Permutation-based conversion from block-sparse to crs

Change-Id: Ic33a6476c033187dff61886deb6d1761524943f0
2026-08-29 16:40:38 +08:00 · 2023-05-03 20:58:35 +03:00
parent abbc4e7974
commit e7bd72d41e
22 changed files with 1618 additions and 61 deletions
@@ -0,0 +1,118 @@
+// 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_structure.h"
+
+#ifndef CERES_NO_CUDA
+
+namespace ceres::internal {
+namespace {
+// Dimension of a sorted array of blocks
+inline int Dimension(const std::vector<Block>& blocks) {
+  if (blocks.empty()) {
+    return 0;
+  }
+  const auto& last = blocks.back();
+  return last.size + last.position;
+}
+}  // namespace
+
+CudaBlockSparseStructure::CudaBlockSparseStructure(
+    const CompressedRowBlockStructure& block_structure, ContextImpl* context)
+    : row_block_offsets_(context),
+      cells_(context),
+      row_blocks_(context),
+      col_blocks_(context) {
+  // Row blocks extracted from CompressedRowBlockStructure::rows
+  std::vector<Block> row_blocks;
+  // Column blocks can be reused as-is
+  const auto& col_blocks = block_structure.cols;
+
+  // Row block offset is an index of the first cell corresponding to row block
+  std::vector<int> row_block_offsets;
+  // Flat array of all cells from all row-blocks
+  std::vector<Cell> cells;
+
+  num_row_blocks_ = block_structure.rows.size();
+  num_col_blocks_ = col_blocks.size();
+
+  row_blocks.reserve(num_row_blocks_);
+  row_block_offsets.reserve(num_row_blocks_ + 1);
+  num_nonzeros_ = 0;
+  num_cells_ = 0;
+  for (const auto& r : block_structure.rows) {
+    const int row_block_size = r.block.size;
+    row_blocks.emplace_back(r.block);
+    row_block_offsets.push_back(num_cells_);
+    for (const auto& c : r.cells) {
+      cells.emplace_back(c);
+      const int col_block_size = col_blocks[c.block_id].size;
+      num_nonzeros_ += col_block_size * row_block_size;
+      ++num_cells_;
+    }
+  }
+  row_block_offsets.push_back(num_cells_);
+
+  num_rows_ = Dimension(row_blocks);
+  num_cols_ = Dimension(col_blocks);
+
+  if (VLOG_IS_ON(3)) {
+    const size_t row_block_offsets_size =
+        row_block_offsets.size() * sizeof(int);
+    const size_t cells_size = cells.size() * sizeof(Cell);
+    const size_t row_blocks_size = row_blocks.size() * sizeof(Block);
+    const size_t col_blocks_size = col_blocks.size() * sizeof(Block);
+    const size_t total_size =
+        row_block_offsets_size + cells_size + col_blocks_size + row_blocks_size;
+    VLOG(3) << "\nCudaBlockSparseStructure:\n"
+               "\tRow block offsets: "
+            << row_block_offsets_size
+            << " bytes\n"
+               "\tColumn blocks: "
+            << col_blocks_size
+            << " bytes\n"
+               "\tRow blocks: "
+            << row_blocks_size
+            << " bytes\n"
+               "\tCells: "
+            << cells_size
+            << " bytes\n"
+               "\tTotal: "
+            << total_size << " bytes of GPU memory";
+  }
+
+  row_block_offsets_.CopyFromCpuVector(row_block_offsets);
+  cells_.CopyFromCpuVector(cells);
+  row_blocks_.CopyFromCpuVector(row_blocks);
+  col_blocks_.CopyFromCpuVector(col_blocks);
+}
+}  // namespace ceres::internal
+
+#endif  // CERES_NO_CUDA