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ChowPatelIlu.hpp
/*
Copyright 2020 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/>.
*/
#ifndef CHOW_PATEL_ILU_HEADER_INCLUDED
#define CHOW_PATEL_ILU_HEADER_INCLUDED
#include <mutex>
#include <opm/simulators/linalg/gpubridge/opencl/opencl.hpp>
// Variables CHOW_PATEL, CHOW_PATEL_GPU and CHOW_PATEL_GPU_PARALLEL are set by CMake
// Pass -DUSE_CHOW_PATEL_ILU=1 to cmake to define CHOW_PATEL and use the iterative ILU decomposition
// Pass -DUSE_CHOW_PATEL_ILU_GPU=1 to run the ILU decomposition sweeps on the GPU
// Pass -DUSE_CHOW_PATEL_ILU_GPU_PARALLEL=1 to use more parallelisation in the GPU kernel, see ChowPatelIlu.cpp
// if CHOW_PATEL is 0, exact ILU decomposition is performed on CPU
// if CHOW_PATEL is 1, iterative ILU decomposition (FGPILU) is done, as described in:
// FINE-GRAINED PARALLEL INCOMPLETE LU FACTORIZATION, E. Chow and A. Patel, SIAM 2015, https://doi.org/10.1137/140968896
// if CHOW_PATEL_GPU is 0, the decomposition is done on CPU
// if CHOW_PATEL_GPU is 1, the decomposition is done by gpu_decomposition() on GPU
// the apply phase of the ChowPatelIlu uses two triangular matrices: L and U
// the exact decomposition uses a full matrix LU which is the superposition of L and U
// ChowPatelIlu could also operate on a full matrix LU when L and U are merged, but it is generally better to keep them split
#if CHOW_PATEL
namespace Opm
{
namespace Accelerator
{
class BlockedMatrix;
// This class implements a blocked version on GPU of the Fine-Grained Parallel ILU (FGPILU) by Chow and Patel 2015:
// FINE-GRAINED PARALLEL INCOMPLETE LU FACTORIZATION, E. Chow and A. Patel, SIAM 2015, https://doi.org/10.1137/140968896
// only blocksize == 3 is supported
// decomposition() allocates the cl::Buffers on the first call, these are C++ objects that deallocate automatically
template <unsigned int block_size>
class ChowPatelIlu
{
private:
cl::Buffer d_Ut_vals, d_L_vals, d_LU_vals;
cl::Buffer d_Ut_ptrs, d_Ut_idxs;
cl::Buffer d_L_rows, d_L_cols;
cl::Buffer d_LU_rows, d_LU_cols;
cl::Buffer d_Ltmp, d_Utmp;
cl::Event event;
std::vector<cl::Event> events;
cl_int err;
std::once_flag initialize_flag;
std::once_flag pattern_uploaded;
int verbosity = 0;
std::unique_ptr<cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&,
cl::Buffer&, cl::Buffer&, cl::Buffer&,
cl::Buffer&, cl::Buffer&, cl::Buffer&,
cl::Buffer&, cl::Buffer&,
const int, cl::LocalSpaceArg, cl::LocalSpaceArg> > chow_patel_ilu_sweep_k;
public:
void decomposition(
cl::CommandQueue *queue, cl::Context *context,
BlockedMatrix *LUmat, BlockedMatrix *Lmat, BlockedMatrix *Umat,
double *invDiagVals, std::vector<int>& diagIndex,
cl::Buffer& d_diagIndex, cl::Buffer& d_invDiagVals,
cl::Buffer& d_Lvals, cl::Buffer& d_Lcols, cl::Buffer& d_Lrows,
cl::Buffer& d_Uvals, cl::Buffer& d_Ucols, cl::Buffer& d_Urows);
void gpu_decomposition(
cl::CommandQueue *queue, cl::Context *context,
int *Ut_ptrs, int *Ut_idxs, double *Ut_vals, int Ut_nnzbs,
int *L_rows, int *L_cols, double *L_vals, int L_nnzbs,
int *LU_rows, int *LU_cols, double *LU_vals, int LU_nnzbs,
int Nb, int num_sweeps);
void setVerbosity(int verbosity_) {
this->verbosity = verbosity_;
}
};
} // namespace Accelerator
} // namespace Opm
#endif // CHOW_PATEL
#endif // CHOW_PATEL_ILU_HEADER_INCLUDED
Opm::Accelerator::BlockedMatrix
This struct resembles a blocked csr matrix, like Dune::BCRSMatrix.
Definition BlockedMatrix.hpp:29
Opm
This file contains a set of helper functions used by VFPProd / VFPInj.
Definition blackoilbioeffectsmodules.hh:43