mirror of
https://github.com/OPM/opm-simulators.git
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139 lines
7.5 KiB
C++
139 lines
7.5 KiB
C++
/*
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Copyright 2020 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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#ifndef OPENCL_HPP
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#define OPENCL_HPP
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#include <string>
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#include <memory>
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#include <opm/simulators/linalg/bda/opencl.hpp>
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namespace bda
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{
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using spmv_kernel_type = cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, const unsigned int,
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cl::Buffer&, cl::Buffer&, const unsigned int, cl::LocalSpaceArg>;
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using ilu_apply1_kernel_type = cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, const cl::Buffer&,
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cl::Buffer&, cl::Buffer&, const unsigned int, const unsigned int, cl::LocalSpaceArg>;
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using ilu_apply2_kernel_type = cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&,
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cl::Buffer&, cl::Buffer&, const unsigned int, const unsigned int, cl::LocalSpaceArg>;
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using stdwell_apply_kernel_type = cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&,
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cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&,
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const unsigned int, const unsigned int, cl::Buffer&,
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cl::LocalSpaceArg, cl::LocalSpaceArg, cl::LocalSpaceArg>;
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using stdwell_apply_no_reorder_kernel_type = cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&,
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cl::Buffer&, cl::Buffer&, cl::Buffer&,
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const unsigned int, const unsigned int, cl::Buffer&,
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cl::LocalSpaceArg, cl::LocalSpaceArg, cl::LocalSpaceArg>;
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using ilu_decomp_kernel_type = cl::KernelFunctor<const unsigned int, const unsigned int, cl::Buffer&, cl::Buffer&,
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cl::Buffer&, cl::Buffer&, cl::Buffer&, const int, cl::LocalSpaceArg>;
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class OpenclKernels
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{
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private:
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static int verbosity;
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static cl::CommandQueue *queue;
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static std::vector<double> tmp; // used as tmp CPU buffer for dot() and norm()
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static bool initialized;
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static std::unique_ptr<cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, const unsigned int, cl::LocalSpaceArg> > dot_k;
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static std::unique_ptr<cl::KernelFunctor<cl::Buffer&, cl::Buffer&, const unsigned int, cl::LocalSpaceArg> > norm_k;
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static std::unique_ptr<cl::KernelFunctor<cl::Buffer&, const double, cl::Buffer&, const unsigned int> > axpy_k;
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static std::unique_ptr<cl::KernelFunctor<cl::Buffer&, const double, const unsigned int> > scale_k;
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static std::unique_ptr<cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, const double, const double, const unsigned int> > custom_k;
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static std::unique_ptr<spmv_kernel_type> spmv_blocked_k;
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static std::unique_ptr<ilu_apply1_kernel_type> ILU_apply1_k;
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static std::unique_ptr<ilu_apply2_kernel_type> ILU_apply2_k;
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static std::unique_ptr<stdwell_apply_kernel_type> stdwell_apply_k;
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static std::unique_ptr<stdwell_apply_no_reorder_kernel_type> stdwell_apply_no_reorder_k;
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static std::unique_ptr<ilu_decomp_kernel_type> ilu_decomp_k;
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/// Generate string with axpy kernel
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/// a = a + alpha * b
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static std::string get_axpy_string();
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/// Generate string with scale kernel
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/// a = a * alpha
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static std::string get_scale_string();
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/// returns partial sums, instead of the final dot product
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/// partial sums are added on CPU
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static std::string get_dot_1_string();
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/// returns partial sums, instead of the final norm
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/// the square root must be computed on CPU
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static std::string get_norm_string();
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/// Generate string with custom kernel
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/// This kernel combines some ilubicgstab vector operations into 1
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/// p = (p - omega * v) * beta + r
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static std::string get_custom_string();
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/// b = mat * x
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/// algorithm based on:
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/// Optimization of Block Sparse Matrix-Vector Multiplication on Shared-MemoryParallel Architectures,
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/// Ryan Eberhardt, Mark Hoemmen, 2016, https://doi.org/10.1109/IPDPSW.2016.42
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static std::string get_spmv_blocked_string();
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/// ILU apply part 1: forward substitution
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/// solves L*x=y where L is a lower triangular sparse blocked matrix
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/// this L can be it's own BSR matrix (if full_matrix is false),
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/// or it can be inside a normal, square matrix, in that case diagIndex indicates where the rows of L end
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/// \param[in] full_matrix whether the kernel should operate on a full (square) matrix or not
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static std::string get_ILU_apply1_string(bool full_matrix);
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/// ILU apply part 2: backward substitution
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/// solves U*x=y where U is an upper triangular sparse blocked matrix
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/// this U can be it's own BSR matrix (if full_matrix is false),
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/// or it can be inside a normal, square matrix, in that case diagIndex indicates where the rows of U start
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/// \param[in] full_matrix whether the kernel should operate on a full (square) matrix or not
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static std::string get_ILU_apply2_string(bool full_matrix);
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/// Generate string with the stdwell_apply kernels
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/// If reorder is true, the B/Ccols do not correspond with the x/y vector
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/// the x/y vector is reordered, use toOrder to address that
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/// \param[in] reorder whether the matrix is reordered or not
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static std::string get_stdwell_apply_string(bool reorder);
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/// Generate string with the exact ilu decomposition kernel
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/// The kernel takes a full BSR matrix and performs inplace ILU decomposition
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static std::string get_ilu_decomp_string();
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OpenclKernels(){}; // disable instantiation
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public:
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static void init(cl::Context *context, cl::CommandQueue *queue, std::vector<cl::Device>& devices, int verbosity);
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static double dot(cl::Buffer& in1, cl::Buffer& in2, cl::Buffer& out, int N);
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static double norm(cl::Buffer& in, cl::Buffer& out, int N);
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static void axpy(cl::Buffer& in, const double a, cl::Buffer& out, int N);
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static void scale(cl::Buffer& in, const double a, int N);
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static void custom(cl::Buffer& p, cl::Buffer& v, cl::Buffer& r, const double omega, const double beta, int N);
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static void spmv_blocked(cl::Buffer& vals, cl::Buffer& cols, cl::Buffer& rows, cl::Buffer& x, cl::Buffer& b, int Nb, unsigned int block_size);
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static void ILU_apply1(cl::Buffer& vals, cl::Buffer& cols, cl::Buffer& rows, cl::Buffer& diagIndex, const cl::Buffer& y, cl::Buffer& x, cl::Buffer& rowsPerColor, int color, int Nb, unsigned int block_size);
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static void ILU_apply2(cl::Buffer& vals, cl::Buffer& cols, cl::Buffer& rows, cl::Buffer& diagIndex, cl::Buffer& invDiagVals, cl::Buffer& x, cl::Buffer& rowsPerColor, int color, int Nb, unsigned int block_size);
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static void ILU_decomp(int firstRow, int lastRow, cl::Buffer& vals, cl::Buffer& cols, cl::Buffer& rows, cl::Buffer& diagIndex, cl::Buffer& invDiagVals, int Nb, unsigned int block_size);
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};
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} // end namespace bda
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#endif
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