...(T))>());
}
/**
* @brief A helper function for the -= operator of tuples
*
* @tparam T the types stored in the tuples x and y
* @tparam i integer sequence used to index the tuples
* @param x tuple of values to be subracted from
* @param y tuple of values to subtract from x
*/
template <typename... T, int... i>
MFEM_HOST_DEVICE constexpr void minus_equals_helper(tuple<T...>& x,
const tuple<T...>& y,
std::integer_sequence<int, i...>)
{
((get<i>(x) -= get<i>(y)), ...);
}
/**
* @tparam T the types stored in the tuples x and y
* @param x a tuple of values
* @param y a tuple of values
* @brief add values contained in y, to the tuple x
*/
template <typename... T>
MFEM_HOST_DEVICE constexpr auto operator-=(tuple<T...>& x,
const tuple<T...>& y)
{
return minus_equals_helper(x, y,
std::make_integer_sequence<int, static_cast<int>(sizeof...(T))>());
}
/**
* @brief A helper function for the - operator of tuples
*
* @tparam S the types stored in the tuple x
* @tparam T the types stored in the tuple y
* @tparam i The integer sequence to i
* @param x tuple of values
* @param y tuple of values
* @return the returned tuple difference
*/
template <typename... S, typename... T, int... i>
MFEM_HOST_DEVICE constexpr auto minus_helper(const tuple<S...>& x,
const tuple<T...>& y,
std::integer_sequence<int, i...>)
{
return tuple{get<i>(x) - get<i>(y)...};
}
/**
* @tparam S the types stored in the tuple x
* @tparam T the types stored in the tuple y
* @param x a tuple of values
* @param y a tuple of values
* @brief return a tuple of values defined by elementwise difference of x and y
*/
template <typename... S, typename... T>
MFEM_HOST_DEVICE constexpr auto operator-(const tuple<S...>& x,
const tuple<T...>& y)
{
static_assert(sizeof...(S) == sizeof...(T));
return minus_helper(x, y,
std::make_integer_sequence<int, static_cast<int>(sizeof...(S))>());
}
/**
* @brief A helper function for the - operator of tuples
*
* @tparam T the types stored in the tuple y
* @tparam i The integer sequence to i
* @param x tuple of values
* @return the returned tuple difference
*/
template <typename... T, int... i>
MFEM_HOST_DEVICE constexpr auto unary_minus_helper(const tuple<T...>& x,
std::integer_sequence<int, i...>)
{
return tuple{-get<i>(x)...};
}
/**
* @tparam T the types stored in the tuple y
* @param x a tuple of values
* @brief return a tuple of values defined by applying the unary minus operator to each element of x
*/
template <typename... T>
MFEM_HOST_DEVICE constexpr auto operator-(const tuple<T...>& x)
{
return unary_minus_helper(x,
std::make_integer_sequence<int, static_cast<int>(sizeof...(T))>());
}
/**
* @brief A helper function for the / operator of tuples
*
* @tparam S the types stored in the tuple x
* @tparam T the types stored in the tuple y
* @tparam i The integer sequence to i
* @param x tuple of values
* @param y tuple of values
* @return the returned tuple ratio
*/
template <typename... S, typename... T, int... i>
MFEM_HOST_DEVICE constexpr auto div_helper(const tuple<S...>& x,
const tuple<T...>& y,
std::integer_sequence<int, i...>)
{
return tuple{get<i>(x) / get<i>(y)...};
}
/**
* @tparam S the types stored in the tuple x
* @tparam T the types stored in the tuple y
* @param x a tuple of values
* @param y a tuple of values
* @brief return a tuple of values defined by elementwise division of x by y
*/
template <typename... S, typename... T>
MFEM_HOST_DEVICE constexpr auto operator/(const tuple<S...>& x,
const tuple<T...>& y)
{
static_assert(sizeof...(S) == sizeof...(T));
return div_helper(x, y,
std::make_integer_sequence<int, static_cast<int>(sizeof...(S))>());
}
/**
* @brief A helper function for the / operator of tuples
*
* @tparam T the types stored in the tuple y
* @tparam i The integer sequence to i
* @param x tuple of values
* @param a the constant numerator
* @return the returned tuple ratio
*/
template <typename... T, int... i>
MFEM_HOST_DEVICE constexpr auto div_helper(const double a,
const tuple<T...>& x, std::integer_sequence<int, i...>)
{
return tuple{a / get<i>(x)...};
}
/**
* @brief A helper function for the / operator of tuples
*
* @tparam T the types stored in the tuple y
* @tparam i The integer sequence to i
* @param x tuple of values
* @param a the constant denomenator
* @return the returned tuple ratio
*/
template <typename... T, int... i>
MFEM_HOST_DEVICE constexpr auto div_helper(const tuple<T...>& x,
const double a, std::integer_sequence<int, i...>)
{
return tuple{get<i>(x) / a...};
}
/**
* @tparam T the types stored in the tuple x
* @param a the numerator
* @param x a tuple of denominator values
* @brief return a tuple of values defined by division of a by the elements of x
*/
template <typename... T>
MFEM_HOST_DEVICE constexpr auto operator/(const double a, const tuple<T...>& x)
{
return div_helper(a, x,
std::make_integer_sequence<int, static_cast<int>(sizeof...(T))>());
}
/**
* @tparam T the types stored in the tuple y
* @param x a tuple of numerator values
* @param a a denominator
* @brief return a tuple of values defined by elementwise division of x by a
*/
template <typename... T>
MFEM_HOST_DEVICE constexpr auto operator/(const tuple<T...>& x, const double a)
{
return div_helper(x, a,
std::make_integer_sequence<int, static_cast<int>(sizeof...(T))>());
}
/**
* @brief A helper function for the * operator of tuples
*
* @tparam S the types stored in the tuple x
* @tparam T the types stored in the tuple y
* @tparam i The integer sequence to i
* @param x tuple of values
* @param y tuple of values
* @return the returned tuple product
*/
template <typename... S, typename... T, int... i>
MFEM_HOST_DEVICE constexpr auto mult_helper(const tuple<S...>& x,
const tuple<T...>& y,
std::integer_sequence<int, i...>)
{
return tuple{get<i>(x) * get<i>(y)...};
}
/**
* @tparam S the types stored in the tuple x
* @tparam T the types stored in the tuple y
* @param x a tuple of values
* @param y a tuple of values
* @brief return a tuple of values defined by elementwise multiplication of x and y
*/
template <typename... S, typename... T>
MFEM_HOST_DEVICE constexpr auto operator*(const tuple<S...>& x,
const tuple<T...>& y)
{
static_assert(sizeof...(S) == sizeof...(T));
return mult_helper(x, y,
std::make_integer_sequence<int, static_cast<int>(sizeof...(S))>());
}
/**
* @brief A helper function for the * operator of tuples
*
* @tparam T the types stored in the tuple y
* @tparam i The integer sequence to i
* @param x tuple of values
* @param a a constant multiplier
* @return the returned tuple product
*/
template <typename... T, int... i>
MFEM_HOST_DEVICE constexpr auto mult_helper(const double a,
const tuple<T...>& x, std::integer_sequence<int, i...>)
{
return tuple{a * get<i>(x)...};
}
/**
* @brief A helper function for the * operator of tuples
*
* @tparam T the types stored in the tuple y
* @tparam i The integer sequence to i
* @param x tuple of values
* @param a a constant multiplier
* @return the returned tuple product
*/
template <typename... T, int... i>
MFEM_HOST_DEVICE constexpr auto mult_helper(const tuple<T...>& x,
const double a, std::integer_sequence<int, i...>)
{
return tuple{get<i>(x) * a...};
}
/**
* @tparam T the types stored in the tuple
* @param a a scaling factor
* @param x the tuple object
* @brief multiply each component of x by the value a on the left
*/
template <typename... T>
MFEM_HOST_DEVICE constexpr auto operator*(const double a, const tuple<T...>& x)
{
return mult_helper(a, x,
std::make_integer_sequence<int, static_cast<int>(sizeof...(T))>());
}
/**
* @tparam T the types stored in the tuple
* @param x the tuple object
* @param a a scaling factor
* @brief multiply each component of x by the value a on the right
*/
template <typename... T>
MFEM_HOST_DEVICE constexpr auto operator*(const tuple<T...>& x, const double a)
{
return mult_helper(x, a,
std::make_integer_sequence<int, static_cast<int>(sizeof...(T))>());
}
/**
* @tparam T the types stored in the tuple
* @tparam i a list of indices used to acces each element of the tuple
* @param out the ostream to write the output to
* @param A the tuple of values
* @brief helper used to implement printing a tuple of values
*/
template <typename... T, std::size_t... i>
auto& print_helper(std::ostream& out, const mfem::tuple<T...>& A,
std::integer_sequence<size_t, i...>)
{
out << "tuple{";
(..., (out << (i == 0 ? "" : ", ") << mfem::get<i>(A)));
out << "}";
return out;
}
/**
* @tparam T the types stored in the tuple
* @param out the ostream to write the output to
* @param A the tuple of values
* @brief print a tuple of values
*/
template <typename... T>
auto& operator<<(std::ostream& out, const mfem::tuple<T...>& A)
{
return print_helper(out, A, std::make_integer_sequence<size_t, sizeof...(T)>());
}
/**
* @brief A helper to apply a lambda to a tuple
*
* @tparam lambda The functor type
* @tparam T The tuple types
* @tparam i The integer sequence to i
* @param f The functor to apply to the tuple
* @param args The input tuple
* @return The functor output
*/
template <typename lambda, typename... T, int... i>
MFEM_HOST_DEVICE auto apply_helper(lambda f, tuple<T...>& args,
std::integer_sequence<int, i...>)
{
return f(get<i>(args)...);
}
/**
* @tparam lambda a callable type
* @tparam T the types of arguments to be passed in to f
* @param f the callable object
* @param args a tuple of arguments
* @brief a way of passing an n-tuple to a function that expects n separate arguments
*
* e.g. foo(bar, baz) is equivalent to apply(foo, mfem::tuple(bar,baz));
*/
template <typename lambda, typename... T>
MFEM_HOST_DEVICE auto apply(lambda f, tuple<T...>& args)
{
return apply_helper(f, std::move(args),
std::make_integer_sequence<int, static_cast<int>(sizeof...(T))>());
}
/**
* @overload
*/
template <typename lambda, typename... T, int... i>
MFEM_HOST_DEVICE auto apply_helper(lambda f, const tuple<T...>& args,
std::integer_sequence<int, i...>)
{
return f(get<i>(args)...);
}
/**
* @tparam lambda a callable type
* @tparam T the types of arguments to be passed in to f
* @param f the callable object
* @param args a tuple of arguments
* @brief a way of passing an n-tuple to a function that expects n separate arguments
*
* e.g. foo(bar, baz) is equivalent to apply(foo, mfem::tuple(bar,baz));
*/
template <typename lambda, typename... T>
MFEM_HOST_DEVICE auto apply(lambda f, const tuple<T...>& args)
{
return apply_helper(f, std::move(args),
std::make_integer_sequence<int, static_cast<int>(sizeof...(T))>());
}
/**
* @brief a struct used to determine the type at index I of a tuple
*
* @note see: https://en.cppreference.com/w/cpp/utility/tuple/tuple_element
*
* @tparam I the index of the desired type
* @tparam T a tuple of different types
*/
template <size_t I, class T>
struct tuple_element;
// recursive case
/// @overload
template <size_t I, class Head, class... Tail>
struct tuple_element<I, tuple<Head, Tail...>> : tuple_element<I - 1,
tuple<Tail...>>
{
};
// base case
/// @overload
template <class Head, class... Tail>
struct tuple_element<0, tuple<Head, Tail...>>
{
using type = Head; ///< the type at the specified index
};
/**
* @brief Trait for checking if a type is a @p mfem::tuple
*/
template <typename T>
struct is_tuple : std::false_type
{
};
/// @overload
template <typename... T>
struct is_tuple<mfem::tuple<T...>> : std::true_type
{
};
/**
* @brief Trait for checking if a type if a @p mfem::tuple containing only @p mfem::tuple
*/
template <typename T>
struct is_tuple_of_tuples : std::false_type
{
};
/**
* @brief Trait for checking if a type if a @p mfem::tuple containing only @p mfem::tuple
*/
template <typename... T>
struct is_tuple_of_tuples<mfem::tuple<T...>>
{
static constexpr bool value = (is_tuple<T>::value &&
...); ///< true/false result of type check
};
} // namespace mfem
+2142
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+7
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@@ -23,6 +23,10 @@
#include <limits>
#include <list>
#undef NVTX_COLOR
#define NVTX_COLOR nvtx::kLavender
#include "general/nvtx.hpp"
namespace mfem
{
@@ -1215,6 +1219,7 @@ const Operator *ParFiniteElementSpace::GetProlongationMatrix() const
if (nd_strias) { return Dof_TrueDof_Matrix(); }
dbg();
if (NRanks == 1)
{
Pconf = new IdentityOperator(GetTrueVSize());
@@ -1234,6 +1239,7 @@ const Operator *ParFiniteElementSpace::GetProlongationMatrix() const
}
else
{
assert(false);
return Dof_TrueDof_Matrix();
}
}
@@ -3646,6 +3652,7 @@ ConformingProlongationOperator::ConformingProlongationOperator(
void ConformingProlongationOperator::Mult(const Vector &x, Vector &y) const
{
dbg();
MFEM_ASSERT(x.Size() == Width(), "");
MFEM_ASSERT(y.Size() == Height(), "");
+17
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@@ -9,6 +9,7 @@
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "../config/config.hpp"
#ifndef MFEM_ENZYME_HPP
#define MFEM_ENZYME_HPP
@@ -25,11 +26,27 @@ extern int enzyme_dup;
extern int enzyme_dupnoneed;
extern int enzyme_out;
extern int enzyme_const;
extern int enzyme_interleave;
#if defined(MFEM_USE_CUDA) || defined(MFEM_USE_HIP)
#define MFEM_DEVICE_EXTERN_STMT(name) extern __device__ int name;
#else
#define MFEM_DEVICE_EXTERN_STMT(name)
#endif
MFEM_DEVICE_EXTERN_STMT(enzyme_dup)
MFEM_DEVICE_EXTERN_STMT(enzyme_dupnoneed)
MFEM_DEVICE_EXTERN_STMT(enzyme_out)
MFEM_DEVICE_EXTERN_STMT(enzyme_const)
MFEM_DEVICE_EXTERN_STMT(enzyme_interleave)
template <typename return_type, typename... Args>
MFEM_HOST_DEVICE inline
return_type __enzyme_autodiff(Args...);
// warning: if inlined, triggers function '__enzyme_fwddiff' is not defined
template <typename return_type, typename... Args>
MFEM_HOST_DEVICE
return_type __enzyme_fwddiff(Args...);
#define MFEM_ENZYME_INACTIVENOFREE __attribute__((enzyme_inactive, enzyme_nofree))
+471
View File
@@ -0,0 +1,471 @@
#pragma once
#include <fmt/format.h>
#include <array>
#include <cassert>
#include <cstddef>
#include <cstdint>
#include <iomanip>
#include <iostream>
#include <memory>
#include <mutex>
#include <stack>
#include <string>
#include "../config/config.hpp"
#ifdef MFEM_USE_MPI
#include <mpi.h>
#endif
#ifdef MFEM_USE_CALIPER
#include <caliper/cali.h>
#endif
#ifdef MFEM_USE_CUDA
#include <cudaProfiler.h>
#include <cuda_runtime_api.h>
#include <nvToolsExt.h>
#else
struct nvtxEventAttributes_t
{
int version;
int size;
int category;
int colorType;
uint32_t color;
int payloadType;
uint64_t payload;
int messageType;
struct
{
std::string ascii;
} message;
};
#define NVTX_VERSION 1
#define NVTX_EVENT_ATTRIB_STRUCT_SIZE 256
#define NVTX_COLOR_ARGB 0
#define NVTX_MESSAGE_TYPE_ASCII 0
#define nvtxRangePushEx(...)
#define nvtxRangePop(...)
#define cudaStreamSynchronize(...)
#endif
namespace nvtx
{
///////////////////////////////////////////////////////////////////////////////
// https://en.wikipedia.org/wiki/Web_colors#Extended_colors
// clang-format off
enum color_names
{
kBlack = 0, kNavyBlue, kDarkBlue, kMediumBlue, kBlue, kDarkGreen, kWebGreen, kTeal,
kDarkCyan, kDeepSkyBlue, kDarkTurquoise, kMediumSpringGreen, kGreen, kLime,
kSpringGreen, kAqua, kCyan, kMidnightBlue, kDodgerBlue, kLightSeaGreen, kForestGreen,
kSeaGreen, kDarkSlateGray, kLimeGreen, kMediumSeaGreen, kTurquoise, kRoyalBlue,
kSteelBlue, kDarkSlateBlue, kMediumTurquoise, kIndigo, kDarkOliveGreen, kCadetBlue,
kCornflower, kRebeccaPurple, kMediumAquamarine, kDimGray, kSlateBlue, kOliveDrab,
kSlateGray, kLightSlateGray, kMediumSlateBlue, kLawnGreen, kWebMaroon, kWebPurple,
kChartreuse, kAquamarine, kOlive, kWebGray, kSkyBlue, kLightSkyBlue, kBlueViolet,
kDarkRed, kDarkMagenta, kSaddleBrown, kDarkSeaGreen, kLightGreen, kMediumPurple,
kDarkViolet, kPaleGreen, kDarkOrchid, kYellowGreen, kPurple, kSienna, kBrown,
kDarkGray, kLightBlue, kGreenYellow, kPaleTurquoise, kMaroon, kLightSteelBlue,
kPowderBlue, kFirebrick, kDarkGoldenrod, kMediumOrchid, kRosyBrown, kDarkKhaki,
kGray, kSilver, kMediumVioletRed, kIndianRed, kPeru, kChocolate, kTan, kLightGray,
kThistle, kOrchid, kGoldenrod, kPaleVioletRed, kCrimson, kGainsboro, kPlum, kBurlywood,
kLightCyan, kLavender, kDarkSalmon, kViolet, kPaleGoldenrod, kLightCoral, kKhaki,
kAliceBlue, kHoneydew, kAzure, kSandyBrown, kWheat, kBeige, kWhiteSmoke, kMintCream,
kGhostWhite, kSalmon, kAntiqueWhite, kLinen, kLightGoldenrod, kOldLace, kRed,
kFuchsia, kMagenta, kDeepPink, kOrangeRed, kTomato, kHotPink, kCoral, kDarkOrange,
kLightSalmon, kOrange, kLightPink, kPink, kGold, kPeachPuff, kNavajoWhite, kMoccasin,
kBisque, kMistyRose, kBlanchedAlmond, kPapayaWhip, kLavenderBlush, kSeashell,
kCornsilk, kLemonChiffon, kFloralWhite, kSnow, kYellow, kLightYellow, kIvory, kWhite,
kNvidia
};
// clang-format on
static constexpr int kNumHexColors = 146;
static constexpr std::array<uint32_t, kNumHexColors> kHexColors =
{
{
0x000000, 0x000080, 0x00008B, 0x0000CD, 0x0000FF, 0x006400, 0x008000,
0x008080, 0x008B8B, 0x00BFFF, 0x00CED1, 0x00FA9A, 0x00FF00, 0x00FF00,
0x00FF7F, 0x00FFFF, 0x00FFFF, 0x191970, 0x1E90FF, 0x20B2AA, 0x228B22,
0x2E8B57, 0x2F4F4F, 0x32CD32, 0x3CB371, 0x40E0D0, 0x4169E1, 0x4682B4,
0x483D8B, 0x48D1CC, 0x4B0082, 0x556B2F, 0x5F9EA0, 0x6495ED, 0x663399,
0x66CDAA, 0x696969, 0x6A5ACD, 0x6B8E23, 0x708090, 0x778899, 0x7B68EE,
0x7CFC00, 0x7F0000, 0x7F007F, 0x7FFF00, 0x7FFFD4, 0x808000, 0x808080,
0x87CEEB, 0x87CEFA, 0x8A2BE2, 0x8B0000, 0x8B008B, 0x8B4513, 0x8FBC8F,
0x90EE90, 0x9370DB, 0x9400D3, 0x98FB98, 0x9932CC, 0x9ACD32, 0xA020F0,
0xA0522D, 0xA52A2A, 0xA9A9A9, 0xADD8E6, 0xADFF2F, 0xAFEEEE, 0xB03060,
0xB0C4DE, 0xB0E0E6, 0xB22222, 0xB8860B, 0xBA55D3, 0xBC8F8F, 0xBDB76B,
0xBEBEBE, 0xC0C0C0, 0xC71585, 0xCD5C5C, 0xCD853F, 0xD2691E, 0xD2B48C,
0xD3D3D3, 0xD8BFD8, 0xDA70D6, 0xDAA520, 0xDB7093, 0xDC143C, 0xDCDCDC,
0xDDA0DD, 0xDEB887, 0xE0FFFF, 0xE6E6FA, 0xE9967A, 0xEE82EE, 0xEEE8AA,
0xF08080, 0xF0E68C, 0xF0F8FF, 0xF0FFF0, 0xF0FFFF, 0xF4A460, 0xF5DEB3,
0xF5F5DC, 0xF5F5F5, 0xF5FFFA, 0xF8F8FF, 0xFA8072, 0xFAEBD7, 0xFAF0E6,
0xFAFAD2, 0xFDF5E6, 0xFF0000, 0xFF00FF, 0xFF00FF, 0xFF1493, 0xFF4500,
0xFF6347, 0xFF69B4, 0xFF7F50, 0xFF8C00, 0xFFA07A, 0xFFA500, 0xFFB6C1,
0xFFC0CB, 0xFFD700, 0xFFDAB9, 0xFFDEAD, 0xFFE4B5, 0xFFE4C4, 0xFFE4E1,
0xFFEBCD, 0xFFEFD5, 0xFFF0F5, 0xFFF5EE, 0xFFF8DC, 0xFFFACD, 0xFFFAF0,
0xFFFAFA, 0xFFFF00, 0xFFFFE0, 0xFFFFF0, 0xFFFFFF, 0x76B900
}
};
///////////////////////////////////////////////////////////////////////////////
inline size_t static_strlen(const char *str)
{
return *str == '\0' ? 0 : static_strlen(str + 1) + 1;
}
inline uint8_t static_checksum8(const char *bfr)
{
unsigned int chk = 0;
size_t len = static_strlen(bfr);
for (; len; len--, bfr++) { chk += static_cast<unsigned int>(*bfr); }
return static_cast<uint8_t>(chk);
}
inline char *static_strrnchr(const char *str, const char c, int n)
{
size_t len = static_strlen(str);
char *p = const_cast<char *>(str) + len - 1;
for (; n; n--, p--, len--)
{
for (; len; p--, len--)
{
if (*p == c) { break; }
}
if (!len) { return nullptr; }
if (n == 1) { return p; }
}
return nullptr;
}
inline uint32_t static_color(const uint8_t COLOR, const int RANK,
const char *FILE)
{
constexpr auto kMpiColorShift = 1;
const auto rank_shift = kMpiColorShift * RANK;
if (COLOR > 0) { return kHexColors[COLOR + rank_shift]; }
const auto file_color = static_checksum8(FILE);
return kHexColors[(file_color + rank_shift) % kNumHexColors];
}
///////////////////////////////////////////////////////////////////////////////
// Helpers to generate unique variable names
#define NVTX_FLF __FILE__, __LINE__, __FUNCTION__
#define NVTX_PRIVATE_NAME(prefix) NVTX_PRIVATE_CONCAT(prefix, __LINE__)
#define NVTX_PRIVATE_CONCAT(a, b) NVTX_PRIVATE_CONCAT2(a, b)
#define NVTX_PRIVATE_CONCAT2(a, b) a##b
#ifndef NVTX_COLOR
#define NVTX_COLOR ::nvtx::kBlack
#endif
///////////////////////////////////////////////////////////////////////////////
struct Debug
{
const bool debug = false, end = true;
inline Debug() = default;
inline Debug(const int RANK, const char *FILE, const int LINE,
const char *FUNC, uint8_t COLOR, bool ini = true,
bool END = true): debug(true), end(END)
{
const char *base = static_strrnchr(FILE, '/', 2);
const char *file = base ? base + 1 : FILE;
const uint32_t rgb = static_color(COLOR, RANK, FILE);
const uint8_t r = (rgb >> 16) & 0xFF, g = (rgb >> 8) & 0xFF,
b = rgb & 0xFF;
std::cout << "\033[38;2;";
std::cout << std::to_string(r) << ";";
std::cout << std::to_string(g) << ";";
std::cout << std::to_string(b) << "m";
if (ini)
{
std::cout << RANK << std::setw(64) << file << ":";
std::cout << "\033[2m" << std::setw(4) << std::left << LINE
<< "\033[22m: ";
if (FUNC) { std::cout << "[" << FUNC << "] "; }
}
std::cout << std::right << "\033[1m";
}
inline ~Debug()
{
if (debug) { std::cout << "\033[m" << (end ? "\n" : "") << std::flush; }
}
template <typename T>
inline void operator<<(const T &arg) const noexcept
{
if (debug) { std::cout << arg; }
}
template <typename T>
inline void operator()(const T &arg) const noexcept
{
if (debug) { this->operator<<(arg); }
}
template <typename... Args>
inline void operator()(const char *fmt, Args &&...args) const noexcept
{
// if (debug) { std::cout << fmt::format(fmt, std::forward<Args>(args)...); }
if (debug) { std::cout << fmt::format(fmt::runtime(fmt), std::forward<Args>(args)...); }
}
inline void operator()() const noexcept {}
static Debug Set(const char *FILE, const int LINE, const char *FUNC,
uint8_t COLOR, bool INI = true, bool END = true)
{
static int mpi_rank = 0, dbg_mpi_rank = 0;
static bool env_mpi = false, env_dbg = false;
static bool ini = false;
if (!ini)
{
env_dbg = (::getenv("MFEM_DEBUG") != nullptr);
env_mpi = ::getenv("MFEM_DEBUG_MPI") != nullptr;
int mpi_flag = 0;
MPI_Initialized(&mpi_flag);
if (mpi_flag) { MPI_Comm_rank(MPI_COMM_WORLD, &mpi_rank); }
dbg_mpi_rank = atoi(env_mpi ? ::getenv("MFEM_DEBUG_MPI") : "0");
ini = true;
}
const bool debug = (env_dbg && (!env_mpi || (dbg_mpi_rank == mpi_rank)));
return debug ? Debug(mpi_rank, FILE, LINE, FUNC, COLOR, INI, END)
: Debug();
}
};
// Debug console traces, unnamed
#define NVTX_DEBUG(...) \
::nvtx::Debug::Set(NVTX_FLF, NVTX_COLOR).operator()(__VA_ARGS__)
#define NVTX_DEBUG_NO_INI(...) \
::nvtx::Debug::Set(NVTX_FLF, NVTX_COLOR, false, true) \
.operator()(__VA_ARGS__)
#define NVTX_DEBUG_APPEND(...) \
::nvtx::Debug::Set(NVTX_FLF, NVTX_COLOR, false, false) \
.operator()(__VA_ARGS__)
#define NVTX_DEBUG_NO_END(...) \
::nvtx::Debug::Set(NVTX_FLF, NVTX_COLOR, true, false) \
.operator()(__VA_ARGS__)
///////////////////////////////////////////////////////////////////////////////
struct Nvtx
{
const bool nvtx = false, enforce_kernel_sync = false;
const char *base, *file;
const uint32_t color = kBlack;
mutable std::string ascii;
mutable nvtxEventAttributes_t event;
mutable bool pushed = false;
inline Nvtx() = default;
Nvtx(bool enforce_kernel_sync, const char *FILE, const int LINE,
const char *FUNC, uint8_t COLOR):
nvtx(true), enforce_kernel_sync(enforce_kernel_sync),
base(static_strrnchr(FILE, '/', 2)), file(base ? base + 1 : FILE),
color(COLOR), ascii(file), event({})
{
event.version = NVTX_VERSION;
event.size = NVTX_EVENT_ATTRIB_STRUCT_SIZE;
event.colorType = NVTX_COLOR_ARGB;
event.color = static_color(COLOR, 0, FILE);
event.messageType = NVTX_MESSAGE_TYPE_ASCII;
ascii += ":";
ascii += std::to_string(LINE);
ascii += ":[";
ascii += FUNC;
ascii += "] ";
pushed = false;
}
explicit Nvtx(const char *title, uint8_t color = kWheat,
bool enforce_kernel_sync = true):
nvtx(true), enforce_kernel_sync(enforce_kernel_sync), color(color),
ascii(title), event({})
{
event.version = NVTX_VERSION;
event.size = NVTX_EVENT_ATTRIB_STRUCT_SIZE;
event.colorType = NVTX_COLOR_ARGB;
event.color = static_color(color, 0, "");
event.messageType = NVTX_MESSAGE_TYPE_ASCII;
event.message.ascii = ascii.c_str();
nvtxRangePushEx(&event);
pushed = true;
}
inline void operator()() const
{
if (!nvtx) { return; }
event.message.ascii = ascii.c_str();
assert(!pushed);
nvtxRangePushEx(&event);
pushed = true;
}
template <typename T>
inline void operator()(const T &arg) const
{
if (!nvtx) { return; }
this->operator<<(arg);
event.message.ascii = ascii.c_str();
assert(!pushed);
nvtxRangePushEx(&event);
pushed = true;
}
template <typename... Args>
inline void operator()(fmt::format_string<Args...> fmt,
Args &&...args) const
{
if (!nvtx) { return; }
ascii += fmt::format(fmt, std::forward<Args>(args)...);
event.message.ascii = ascii.c_str();
assert(!pushed);
nvtxRangePushEx(&event);
pushed = true;
}
template <typename T>
inline void operator<<(const T &arg) const
{
if (nvtx) { ascii += arg; }
}
inline ~Nvtx()
{
if (!nvtx) { return; }
if (enforce_kernel_sync)
{
nvtxEventAttributes_t eks = {};
eks.version = NVTX_VERSION;
eks.size = NVTX_EVENT_ATTRIB_STRUCT_SIZE;
eks.category = 0; // user value
eks.colorType = NVTX_COLOR_ARGB;
eks.messageType = NVTX_MESSAGE_TYPE_ASCII;
eks.message.ascii = "!"; // enforce kernel synchronization
eks.color = kHexColors[kYellow];
nvtxRangePushEx(&eks);
cudaStreamSynchronize(nullptr);
nvtxRangePop(/*eks*/);
}
assert(pushed);
nvtxRangePop(/*event*/);
}
using nvtx_ptr = std::unique_ptr<Nvtx>;
using nvtx_stack_t = std::stack<nvtx_ptr>;
static nvtx_ptr Set(const char *FILE, const int LINE, const char *FUNC,
uint8_t COLOR)
{
static bool nvtx = false, eks = false;
static bool ini = false;
if (!ini)
{
eks = ::getenv("MFEM_EKS") != nullptr;
nvtx = ::getenv("MFEM_NVTX") != nullptr;
Nvtx force_first_eks("Init EKS", kYellow, true);
ini = true;
}
return nvtx_ptr(nvtx ? new Nvtx(eks, FILE, LINE, FUNC, COLOR)
: new Nvtx());
}
static nvtx_stack_t &Stack()
{
auto nvtx_events = []() -> nvtx_stack_t &
{
static nvtx_stack_t events;
return events;
};
static std::once_flag ready;
// one touch to guarantee the object is ready
std::call_once(ready, [&] { nvtx_events(); });
return nvtx_events();
}
};
// Temporary object only alive for the current statement
#define NVTX_(COLOR, ...) \
NVTX_DEBUG(__VA_ARGS__); \
std::unique_ptr<::nvtx::Nvtx> NVTX_PRIVATE_NAME(nvtx) = \
::nvtx::Nvtx::Set(NVTX_FLF, COLOR); \
NVTX_PRIVATE_NAME(nvtx)->operator()(__VA_ARGS__)
// Temporary object only alive for the current statement
#define NVTX(...) NVTX_(NVTX_COLOR, __VA_ARGS__)
// Begin(with color)/End NVTX event traces
#define NVTX_BEGIN_(COLOR, ...) \
NVTX_DEBUG(__VA_ARGS__); \
::nvtx::Nvtx::Stack().push(::nvtx::Nvtx::Set(NVTX_FLF, COLOR)); \
::nvtx::Nvtx::Stack().top()->operator()(__VA_ARGS__)
// Begin/End NVTX event traces
#define NVTX_BEGIN(...) NVTX_BEGIN_(NVTX_COLOR, __VA_ARGS__);
#define NVTX_END(...) \
::nvtx::Nvtx::Stack().top().reset(); \
::nvtx::Nvtx::Stack().pop()
#ifdef USE_CALIPER
// CALIPER & NVTX marks
#define NVTX_MARK_FUNCTION \
NVTX(); \
std::unique_ptr<cali::Function> __cali_ann##__func__; \
__cali_ann##__func__ = std::make_unique<cali::Function>(__func__);
#define NVTX_MARK(...) \
NVTX(__VA_ARGS__); \
std::unique_ptr<cali::Function> __cali_ann##__func__; \
__cali_ann##__func__ = std::make_unique<cali::Function>(__VA_ARGS__);
#define NVTX_MARK_FUNCTION_NAME(STR_NAME) \
NVTX(STR_NAME); \
std::unique_ptr<cali::Function> __cali_ann##__func__; \
if (g_caliper) { \
__cali_ann##__func__ = std::make_unique<cali::Function>(STR_NAME); \
}
#define NVTX_MARK_BEGIN(...) \
CALI_MARK_BEGIN(__VA_ARGS__); \
NVTX_BEGIN(__VA_ARGS__);
#define NVTX_MARK_END(...) \
NVTX_END(__VA_ARGS__); \
CALI_MARK_END(__VA_ARGS__);
#else
#define NVTX_MARK_FUNCTION NVTX()
#define NVTX_MARK(...) NVTX(__VA_ARGS__)
#define NVTX_MARK_FUNCTION_NAME(...) NVTX(__VA_ARGS__)
#define NVTX_MARK_BEGIN(...) NVTX_BEGIN(__VA_ARGS__)
#define NVTX_MARK_END(...) NVTX_END(__VA_ARGS__)
#endif
} // namespace nvtx
// Debug console traces, unnamed
#if 1
#define dbg(...) NVTX_DEBUG(__VA_ARGS__)
#define dbl(...) NVTX_DEBUG_NO_END(__VA_ARGS__)
#define dba(...) NVTX_DEBUG_APPEND(__VA_ARGS__)
#define dbc(...) NVTX_DEBUG_NO_INI(__VA_ARGS__)
#else
#define dbg(...)
#define dbl(...) (void)0
#define dba(...)
#define dbc(...)
#endif
+14 -1
View File
@@ -87,7 +87,9 @@ protected:
public:
/// Default constructor
DeviceTensor() = delete;
// DeviceTensor() = delete;
MFEM_HOST_DEVICE
DeviceTensor() {}
/// Constructor to initialize a tensor from the Scalar array data_
template <typename... Args> MFEM_HOST_DEVICE
@@ -122,6 +124,17 @@ public:
{
return data[i];
}
/// Returns the shape of the tensor.
MFEM_HOST_DEVICE inline std::array<int, Dim> GetShape() const
{
std::array<int, Dim> s;
for (int i = 0; i < Dim; i++)
{
s[i] = sizes[i];
}
return s;
}
};
+210 -12
View File
@@ -1,4 +1,4 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// Copyright (c) 2010-2024, 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.
//
@@ -19,6 +19,8 @@
#define MFEM_INTERNAL_TENSOR_HPP
#include "dual.hpp"
#include "general/backends.hpp"
#include <limits>
#include <type_traits> // for std::false_type
namespace mfem
@@ -436,6 +438,23 @@ tensor<decltype(f(n1, n2, n3, n4)), n1, n2, n3, n4>
return A;
}
// needs to be generalized
template <typename T, int m, int n> MFEM_HOST_DEVICE
tensor<T, n> get_col(tensor<T, m, n> A, int j)
{
tensor<T, n> c{};
c(0) = A[0][j];
c(1) = A[1][j];
return c;
}
/// @overload
template <typename T> MFEM_HOST_DEVICE
tensor<T, 1> get_col(tensor<T, 1, 1> A, int j)
{
return tensor<T, 1> {A[0][0]};
}
/**
* @brief return the sum of two tensors
* @tparam S the underlying type of the lefthand argument
@@ -697,6 +716,20 @@ auto outer(S A, T B) -> decltype(A * B)
return A * B;
}
template <typename T, int n, int m> MFEM_HOST_DEVICE
tensor<T, n + m> flatten(tensor<T, n, m> A)
{
tensor<T, n + m> B{};
for (int i = 0; i < n; i++)
{
for (int j = 0; j < m; j++)
{
B(i + j * m) = A(i, j);
}
}
return B;
}
/**
* @overload
* @note this overload implements the case where the left argument is a scalar, and the right argument is a tensor
@@ -1051,6 +1084,18 @@ decltype(S {} * T{})
return AB;
}
template <typename T, int m> MFEM_HOST_DEVICE
auto dot(const tensor<T, m>& A, const tensor<T, m>& B) ->
decltype(T {})
{
decltype(T{}) AB{};
for (int i = 0; i < m; i++)
{
AB += A[i] * B[i];
}
return AB;
}
template <typename S, typename T, int m, int... n> MFEM_HOST_DEVICE
auto dot(const tensor<S, m>& A, const tensor<T, m, n...>& B) ->
tensor<decltype(S {} * T{}), n...>
@@ -1321,6 +1366,12 @@ tensor<T, n, m> transpose(const tensor<T, m, n>& A)
* @param[in] A The matrix to obtain the determinant of
*/
template <typename T> MFEM_HOST_DEVICE
T det(const tensor<T, 1, 1>& A)
{
return A[0][0];
}
/// @overload
template <typename T> MFEM_HOST_DEVICE
T det(const tensor<T, 2, 2>& A)
{
return A[0][0] * A[1][1] - A[0][1] * A[1][0];
@@ -1335,6 +1386,145 @@ T det(const tensor<T, 3, 3>& A)
A[2][0];
}
template <typename T> MFEM_HOST_DEVICE
std::tuple<tensor<T, 1>, tensor<T, 1, 1>> eig(tensor<T, 1, 1> &A)
{
return {tensor<T, 1>{A[0][0]}, tensor<T, 1, 1>{{{1.0}}}};
}
template <typename T> MFEM_HOST_DEVICE
std::tuple<tensor<T, 2>, tensor<T, 2, 2>> eig(tensor<T, 2, 2> &A)
{
tensor<T, 2> e;
tensor<T, 2, 2> v;
double d0 = A(0, 0);
double d2 = A(0, 1);
double d3 = A(1, 1);
double c, s;
if (d2 == 0.0)
{
c = 1.0;
s = 0.0;
}
else
{
double t;
const double zeta = (d3 - d0) / (2.0 * d2);
const double azeta = fabs(zeta);
if (azeta < std::sqrt(1.0/std::numeric_limits<T>::epsilon()))
{
t = copysign(1./(azeta + std::sqrt(1. + zeta*zeta)), zeta);
}
else
{
t = copysign(0.5/azeta, zeta);
}
c = std::sqrt(1./(1. + t*t));
s = c*t;
t *= d2;
d0 -= t;
d3 += t;
}
if (d0 <= d3)
{
e(0) = d0;
e(1) = d3;
v(0, 0) = c;
v(1, 0) = -s;
v(0, 1) = s;
v(1, 1) = c;
}
else
{
e(0) = d3;
e(1) = d0;
v(0, 0) = s;
v(1, 0) = c;
v(0, 1) = c;
v(1, 1) = -s;
}
return {e, v};
}
template <typename T> MFEM_HOST_DEVICE
void GetScalingFactor(const T &d_max, T &mult)
{
int d_exp;
if (d_max > 0.)
{
mult = frexp(d_max, &d_exp);
if (d_exp == std::numeric_limits<T>::max_exponent)
{
mult *= std::numeric_limits<T>::radix;
}
mult = d_max/mult;
}
else
{
mult = 1.;
}
}
template <typename T> MFEM_HOST_DEVICE
T calcsv(const tensor<T, 1, 1> A, const int i)
{
return A[0][0];
}
/**
* @brief Compute the i-th singular value of a 2x2 matrix A
*/
template <typename T> MFEM_HOST_DEVICE
T calcsv(const tensor<T, 2, 2> A, const int i)
{
double mult;
double d0, d1, d2, d3;
d0 = A(0, 0);
d1 = A(1, 0);
d2 = A(0, 1);
d3 = A(1, 1);
double d_max = fabs(d0);
if (d_max < fabs(d1)) { d_max = fabs(d1); }
if (d_max < fabs(d2)) { d_max = fabs(d2); }
if (d_max < fabs(d3)) { d_max = fabs(d3); }
GetScalingFactor(d_max, mult);
d0 /= mult;
d1 /= mult;
d2 /= mult;
d3 /= mult;
double t = 0.5*((d0+d2)*(d0-d2)+(d1-d3)*(d1+d3));
double s = d0*d2 + d1*d3;
s = std::sqrt(0.5*(d0*d0 + d1*d1 + d2*d2 + d3*d3) + std::sqrt(t*t + s*s));
if (s == 0.0)
{
return 0.0;
}
t = fabs(d0*d3 - d1*d2) / s;
if (t > s)
{
if (i == 0)
{
return t*mult;
}
return s*mult;
}
if (i == 0)
{
return s*mult;
}
return t*mult;
}
/**
* @brief Return whether a square rank 2 tensor is symmetric
*
@@ -1474,13 +1664,20 @@ tensor<T, n> linear_solve(tensor<T, n, n> A, const tensor<T, n> b)
/**
* @brief Inverts a matrix
* @param[in] A The matrix to invert
* @note Uses a shortcut for inverting a 2-by-2 matrix
* @note Uses a shortcut for inverting a 1x1, 2x2 and 3x3 matrix
*/
inline MFEM_HOST_DEVICE tensor<real_t, 2, 2> inv(const tensor<real_t, 2, 2>& A)
template <typename T>
inline MFEM_HOST_DEVICE tensor<T, 1, 1> inv(const tensor<T, 1, 1>& A)
{
real_t inv_detA(1.0 / det(A));
return tensor<T, 1, 1> {{{T{1.0} / A[0][0]}}};
}
tensor<real_t, 2, 2> invA{};
template <typename T>
inline MFEM_HOST_DEVICE tensor<T, 2, 2> inv(const tensor<T, 2, 2>& A)
{
T inv_detA(1.0 / det(A));
tensor<T, 2, 2> invA{};
invA[0][0] = A[1][1] * inv_detA;
invA[0][1] = -A[0][1] * inv_detA;
@@ -1494,11 +1691,12 @@ inline MFEM_HOST_DEVICE tensor<real_t, 2, 2> inv(const tensor<real_t, 2, 2>& A)
* @overload
* @note Uses a shortcut for inverting a 3-by-3 matrix
*/
inline MFEM_HOST_DEVICE tensor<real_t, 3, 3> inv(const tensor<real_t, 3, 3>& A)
template <typename T>
inline MFEM_HOST_DEVICE tensor<T, 3, 3> inv(const tensor<T, 3, 3>& A)
{
real_t inv_detA(1.0 / det(A));
T inv_detA(1.0 / det(A));
tensor<real_t, 3, 3> invA{};
tensor<T, 3, 3> invA{};
invA[0][0] = (A[1][1] * A[2][2] - A[1][2] * A[2][1]) * inv_detA;
invA[0][1] = (A[0][2] * A[2][1] - A[0][1] * A[2][2]) * inv_detA;
@@ -1520,7 +1718,7 @@ inline MFEM_HOST_DEVICE tensor<real_t, 3, 3> inv(const tensor<real_t, 3, 3>& A)
template <typename T, int n> MFEM_HOST_DEVICE
tensor<T, n, n> inv(const tensor<T, n, n>& A)
{
auto abs = [](real_t x) { return (x < 0) ? -x : x; };
auto abs = [](T x) { return (x < 0) ? -x : x; };
auto swap = [](tensor<T, n>& x, tensor<T, n>& y)
{
auto tmp = x;
@@ -1528,12 +1726,12 @@ tensor<T, n, n> inv(const tensor<T, n, n>& A)
y = tmp;
};
tensor<real_t, n, n> B = Identity<n>();
tensor<T, n, n> B = Identity<n>();
for (int i = 0; i < n; i++)
{
// Search for maximum in this column
real_t max_val = abs(A[i][i]);
T max_val = abs(A[i][i]);
int max_row = i;
for (int j = i + 1; j < n; j++)
@@ -1553,7 +1751,7 @@ tensor<T, n, n> inv(const tensor<T, n, n>& A)
{
if (A[j][i] != 0.0)
{
real_t c = -A[j][i] / A[i][i];
T c = -A[j][i] / A[i][i];
A[j] += c * A[i];
B[j] += c * B[i];
A[j][i] = 0;
+1
View File
@@ -17,6 +17,7 @@ include_directories(BEFORE ${CMAKE_CURRENT_SOURCE_DIR})
# The following list can be updated using (in bash):
# for d in general linalg mesh fem enzyme; do ls -1 $d/*.cpp; done
set(UNIT_TESTS_SRCS
dfem/test_diffusion.cpp
general/test_array.cpp
general/test_arrays_by_name.cpp
general/test_error.cpp
+240
View File
@@ -0,0 +1,240 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
#include "unit_tests.hpp"
#include "mfem.hpp"
#include "fem/dfem/doperator.hpp"
#include "linalg/tensor.hpp"
using namespace mfem;
using mfem::internal::tensor;
using DOperator = DifferentiableOperator;
#undef NVTX_COLOR
#define NVTX_COLOR nvtx::kAquamarine
#include "general/nvtx.hpp"
namespace dfem_pa_kernels
{
///////////////////////////////////////////////////////////////////////////////
template <int DIM> struct Diffusion
{
using vecd_t = tensor<real_t, DIM>;
using matd_t = tensor<real_t, DIM, DIM>;
struct MFApply
{
MFEM_HOST_DEVICE inline auto operator()(const vecd_t &dudxi,
const real_t &rho,
const matd_t &J,
const real_t &w) const
{
const auto invJ = inv(J), TinJ = transpose(invJ);
return mfem::tuple{ (dudxi * invJ) * TinJ * det(J) * w * rho };
}
};
struct PASetup
{
MFEM_HOST_DEVICE inline auto operator()(const real_t &u,
const real_t &rho,
const matd_t &J,
const real_t &w) const
{
return mfem::tuple{ inv(J) * transpose(inv(J)) * det(J) * w * rho };
}
};
struct PAApply
{
MFEM_HOST_DEVICE inline auto operator()(const vecd_t &dudxi,
const matd_t &q) const
{
return mfem::tuple{ q * dudxi };
};
};
};
///////////////////////////////////////////////////////////////////////////////
template <int DIM>
void DFemDiffusion(const char *filename, int p, const int r)
{
CAPTURE(filename, DIM, p, r);
Mesh smesh(filename);
ParMesh pmesh(MPI_COMM_WORLD, smesh);
MFEM_VERIFY(pmesh.Dimension() == DIM, "Mesh dimension mismatch");
pmesh.EnsureNodes();
auto *nodes = static_cast<ParGridFunction *>(pmesh.GetNodes());
p = std::max(p, pmesh.GetNodalFESpace()->GetMaxElementOrder());
smesh.Clear();
Array<int> all_domain_attr;
if (pmesh.bdr_attributes.Size() > 0)
{
all_domain_attr.SetSize(pmesh.bdr_attributes.Max());
all_domain_attr = 1;
}
H1_FECollection fec(p, DIM);
ParFiniteElementSpace pfes(&pmesh, &fec);
ParFiniteElementSpace *mfes = nodes->ParFESpace();
const int NE = pfes.GetNE(), d1d(p + 1), q = 2 * p + r;
const auto *ir = &IntRules.Get(pmesh.GetTypicalElementGeometry(), q);
const int q1d(IntRules.Get(Geometry::SEGMENT, ir->GetOrder()).GetNPoints());
MFEM_VERIFY(d1d <= q1d, "q1d should be >= d1d");
MFEM_VERIFY(NE > 0, "Mesh with no elements is not yet supported!");
ParGridFunction x(&pfes), y(&pfes), z(&pfes);
x.Randomize(1);
x.SetTrueVector();
x.SetFromTrueVector();
auto rho = [](const Vector &xyz)
{
const real_t x = xyz(0), y = xyz(1), z = DIM == 3 ? xyz(2) : 0.0;
real_t r = M_PI * pow(x, 2);
if (DIM >= 2) { r += pow(y, 3); }
if (DIM >= 3) { r += pow(z, 4); }
return r;
};
FunctionCoefficient rho_coeff(rho);
ParBilinearForm blf_fa(&pfes);
blf_fa.AddDomainIntegrator(new DiffusionIntegrator(rho_coeff, ir));
blf_fa.Assemble();
blf_fa.Finalize();
SECTION("Partial assembly")
{
dbg("Partial assembly");
ParBilinearForm blf_pa(&pfes);
blf_pa.AddDomainIntegrator(new DiffusionIntegrator(rho_coeff, ir));
blf_pa.SetAssemblyLevel(AssemblyLevel::PARTIAL);
blf_pa.Assemble();
blf_pa.Mult(x, z);
blf_fa.Mult(x, y);
y -= z;
REQUIRE(y.Normlinf() == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
QuadratureSpace qs(pmesh, *ir);
CoefficientVector rho_coeff_cv(rho_coeff, qs);
MFEM_VERIFY(rho_coeff_cv.GetVDim() == 1, "Coefficient should be scalar");
MFEM_VERIFY(rho_coeff_cv.Size() == q1d * q1d * (DIM == 3 ? q1d : 1) * NE, "");
const int rho_local_size = 1;
const int rho_elem_size(rho_local_size * ir->GetNPoints());
const int rho_total_size(rho_elem_size * NE);
ParametricSpace rho_ps(DIM, rho_local_size, rho_elem_size, rho_total_size,
DIM == 3 ? d1d : d1d * d1d, // 🔥 2D workaround
DIM == 3 ? q1d : q1d * q1d);
static constexpr int U = 0, Coords = 1, Rho = 3;
const auto sol = std::vector{ FieldDescriptor{ U, &pfes } };
SECTION("DFEM Matrix free")
{
DOperator dop_mf(sol, {{Rho, &rho_ps}, {Coords, mfes}}, pmesh);
typename Diffusion<DIM>::MFApply mf_apply_qf;
dop_mf.AddDomainIntegrator(mf_apply_qf,
mfem::tuple{ Gradient<U>{}, None<Rho>{},
Gradient<Coords>{}, Weight{} },
mfem::tuple{ Gradient<U>{} }, *ir,
all_domain_attr);
dop_mf.SetParameters({ &rho_coeff_cv, nodes });
dop_mf.Mult(x, z);
z.SetTrueVector(), z.SetFromTrueVector();
blf_fa.Mult(x, y);
y.SetTrueVector(), y.SetFromTrueVector();
y -= z;
REQUIRE(y.Normlinf() == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
SECTION("DFEM Partial assembly")
{
static constexpr int QData = 2;
const int qd_local_size = DIM * DIM;
const int qd_elem_size(qd_local_size * ir->GetNPoints());
const int qd_total_size(qd_elem_size * NE);
ParametricSpace qd_ps(DIM, qd_local_size, qd_elem_size, qd_total_size,
DIM == 3 ? d1d : d1d * d1d, // 🔥 2D workaround
DIM == 3 ? q1d : q1d * q1d);
ParametricFunction qdata(qd_ps);
qdata.UseDevice(true);
DOperator dSetup(sol, {{Rho, &rho_ps}, {Coords, mfes}, {QData, &qd_ps}}, pmesh);
typename Diffusion<DIM>::PASetup pa_setup_qf;
dSetup.AddDomainIntegrator(
pa_setup_qf,
mfem::tuple{ None<U>{}, None<Rho>{}, Gradient<Coords>{}, Weight{} },
mfem::tuple{ None<QData>{} }, *ir, all_domain_attr);
dSetup.SetParameters({ &rho_coeff_cv, nodes, &qdata });
pfes.GetRestrictionMatrix()->Mult(x, x.GetTrueVector());
dSetup.Mult(x.GetTrueVector(), qdata);
DOperator dop_pa(sol, { { QData, &qd_ps } }, pmesh);
typename Diffusion<DIM>::PAApply pa_apply_qf;
dop_pa.AddDomainIntegrator(pa_apply_qf,
mfem::tuple{ Gradient<U>{}, None<QData>{} },
mfem::tuple{ Gradient<U>{} },
*ir, all_domain_attr);
dop_pa.SetParameters({ &qdata });
dop_pa.Mult(x, z);
z.SetTrueVector(), z.SetFromTrueVector();
blf_fa.Mult(x, y);
y.SetTrueVector(), y.SetFromTrueVector();
y -= z;
REQUIRE(y.Normlinf() == MFEM_Approx(0.0));
MPI_Barrier(MPI_COMM_WORLD);
}
}
///////////////////////////////////////////////////////////////////////////////
TEST_CASE("DFEM Diffusion", "[Parallel][DFEM]")
{
const bool all_tests = launch_all_non_regression_tests;
const auto p = !all_tests ? 1 : GENERATE(1, 2, 3);
const auto r = !all_tests ? 0 : GENERATE(0, 1, 2, 3);
SECTION("2D p=" + std::to_string(p) + " r=" + std::to_string(r))
{
const auto filename =
GENERATE("../../data/star.mesh",
"../../data/star-q3.mesh",
"../../data/rt-2d-q3.mesh",
"../../data/inline-quad.mesh",
"../../data/periodic-square.mesh");
DFemDiffusion<2>(filename, p, r);
}
SECTION("3D p=" + std::to_string(p) + " r=" + std::to_string(r))
{
const auto filename =
GENERATE("../../data/fichera.mesh",
"../../data/fichera-q3.mesh",
"../../data/inline-hex.mesh",
"../../data/toroid-hex.mesh",
"../../data/periodic-cube.mesh");
DFemDiffusion<3>(filename, p, r);
}
}
} // namespace dfem_pa_kernels
+6
View File
@@ -18,6 +18,10 @@
#error "This test should be disabled without MFEM_USE_MPI!"
#endif
#undef NVTX_COLOR
#define NVTX_COLOR nvtx::kOrange
#include "general/nvtx.hpp"
int main(int argc, char *argv[])
{
#ifdef MFEM_USE_SINGLE
@@ -32,6 +36,8 @@ int main(int argc, char *argv[])
#endif
mfem::Device device("cpu"); // make sure hypre runs on CPU, if possible
dbg();
// Only run tests that are labeled with Parallel.
return RunCatchSession(argc, argv, {"[Parallel]"}, Root());
}