| // Ceres Solver - A fast non-linear least squares minimizer | |
| // Copyright 2022 Google Inc. All rights reserved. | |
| // http://ceres-solver.org/ | |
| // | |
| // Redistribution and use in source and binary forms, with or without | |
| // modification, are permitted provided that the following conditions are met: | |
| // | |
| // * Redistributions of source code must retain the above copyright notice, | |
| // this list of conditions and the following disclaimer. | |
| // * Redistributions in binary form must reproduce the above copyright notice, | |
| // this list of conditions and the following disclaimer in the documentation | |
| // and/or other materials provided with the distribution. | |
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| // used to endorse or promote products derived from this software without | |
| // specific prior written permission. | |
| // | |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | |
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| // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE | |
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| // POSSIBILITY OF SUCH DAMAGE. | |
| // | |
| // Author: joydeepb@cs.utexas.edu (Joydeep Biswas) | |
| // | |
| // A CUDA sparse matrix linear operator. | |
| // This include must come before any #ifndef check on Ceres compile options. | |
| // clang-format off | |
| #include "ceres/internal/config.h" | |
| // clang-format on | |
| #include "ceres/cuda_sparse_matrix.h" | |
| #include <math.h> | |
| #include <memory> | |
| #include "ceres/block_sparse_matrix.h" | |
| #include "ceres/compressed_row_sparse_matrix.h" | |
| #include "ceres/context_impl.h" | |
| #include "ceres/crs_matrix.h" | |
| #include "ceres/internal/export.h" | |
| #include "ceres/types.h" | |
| #include "ceres/wall_time.h" | |
| #ifndef CERES_NO_CUDA | |
| #include "ceres/ceres_cuda_kernels.h" | |
| #include "ceres/cuda_buffer.h" | |
| #include "ceres/cuda_vector.h" | |
| #include "cusparse.h" | |
| namespace ceres::internal { | |
| CudaSparseMatrix::CudaSparseMatrix( | |
| ContextImpl* context, const CompressedRowSparseMatrix& crs_matrix) { | |
| DCHECK_NE(context, nullptr); | |
| CHECK(context->IsCUDAInitialized()); | |
| context_ = context; | |
| num_rows_ = crs_matrix.num_rows(); | |
| num_cols_ = crs_matrix.num_cols(); | |
| num_nonzeros_ = crs_matrix.num_nonzeros(); | |
| rows_.CopyFromCpu(crs_matrix.rows(), num_rows_ + 1, context_->stream_); | |
| cols_.CopyFromCpu(crs_matrix.cols(), num_nonzeros_, context_->stream_); | |
| values_.CopyFromCpu(crs_matrix.values(), num_nonzeros_, context_->stream_); | |
| cusparseCreateCsr(&descr_, | |
| num_rows_, | |
| num_cols_, | |
| num_nonzeros_, | |
| rows_.data(), | |
| cols_.data(), | |
| values_.data(), | |
| CUSPARSE_INDEX_32I, | |
| CUSPARSE_INDEX_32I, | |
| CUSPARSE_INDEX_BASE_ZERO, | |
| CUDA_R_64F); | |
| } | |
| CudaSparseMatrix::~CudaSparseMatrix() { | |
| CHECK_EQ(cusparseDestroySpMat(descr_), CUSPARSE_STATUS_SUCCESS); | |
| descr_ = nullptr; | |
| } | |
| void CudaSparseMatrix::CopyValuesFromCpu( | |
| const CompressedRowSparseMatrix& crs_matrix) { | |
| // There is no quick and easy way to verify that the structure is unchanged, | |
| // but at least we can check that the size of the matrix and the number of | |
| // nonzeros is unchanged. | |
| CHECK_EQ(num_rows_, crs_matrix.num_rows()); | |
| CHECK_EQ(num_cols_, crs_matrix.num_cols()); | |
| CHECK_EQ(num_nonzeros_, crs_matrix.num_nonzeros()); | |
| values_.CopyFromCpu(crs_matrix.values(), num_nonzeros_, context_->stream_); | |
| } | |
| void CudaSparseMatrix::SpMv(cusparseOperation_t op, | |
| const CudaVector& x, | |
| CudaVector* y) { | |
| size_t buffer_size = 0; | |
| const double alpha = 1.0; | |
| const double beta = 1.0; | |
| CHECK_EQ(cusparseSpMV_bufferSize(context_->cusparse_handle_, | |
| op, | |
| &alpha, | |
| descr_, | |
| x.descr(), | |
| &beta, | |
| y->descr(), | |
| CUDA_R_64F, | |
| CUSPARSE_SPMV_ALG_DEFAULT, | |
| &buffer_size), | |
| CUSPARSE_STATUS_SUCCESS); | |
| spmv_buffer_.Reserve(buffer_size); | |
| CHECK_EQ(cusparseSpMV(context_->cusparse_handle_, | |
| op, | |
| &alpha, | |
| descr_, | |
| x.descr(), | |
| &beta, | |
| y->descr(), | |
| CUDA_R_64F, | |
| CUSPARSE_SPMV_ALG_DEFAULT, | |
| spmv_buffer_.data()), | |
| CUSPARSE_STATUS_SUCCESS); | |
| } | |
| void CudaSparseMatrix::RightMultiplyAndAccumulate(const CudaVector& x, | |
| CudaVector* y) { | |
| SpMv(CUSPARSE_OPERATION_NON_TRANSPOSE, x, y); | |
| } | |
| void CudaSparseMatrix::LeftMultiplyAndAccumulate(const CudaVector& x, | |
| CudaVector* y) { | |
| // TODO(Joydeep Biswas): We should consider storing a transposed copy of the | |
| // matrix by converting CSR to CSC. From the cuSPARSE documentation: | |
| // "In general, opA == CUSPARSE_OPERATION_NON_TRANSPOSE is 3x faster than opA | |
| // != CUSPARSE_OPERATION_NON_TRANSPOSE" | |
| SpMv(CUSPARSE_OPERATION_TRANSPOSE, x, y); | |
| } | |
| } // namespace ceres::internal | |
| #endif // CERES_NO_CUDA |