| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2023 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. |
| // * Neither the name of Google Inc. nor the names of its contributors may be |
| // 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" |
| // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE |
| // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE |
| // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE |
| // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR |
| // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF |
| // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS |
| // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN |
| // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) |
| // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE |
| // POSSIBILITY OF SUCH DAMAGE. |
| // |
| // Authors: dmitriy.korchemkin@gmail.com (Dmitriy Korchemkin) |
| |
| #include "ceres/cuda_block_sparse_crs_view.h" |
| |
| #ifndef CERES_NO_CUDA |
| |
| #include "ceres/cuda_kernels_bsm_to_crs.h" |
| |
| namespace ceres::internal { |
| |
| CudaBlockSparseCRSView::CudaBlockSparseCRSView(const BlockSparseMatrix& bsm, |
| ContextImpl* context) |
| : context_(context) { |
| block_structure_ = std::make_unique<CudaBlockSparseStructure>( |
| *bsm.block_structure(), context); |
| crs_matrix_ = std::make_unique<CudaSparseMatrix>( |
| bsm.num_rows(), bsm.num_cols(), bsm.num_nonzeros(), context); |
| FillCRSStructure(block_structure_->num_row_blocks(), |
| bsm.num_rows(), |
| block_structure_->first_cell_in_row_block(), |
| block_structure_->cells(), |
| block_structure_->row_blocks(), |
| block_structure_->col_blocks(), |
| crs_matrix_->mutable_rows(), |
| crs_matrix_->mutable_cols(), |
| context->DefaultStream()); |
| is_crs_compatible_ = block_structure_->IsCrsCompatible(); |
| // if matrix is crs-compatible - we can drop block-structure and don't need |
| // streamed_buffer_ |
| if (is_crs_compatible_) { |
| VLOG(3) << "Block-sparse matrix is compatible with CRS, discarding " |
| "block-structure"; |
| block_structure_ = nullptr; |
| } else { |
| streamed_buffer_ = std::make_unique<CudaStreamedBuffer<double>>( |
| context_, kMaxTemporaryArraySize); |
| } |
| UpdateValues(bsm); |
| } |
| |
| void CudaBlockSparseCRSView::UpdateValues(const BlockSparseMatrix& bsm) { |
| if (is_crs_compatible_) { |
| // Values of CRS-compatible matrices can be copied as-is |
| CHECK_EQ(cudaSuccess, |
| cudaMemcpyAsync(crs_matrix_->mutable_values(), |
| bsm.values(), |
| bsm.num_nonzeros() * sizeof(double), |
| cudaMemcpyHostToDevice, |
| context_->DefaultStream())); |
| return; |
| } |
| streamed_buffer_->CopyToGpu( |
| bsm.values(), |
| bsm.num_nonzeros(), |
| [bs = block_structure_.get(), crs = crs_matrix_.get()]( |
| const double* values, int num_values, int offset, auto stream) { |
| PermuteToCRS(offset, |
| num_values, |
| bs->num_row_blocks(), |
| bs->first_cell_in_row_block(), |
| bs->cells(), |
| bs->row_blocks(), |
| bs->col_blocks(), |
| crs->rows(), |
| values, |
| crs->mutable_values(), |
| stream); |
| }); |
| } |
| |
| } // namespace ceres::internal |
| #endif // CERES_NO_CUDA |