Factor out CUDA part of amgclSolver

This commit is contained in:
Tong Dong Qiu 2021-07-06 17:10:17 +02:00
parent b2156a4edc
commit f77d745b51
5 changed files with 107 additions and 51 deletions

View File

@ -221,9 +221,6 @@ if(amgcl_FOUND)
# Hence we set AMGCL_INCLUDE_DIRS.
get_property(AMGCL_INCLUDE_DIRS TARGET amgcl::amgcl PROPERTY INTERFACE_INCLUDE_DIRECTORIES)
include_directories(SYSTEM ${AMGCL_INCLUDE_DIRS})
if(CUDA_FOUND)
set_source_files_properties(opm/simulators/linalg/bda/amgclSolverBackend.cpp PROPERTIES LANGUAGE CUDA)
endif()
endif()
if(OpenCL_FOUND)

View File

@ -119,6 +119,9 @@ if(HAVE_AMGCL)
list (APPEND MAIN_SOURCE_FILES opm/simulators/linalg/bda/WellContributions.cpp)
list (APPEND MAIN_SOURCE_FILES opm/simulators/linalg/bda/MultisegmentWellContribution.cpp)
list (APPEND MAIN_SOURCE_FILES opm/simulators/linalg/bda/amgclSolverBackend.cpp)
if(CUDA_FOUND)
list (APPEND MAIN_SOURCE_FILES opm/simulators/linalg/bda/amgclSolverBackend.cu)
endif()
endif()
if(MPI_FOUND)
list(APPEND MAIN_SOURCE_FILES opm/simulators/utils/ParallelEclipseState.cpp

View File

@ -30,6 +30,10 @@
#include <boost/property_tree/json_parser.hpp>
#if HAVE_VEXCL
#include <amgcl/backend/vexcl.hpp>
#include <amgcl/backend/vexcl_static_matrix.hpp>
#endif
namespace bda
{
@ -74,10 +78,10 @@ void amgclSolverBackend<block_size>::initialize(int N_, int nnz_, int dim) {
if (file.is_open()) { // if file exists, read parameters from file
boost::property_tree::read_json(file, prm);
backend_type_string = prm.get<std::string>("backend_type"); // defaults to cpu if not specified
backend_type_string = prm.get("backend_type", "cpu"); // defaults to cpu if not specified
out << "Using parameters from " << filename << ":\n";
} else { // otherwise use default parameters, same as Dune
prm.put("backend_type", "cpu");
prm.put("backend_type", "cpu"); // put it in the tree so it gets printed
prm.put("precond.class", "relaxation");
prm.put("precond.type", "ilu0");
prm.put("precond.damping", 0.9);
@ -85,6 +89,7 @@ void amgclSolverBackend<block_size>::initialize(int N_, int nnz_, int dim) {
prm.put("solver.tol", tolerance);
prm.put("solver.maxiter", maxit);
prm.put("solver.verbose", verbosity >= 2);
backend_type_string = prm.get("backend_type", "cpu");
out << "Using default amgcl parameters:\n";
}
@ -98,16 +103,11 @@ void amgclSolverBackend<block_size>::initialize(int N_, int nnz_, int dim) {
} else if (backend_type_string == "vexcl") {
backend_type = Amgcl_backend_type::vexcl;
} else {
OPM_THROW(std::logic_error, "Error unknown value for amgcl parameter 'backend_type'");
OPM_THROW(std::logic_error, "Error unknown value for amgcl parameter 'backend_type', use [cpu|cuda|vexcl]");
}
if (backend_type == Amgcl_backend_type::cuda) {
#if HAVE_CUDA
cudaDeviceProp prop;
cudaGetDeviceProperties(&prop, deviceID);
out << prop.name << std::endl;
cusparseCreate(&CUDA_bprm.cusparse_handle);
#else
#if !HAVE_CUDA
OPM_THROW(std::logic_error, "Error amgcl is trying to use CUDA, but CUDA was not found by CMake");
#endif
}
@ -211,33 +211,11 @@ void solve_vexcl(
template <unsigned int block_size>
void amgclSolverBackend<block_size>::solve_system(double *b, BdaResult &res) {
Timer t;
int iters = 0;
double error = 0.0;
try {
if (backend_type == Amgcl_backend_type::cuda) { // use CUDA
#if HAVE_CUDA
// create matrix object
auto A = std::tie(N, A_rows, A_cols, A_vals);
// create solver and construct preconditioner
// don't reuse this unless the preconditioner can be reused
CUDA_Solver solve(A, prm, CUDA_bprm);
// print solver structure (once)
std::call_once(print_info, [&](){
std::ostringstream out;
out << solve << std::endl;
OpmLog::info(out.str());
});
thrust::device_vector<double> B(b, b + N);
thrust::device_vector<double> X(N, 0.0);
// actually solve
std::tie(iters, error) = solve(B, X);
thrust::copy(X.begin(), X.end(), x.begin());
solve_cuda(b);
#endif
} else if (backend_type == Amgcl_backend_type::cpu) { // use builtin backend (CPU)
// create matrix object

View File

@ -0,0 +1,89 @@
/*
Copyright 2021 Equinor ASA
This file is part of the Open Porous Media project (OPM).
OPM is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
OPM is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with OPM. If not, see <http://www.gnu.org/licenses/>.
*/
#include <config.h>
#include <sstream>
#include <opm/common/OpmLog/OpmLog.hpp>
#include <amgcl/backend/cuda.hpp>
#include <amgcl/relaxation/cusparse_ilu0.hpp>
#include <opm/simulators/linalg/bda/amgclSolverBackend.hpp>
/// This file is only compiled when both amgcl and CUDA are found by CMake
namespace bda
{
using Opm::OpmLog;
template <unsigned int block_size>
void amgclSolverBackend<block_size>::solve_cuda(double *b) {
typedef amgcl::backend::cuda<double> CUDA_Backend;
typedef amgcl::make_solver<amgcl::runtime::preconditioner<CUDA_Backend>, amgcl::runtime::solver::wrapper<CUDA_Backend> > CUDA_Solver;
static typename CUDA_Backend::params CUDA_bprm; // amgcl backend parameters, only used for cusparseHandle
// initialize cusparse handle for amgcl, cannot merge this call_once with 'print solver structure'
std::call_once(cuda_initialize, [&](){
cudaDeviceProp prop;
cudaGetDeviceProperties(&prop, deviceID);
std::ostringstream out;
out << prop.name << std::endl;
OpmLog::info(out.str());
cusparseCreate(&CUDA_bprm.cusparse_handle);
});
// create matrix object
auto A = std::tie(N, A_rows, A_cols, A_vals);
// create solver and construct preconditioner
// don't reuse this unless the preconditioner can be reused
CUDA_Solver solve(A, prm, CUDA_bprm);
// print solver structure (once)
std::call_once(print_info, [&](){
std::ostringstream out;
out << solve << std::endl;
OpmLog::info(out.str());
});
thrust::device_vector<double> B(b, b + N);
thrust::device_vector<double> X(N, 0.0);
// actually solve
std::tie(iters, error) = solve(B, X);
thrust::copy(X.begin(), X.end(), x.begin());
}
#define INSTANTIATE_BDA_FUNCTIONS(n) \
template void amgclSolverBackend<n>::solve_cuda(double*); \
INSTANTIATE_BDA_FUNCTIONS(1);
INSTANTIATE_BDA_FUNCTIONS(2);
INSTANTIATE_BDA_FUNCTIONS(3);
INSTANTIATE_BDA_FUNCTIONS(4);
#undef INSTANTIATE_BDA_FUNCTIONS
} // namespace bda

View File

@ -38,16 +38,6 @@
#include <amgcl/preconditioner/runtime.hpp>
#include <amgcl/value_type/static_matrix.hpp>
#if HAVE_CUDA
#include <amgcl/backend/cuda.hpp>
#include <amgcl/relaxation/cusparse_ilu0.hpp>
#endif
#if HAVE_VEXCL
#include <amgcl/backend/vexcl.hpp>
#include <amgcl/backend/vexcl_static_matrix.hpp>
#endif
namespace bda
{
@ -69,11 +59,6 @@ class amgclSolverBackend : public BdaSolver<block_size>
using Base::tolerance;
using Base::initialized;
#if HAVE_CUDA
typedef amgcl::backend::cuda<double> CUDA_Backend;
typedef amgcl::make_solver<amgcl::runtime::preconditioner<CUDA_Backend>, amgcl::runtime::solver::wrapper<CUDA_Backend> > CUDA_Solver;
#endif
typedef amgcl::static_matrix<double, block_size, block_size> dmat_type; // matrix value type in double precision
typedef amgcl::static_matrix<double, block_size, 1> dvec_type; // the corresponding vector value type
typedef amgcl::backend::builtin<dmat_type> CPU_Backend;
@ -97,8 +82,12 @@ private:
Amgcl_backend_type backend_type = cpu;
boost::property_tree::ptree prm; // amgcl parameters
int iters = 0;
double error = 0.0;
#if HAVE_CUDA
typename CUDA_Backend::params CUDA_bprm; // amgcl backend parameters, only used for cusparseHandle
std::once_flag cuda_initialize;
void solve_cuda(double *b);
#endif
/// Initialize GPU and allocate memory