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opm-simulators/opm/simulators/linalg/bda/BdaBridge.cpp
Tong Dong Qiu 2c50951ddd Implement PR comments
2023-04-06 13:14:19 +02:00

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/*
Copyright 2019 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 "dune/istl/bcrsmatrix.hh"
#include <opm/simulators/linalg/matrixblock.hh>
#include <opm/common/OpmLog/OpmLog.hpp>
#include <opm/common/ErrorMacros.hpp>
#include <opm/simulators/linalg/bda/BdaBridge.hpp>
#include <opm/simulators/linalg/bda/BdaResult.hpp>
#if HAVE_CUDA
#include <opm/simulators/linalg/bda/cuda/cusparseSolverBackend.hpp>
#endif
#if HAVE_OPENCL
#include <opm/simulators/linalg/bda/opencl/openclSolverBackend.hpp>
#include <opm/simulators/linalg/bda/opencl/openclWellContributions.hpp>
#endif
#if HAVE_AMGCL
#include <opm/simulators/linalg/bda/amgclSolverBackend.hpp>
#endif
#if HAVE_ROCALUTION
#include <opm/simulators/linalg/bda/rocalutionSolverBackend.hpp>
#endif
#if HAVE_ROCSPARSE
#include <opm/simulators/linalg/bda/rocsparseSolverBackend.hpp>
#endif
typedef Dune::InverseOperatorResult InverseOperatorResult;
namespace Opm
{
using Opm::Accelerator::BdaResult;
using Opm::Accelerator::BdaSolver;
using Opm::Accelerator::SolverStatus;
template <class BridgeMatrix, class BridgeVector, int block_size>
BdaBridge<BridgeMatrix, BridgeVector, block_size>::BdaBridge(std::string accelerator_mode_,
int linear_solver_verbosity, int maxit,
double tolerance,
[[maybe_unused]] unsigned int platformID,
unsigned int deviceID,
[[maybe_unused]] bool opencl_ilu_parallel,
[[maybe_unused]] std::string linsolver)
: verbosity(linear_solver_verbosity), accelerator_mode(accelerator_mode_)
{
if (accelerator_mode.compare("cusparse") == 0) {
#if HAVE_CUDA
use_gpu = true;
backend.reset(new Opm::Accelerator::cusparseSolverBackend<block_size>(linear_solver_verbosity, maxit, tolerance, deviceID));
#else
OPM_THROW(std::logic_error, "Error cusparseSolver was chosen, but CUDA was not found by CMake");
#endif
} else if (accelerator_mode.compare("opencl") == 0) {
#if HAVE_OPENCL
use_gpu = true;
backend.reset(new Opm::Accelerator::openclSolverBackend<block_size>(linear_solver_verbosity, maxit, tolerance, platformID, deviceID, opencl_ilu_parallel, linsolver));
#else
OPM_THROW(std::logic_error, "Error openclSolver was chosen, but OpenCL was not found by CMake");
#endif
} else if (accelerator_mode.compare("amgcl") == 0) {
#if HAVE_AMGCL
use_gpu = true; // should be replaced by a 'use_bridge' boolean
backend.reset(new Opm::Accelerator::amgclSolverBackend<block_size>(linear_solver_verbosity, maxit, tolerance, platformID, deviceID));
#else
OPM_THROW(std::logic_error, "Error amgclSolver was chosen, but amgcl was not found by CMake");
#endif
} else if (accelerator_mode.compare("rocalution") == 0) {
#if HAVE_ROCALUTION
use_gpu = true; // should be replaced by a 'use_bridge' boolean
backend.reset(new Opm::Accelerator::rocalutionSolverBackend<block_size>(linear_solver_verbosity, maxit, tolerance));
#else
OPM_THROW(std::logic_error, "Error rocalutionSolver was chosen, but rocalution was not found by CMake");
#endif
} else if (accelerator_mode.compare("rocsparse") == 0) {
#if HAVE_ROCSPARSE
use_gpu = true; // should be replaced by a 'use_bridge' boolean
backend.reset(new Opm::Accelerator::rocsparseSolverBackend<block_size>(linear_solver_verbosity, maxit, tolerance, platformID, deviceID));
#else
OPM_THROW(std::logic_error, "Error rocsparseSolver was chosen, but rocsparse/rocblas was not found by CMake");
#endif
} else if (accelerator_mode.compare("none") == 0) {
use_gpu = false;
} else {
OPM_THROW(std::logic_error, "Error unknown value for parameter 'AcceleratorMode', should be passed like '--accelerator-mode=[none|cusparse|opencl|amgcl|rocalution]");
}
}
template <class BridgeMatrix>
int replaceZeroDiagonal(BridgeMatrix& mat, std::vector<typename BridgeMatrix::size_type>& diag_indices) {
int numZeros = 0;
const int dim = mat[0][0].N(); // might be replaced with BridgeMatrix::block_type::size()
const double zero_replace = 1e-15;
if (diag_indices.empty()) {
int Nb = mat.N();
diag_indices.reserve(Nb);
for (typename BridgeMatrix::iterator r = mat.begin(); r != mat.end(); ++r) {
auto diag = r->find(r.index()); // diag is an iterator
assert(diag.index() == r.index()); // every row must have a diagonal block
for (int rr = 0; rr < dim; ++rr) {
auto& val = (*diag)[rr][rr]; // reference to easily change the value
if (val == 0.0) { // could be replaced by '< 1e-30' or similar
val = zero_replace;
++numZeros;
}
}
diag_indices.emplace_back(diag.offset());
}
}else{
for (typename BridgeMatrix::iterator r = mat.begin(); r != mat.end(); ++r) {
typename BridgeMatrix::size_type offset = diag_indices[r.index()];
auto& diag_block = r->getptr()[offset]; // diag_block is a reference to MatrixBlock, located on column r of row r
for (int rr = 0; rr < dim; ++rr) {
auto& val = diag_block[rr][rr];
if (val == 0.0) { // could be replaced by '< 1e-30' or similar
val = zero_replace;
++numZeros;
}
}
}
}
return numZeros;
}
// iterate sparsity pattern from Matrix and put colIndices and rowPointers in arrays
// sparsity pattern should stay the same
// this could be removed if Dune::BCRSMatrix features an API call that returns colIndices and rowPointers
template <class BridgeMatrix, class BridgeVector, int block_size>
void BdaBridge<BridgeMatrix, BridgeVector, block_size>::copySparsityPatternFromISTL(const BridgeMatrix& mat, std::vector<int> &h_rows, std::vector<int> &h_cols) {
h_rows.clear();
h_cols.clear();
// convert colIndices and rowPointers
h_rows.emplace_back(0);
for (typename BridgeMatrix::const_iterator r = mat.begin(); r != mat.end(); ++r) {
for (auto c = r->begin(); c != r->end(); ++c) {
h_cols.emplace_back(c.index());
}
h_rows.emplace_back(h_cols.size());
}
// h_rows and h_cols could be changed to 'unsigned int', but cusparse expects 'int'
if (static_cast<unsigned int>(h_rows[mat.N()]) != mat.nonzeroes()) {
OPM_THROW(std::logic_error, "Error size of rows do not sum to number of nonzeroes in BdaBridge::copySparsityPatternFromISTL()");
}
}
// check if the nnz values of the matrix are in contiguous memory
// this is done by checking if the distance between the last value of the last block of row 0 and
// the first value of the first row of row 1 is equal to 1
// if the matrix only has 1 row, it is always contiguous
template <class BridgeMatrix>
void checkMemoryContiguous(const BridgeMatrix& mat) {
auto block_size = mat[0][0].N();
auto row = mat.begin();
auto last_of_row0 = row->begin();
// last_of_row0 points to last block, not to row->end()
for(auto tmp = row->begin(); tmp != row->end(); ++tmp) {
last_of_row0 = tmp;
}
bool isContiguous = mat.N() < 2 || std::distance(&((*last_of_row0)[block_size-1][block_size-1]), &(*mat[1].begin())[0][0]) == 1;
if (!isContiguous) {
OPM_THROW(std::logic_error, "Error memory of Matrix looks not contiguous");
}
}
template <class BridgeMatrix, class BridgeVector, int block_size>
void BdaBridge<BridgeMatrix, BridgeVector, block_size>::solve_system(BridgeMatrix* bridgeMat,
BridgeMatrix* jacMat,
int numJacobiBlocks,
BridgeVector& b,
WellContributions& wellContribs,
InverseOperatorResult& res)
{
if (use_gpu) {
BdaResult result;
result.converged = false;
const int dim = (*bridgeMat)[0][0].N();
const int Nb = bridgeMat->N();
const int nnzb = bridgeMat->nonzeroes();
if (dim != 3) {
OpmLog::warning("BdaSolver only accepts blocksize = 3 at this time, will use Dune for the remainder of the program");
use_gpu = false;
return;
}
if (!matrix) {
h_rows.reserve(Nb+1);
h_cols.reserve(nnzb);
copySparsityPatternFromISTL(*bridgeMat, h_rows, h_cols);
checkMemoryContiguous(*bridgeMat);
matrix = std::make_unique<Opm::Accelerator::BlockedMatrix>(Nb, nnzb, block_size, static_cast<double*>(&(((*bridgeMat)[0][0][0][0]))), h_cols.data(), h_rows.data());
}
Dune::Timer t_zeros;
int numZeros = replaceZeroDiagonal(*bridgeMat, diagIndices);
if (verbosity >= 2) {
std::ostringstream out;
out << "Checking zeros took: " << t_zeros.stop() << " s, found " << numZeros << " zeros";
OpmLog::info(out.str());
}
if (numJacobiBlocks >= 2) {
const int jacNnzb = (h_jacRows.empty()) ? jacMat->nonzeroes() : h_jacRows.back();
if (!jacMatrix) {
h_jacRows.reserve(Nb+1);
h_jacCols.reserve(jacNnzb);
copySparsityPatternFromISTL(*jacMat, h_jacRows, h_jacCols);
checkMemoryContiguous(*jacMat);
jacMatrix = std::make_unique<Opm::Accelerator::BlockedMatrix>(Nb, jacNnzb, block_size, static_cast<double*>(&(((*jacMat)[0][0][0][0]))), h_jacCols.data(), h_jacRows.data());
}
Dune::Timer t_zeros2;
int jacNumZeros = replaceZeroDiagonal(*jacMat, jacDiagIndices);
if (verbosity >= 2) {
std::ostringstream out;
out << "Checking zeros for jacMat took: " << t_zeros2.stop() << " s, found " << jacNumZeros << " zeros";
OpmLog::info(out.str());
}
}
/////////////////////////
// actually solve
// assume that underlying data (nonzeroes) from b (Dune::BlockVector) are contiguous, if this is not the case, the chosen BdaSolver is expected to perform undefined behaviour
SolverStatus status = backend->solve_system(matrix, static_cast<double*>(&(b[0][0])), jacMatrix, wellContribs, result);
switch(status) {
case SolverStatus::BDA_SOLVER_SUCCESS:
//OpmLog::info("BdaSolver converged");
break;
case SolverStatus::BDA_SOLVER_ANALYSIS_FAILED:
OpmLog::warning("BdaSolver could not analyse level information of matrix, perhaps there is still a 0.0 on the diagonal of a block on the diagonal");
break;
case SolverStatus::BDA_SOLVER_CREATE_PRECONDITIONER_FAILED:
OpmLog::warning("BdaSolver could not create preconditioner, perhaps there is still a 0.0 on the diagonal of a block on the diagonal");
break;
default:
OpmLog::warning("BdaSolver returned unknown status code");
}
res.iterations = result.iterations;
res.reduction = result.reduction;
res.converged = result.converged;
res.conv_rate = result.conv_rate;
res.elapsed = result.elapsed;
} else {
res.converged = false;
}
}
template <class BridgeMatrix, class BridgeVector, int block_size>
void BdaBridge<BridgeMatrix, BridgeVector, block_size>::get_result([[maybe_unused]] BridgeVector& x) {
if (use_gpu) {
backend->get_result(static_cast<double*>(&(x[0][0])));
}
}
template <class BridgeMatrix, class BridgeVector, int block_size>
void BdaBridge<BridgeMatrix, BridgeVector, block_size>::initWellContributions([[maybe_unused]] WellContributions& wellContribs,
[[maybe_unused]] unsigned N) {
if(accelerator_mode.compare("opencl") == 0){
#if HAVE_OPENCL
const auto openclBackend = static_cast<const Opm::Accelerator::openclSolverBackend<block_size>*>(backend.get());
static_cast<WellContributionsOCL&>(wellContribs).setOpenCLEnv(openclBackend->context.get(), openclBackend->queue.get());
#else
OPM_THROW(std::logic_error, "Error openclSolver was chosen, but OpenCL was not found by CMake");
#endif
}
wellContribs.setVectorSize(N);
}
// the tests use Dune::FieldMatrix, Flow uses Opm::MatrixBlock
#define INSTANTIATE_BDA_FUNCTIONS(n) \
template class BdaBridge<Dune::BCRSMatrix<Opm::MatrixBlock<double, n, n>, std::allocator<Opm::MatrixBlock<double, n, n> > >, \
Dune::BlockVector<Dune::FieldVector<double, n>, std::allocator<Dune::FieldVector<double, n> > >, \
n>; \
\
template class BdaBridge<Dune::BCRSMatrix<Dune::FieldMatrix<double, n, n>, std::allocator<Dune::FieldMatrix<double, n, n> > >, \
Dune::BlockVector<Dune::FieldVector<double, n>, std::allocator<Dune::FieldVector<double, n> > >, \
n>;
INSTANTIATE_BDA_FUNCTIONS(1);
INSTANTIATE_BDA_FUNCTIONS(2);
INSTANTIATE_BDA_FUNCTIONS(3);
INSTANTIATE_BDA_FUNCTIONS(4);
INSTANTIATE_BDA_FUNCTIONS(5);
INSTANTIATE_BDA_FUNCTIONS(6);
#undef INSTANTIATE_BDA_FUNCTIONS
} // namespace Opm
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