mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 16:40:38 +08:00
Sameer Agarwal
5a30cae583
1. Add a version history 2. Update copyright years across the code base 3. Run format_all.sh 4. Update version strings from 2.1.0 to 2.2.0 in the docs and elsewhere. Change-Id: I46d8d479d54bd6002d532785e67342106e73c9ac
57 lines
2.8 KiB
C++
57 lines
2.8 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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// Author: joydeepb@cs.utexas.edu (Joydeep Biswas)
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#ifndef CERES_INTERNAL_CUDA_KERNELS_UTILS_H_
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#define CERES_INTERNAL_CUDA_KERNELS_UTILS_H_
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namespace ceres {
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namespace internal {
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// Parallel execution on CUDA device requires splitting job into blocks of a
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// fixed size. We use block-size of kCudaBlockSize for all kernels that do not
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// require any specific block size. As the CUDA Toolkit documentation says,
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// "although arbitrary in this case, is a common choice". This is determined by
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// the warp size, max block size, and multiprocessor sizes of recent GPUs. For
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// complex kernels with significant register usage and unusual memory patterns,
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// the occupancy calculator API might provide better performance. See "Occupancy
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// Calculator" under the CUDA toolkit documentation.
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constexpr int kCudaBlockSize = 256;
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// Compute number of blocks of kCudaBlockSize that span over 1-d grid with
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// dimension size. Note that 1-d grid dimension is limited by 2^31-1 in CUDA,
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// thus a signed int is used as an argument.
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inline int NumBlocksInGrid(int size) {
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return (size + kCudaBlockSize - 1) / kCudaBlockSize;
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}
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} // namespace internal
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} // namespace ceres
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#endif // CERES_INTERNAL_CUDA_KERNELS_UTILS_H_
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