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https://github.com/OPM/opm-simulators.git
synced 2024-12-28 02:00:59 -06:00
Factor out CUDA part of amgclSolver
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@ -221,9 +221,6 @@ if(amgcl_FOUND)
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# Hence we set AMGCL_INCLUDE_DIRS.
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get_property(AMGCL_INCLUDE_DIRS TARGET amgcl::amgcl PROPERTY INTERFACE_INCLUDE_DIRECTORIES)
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include_directories(SYSTEM ${AMGCL_INCLUDE_DIRS})
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if(CUDA_FOUND)
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set_source_files_properties(opm/simulators/linalg/bda/amgclSolverBackend.cpp PROPERTIES LANGUAGE CUDA)
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endif()
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endif()
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if(OpenCL_FOUND)
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@ -119,6 +119,9 @@ if(HAVE_AMGCL)
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list (APPEND MAIN_SOURCE_FILES opm/simulators/linalg/bda/WellContributions.cpp)
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list (APPEND MAIN_SOURCE_FILES opm/simulators/linalg/bda/MultisegmentWellContribution.cpp)
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list (APPEND MAIN_SOURCE_FILES opm/simulators/linalg/bda/amgclSolverBackend.cpp)
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if(CUDA_FOUND)
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list (APPEND MAIN_SOURCE_FILES opm/simulators/linalg/bda/amgclSolverBackend.cu)
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endif()
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endif()
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if(MPI_FOUND)
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list(APPEND MAIN_SOURCE_FILES opm/simulators/utils/ParallelEclipseState.cpp
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@ -30,6 +30,10 @@
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#include <boost/property_tree/json_parser.hpp>
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#if HAVE_VEXCL
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#include <amgcl/backend/vexcl.hpp>
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#include <amgcl/backend/vexcl_static_matrix.hpp>
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#endif
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namespace bda
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{
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@ -74,10 +78,10 @@ void amgclSolverBackend<block_size>::initialize(int N_, int nnz_, int dim) {
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if (file.is_open()) { // if file exists, read parameters from file
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boost::property_tree::read_json(file, prm);
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backend_type_string = prm.get<std::string>("backend_type"); // defaults to cpu if not specified
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backend_type_string = prm.get("backend_type", "cpu"); // defaults to cpu if not specified
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out << "Using parameters from " << filename << ":\n";
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} else { // otherwise use default parameters, same as Dune
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prm.put("backend_type", "cpu");
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prm.put("backend_type", "cpu"); // put it in the tree so it gets printed
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prm.put("precond.class", "relaxation");
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prm.put("precond.type", "ilu0");
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prm.put("precond.damping", 0.9);
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@ -85,6 +89,7 @@ void amgclSolverBackend<block_size>::initialize(int N_, int nnz_, int dim) {
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prm.put("solver.tol", tolerance);
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prm.put("solver.maxiter", maxit);
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prm.put("solver.verbose", verbosity >= 2);
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backend_type_string = prm.get("backend_type", "cpu");
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out << "Using default amgcl parameters:\n";
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}
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@ -98,16 +103,11 @@ void amgclSolverBackend<block_size>::initialize(int N_, int nnz_, int dim) {
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} else if (backend_type_string == "vexcl") {
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backend_type = Amgcl_backend_type::vexcl;
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} else {
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OPM_THROW(std::logic_error, "Error unknown value for amgcl parameter 'backend_type'");
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OPM_THROW(std::logic_error, "Error unknown value for amgcl parameter 'backend_type', use [cpu|cuda|vexcl]");
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}
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if (backend_type == Amgcl_backend_type::cuda) {
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#if HAVE_CUDA
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cudaDeviceProp prop;
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cudaGetDeviceProperties(&prop, deviceID);
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out << prop.name << std::endl;
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cusparseCreate(&CUDA_bprm.cusparse_handle);
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#else
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#if !HAVE_CUDA
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OPM_THROW(std::logic_error, "Error amgcl is trying to use CUDA, but CUDA was not found by CMake");
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#endif
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}
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@ -211,33 +211,11 @@ void solve_vexcl(
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template <unsigned int block_size>
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void amgclSolverBackend<block_size>::solve_system(double *b, BdaResult &res) {
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Timer t;
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int iters = 0;
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double error = 0.0;
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try {
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if (backend_type == Amgcl_backend_type::cuda) { // use CUDA
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#if HAVE_CUDA
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// create matrix object
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auto A = std::tie(N, A_rows, A_cols, A_vals);
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// create solver and construct preconditioner
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// don't reuse this unless the preconditioner can be reused
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CUDA_Solver solve(A, prm, CUDA_bprm);
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// print solver structure (once)
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std::call_once(print_info, [&](){
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std::ostringstream out;
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out << solve << std::endl;
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OpmLog::info(out.str());
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});
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thrust::device_vector<double> B(b, b + N);
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thrust::device_vector<double> X(N, 0.0);
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// actually solve
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std::tie(iters, error) = solve(B, X);
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thrust::copy(X.begin(), X.end(), x.begin());
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solve_cuda(b);
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#endif
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} else if (backend_type == Amgcl_backend_type::cpu) { // use builtin backend (CPU)
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// create matrix object
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89
opm/simulators/linalg/bda/amgclSolverBackend.cu
Normal file
89
opm/simulators/linalg/bda/amgclSolverBackend.cu
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@ -0,0 +1,89 @@
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/*
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Copyright 2021 Equinor ASA
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This file is part of the Open Porous Media project (OPM).
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OPM is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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OPM is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with OPM. If not, see <http://www.gnu.org/licenses/>.
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*/
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#include <config.h>
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#include <sstream>
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#include <opm/common/OpmLog/OpmLog.hpp>
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#include <amgcl/backend/cuda.hpp>
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#include <amgcl/relaxation/cusparse_ilu0.hpp>
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#include <opm/simulators/linalg/bda/amgclSolverBackend.hpp>
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/// This file is only compiled when both amgcl and CUDA are found by CMake
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namespace bda
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{
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using Opm::OpmLog;
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template <unsigned int block_size>
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void amgclSolverBackend<block_size>::solve_cuda(double *b) {
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typedef amgcl::backend::cuda<double> CUDA_Backend;
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typedef amgcl::make_solver<amgcl::runtime::preconditioner<CUDA_Backend>, amgcl::runtime::solver::wrapper<CUDA_Backend> > CUDA_Solver;
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static typename CUDA_Backend::params CUDA_bprm; // amgcl backend parameters, only used for cusparseHandle
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// initialize cusparse handle for amgcl, cannot merge this call_once with 'print solver structure'
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std::call_once(cuda_initialize, [&](){
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cudaDeviceProp prop;
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cudaGetDeviceProperties(&prop, deviceID);
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std::ostringstream out;
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out << prop.name << std::endl;
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OpmLog::info(out.str());
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cusparseCreate(&CUDA_bprm.cusparse_handle);
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});
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// create matrix object
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auto A = std::tie(N, A_rows, A_cols, A_vals);
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// create solver and construct preconditioner
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// don't reuse this unless the preconditioner can be reused
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CUDA_Solver solve(A, prm, CUDA_bprm);
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// print solver structure (once)
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std::call_once(print_info, [&](){
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std::ostringstream out;
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out << solve << std::endl;
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OpmLog::info(out.str());
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});
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thrust::device_vector<double> B(b, b + N);
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thrust::device_vector<double> X(N, 0.0);
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// actually solve
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std::tie(iters, error) = solve(B, X);
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thrust::copy(X.begin(), X.end(), x.begin());
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}
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#define INSTANTIATE_BDA_FUNCTIONS(n) \
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template void amgclSolverBackend<n>::solve_cuda(double*); \
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INSTANTIATE_BDA_FUNCTIONS(1);
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INSTANTIATE_BDA_FUNCTIONS(2);
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INSTANTIATE_BDA_FUNCTIONS(3);
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INSTANTIATE_BDA_FUNCTIONS(4);
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#undef INSTANTIATE_BDA_FUNCTIONS
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} // namespace bda
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@ -38,16 +38,6 @@
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#include <amgcl/preconditioner/runtime.hpp>
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#include <amgcl/value_type/static_matrix.hpp>
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#if HAVE_CUDA
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#include <amgcl/backend/cuda.hpp>
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#include <amgcl/relaxation/cusparse_ilu0.hpp>
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#endif
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#if HAVE_VEXCL
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#include <amgcl/backend/vexcl.hpp>
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#include <amgcl/backend/vexcl_static_matrix.hpp>
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#endif
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namespace bda
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{
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@ -69,11 +59,6 @@ class amgclSolverBackend : public BdaSolver<block_size>
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using Base::tolerance;
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using Base::initialized;
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#if HAVE_CUDA
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typedef amgcl::backend::cuda<double> CUDA_Backend;
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typedef amgcl::make_solver<amgcl::runtime::preconditioner<CUDA_Backend>, amgcl::runtime::solver::wrapper<CUDA_Backend> > CUDA_Solver;
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#endif
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typedef amgcl::static_matrix<double, block_size, block_size> dmat_type; // matrix value type in double precision
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typedef amgcl::static_matrix<double, block_size, 1> dvec_type; // the corresponding vector value type
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typedef amgcl::backend::builtin<dmat_type> CPU_Backend;
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@ -97,8 +82,12 @@ private:
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Amgcl_backend_type backend_type = cpu;
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boost::property_tree::ptree prm; // amgcl parameters
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int iters = 0;
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double error = 0.0;
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#if HAVE_CUDA
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typename CUDA_Backend::params CUDA_bprm; // amgcl backend parameters, only used for cusparseHandle
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std::once_flag cuda_initialize;
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void solve_cuda(double *b);
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#endif
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/// Initialize GPU and allocate memory
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