mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 08:34:37 +08:00
Sameer Agarwal
106 lines
4.4 KiB
C++
106 lines
4.4 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2023 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Authors: dmitriy.korchemkin@gmail.com (Dmitriy Korchemkin)
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#include "ceres/cuda_block_sparse_crs_view.h"
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#ifndef CERES_NO_CUDA
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#include "absl/log/check.h"
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#include "absl/log/log.h"
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#include "ceres/cuda_kernels_bsm_to_crs.h"
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namespace ceres::internal {
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CudaBlockSparseCRSView::CudaBlockSparseCRSView(const BlockSparseMatrix& bsm,
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ContextImpl* context)
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: context_(context) {
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block_structure_ = std::make_unique<CudaBlockSparseStructure>(
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*bsm.block_structure(), context);
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CudaBuffer<int32_t> rows(context, bsm.num_rows() + 1);
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CudaBuffer<int32_t> cols(context, bsm.num_nonzeros());
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FillCRSStructure(block_structure_->num_row_blocks(),
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bsm.num_rows(),
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block_structure_->first_cell_in_row_block(),
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block_structure_->cells(),
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block_structure_->row_blocks(),
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block_structure_->col_blocks(),
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rows.data(),
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cols.data(),
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context->DefaultStream(),
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context->is_cuda_memory_pools_supported_);
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is_crs_compatible_ = block_structure_->IsCrsCompatible();
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// if matrix is crs-compatible - we can drop block-structure and don't need
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// streamed_buffer_
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if (is_crs_compatible_) {
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VLOG(3) << "Block-sparse matrix is compatible with CRS, discarding "
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"block-structure";
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block_structure_ = nullptr;
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} else {
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streamed_buffer_ = std::make_unique<CudaStreamedBuffer<double>>(
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context_, kMaxTemporaryArraySize);
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}
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crs_matrix_ = std::make_unique<CudaSparseMatrix>(
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bsm.num_cols(), std::move(rows), std::move(cols), context);
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UpdateValues(bsm);
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}
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void CudaBlockSparseCRSView::UpdateValues(const BlockSparseMatrix& bsm) {
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if (is_crs_compatible_) {
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// Values of CRS-compatible matrices can be copied as-is
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CHECK_EQ(cudaSuccess,
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cudaMemcpyAsync(crs_matrix_->mutable_values(),
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bsm.values(),
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bsm.num_nonzeros() * sizeof(double),
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cudaMemcpyHostToDevice,
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context_->DefaultStream()));
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return;
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}
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streamed_buffer_->CopyToGpu(
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bsm.values(),
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bsm.num_nonzeros(),
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[bs = block_structure_.get(), crs = crs_matrix_.get()](
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const double* values, int num_values, int offset, auto stream) {
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PermuteToCRS(offset,
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num_values,
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bs->num_row_blocks(),
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bs->first_cell_in_row_block(),
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bs->cells(),
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bs->row_blocks(),
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bs->col_blocks(),
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crs->rows(),
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values,
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crs->mutable_values(),
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stream);
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});
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}
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} // namespace ceres::internal
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#endif // CERES_NO_CUDA
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