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https://github.com/ceres-solver/ceres-solver.git
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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
173 lines
6.6 KiB
C++
173 lines
6.6 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_BUFFER_H_
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#define CERES_INTERNAL_CUDA_BUFFER_H_
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#include "ceres/context_impl.h"
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#include "ceres/internal/config.h"
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#ifndef CERES_NO_CUDA
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#include <vector>
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#include "cuda_runtime.h"
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#include "glog/logging.h"
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namespace ceres::internal {
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// An encapsulated buffer to maintain GPU memory, and handle transfers between
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// GPU and system memory. It is the responsibility of the user to ensure that
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// the appropriate GPU device is selected before each subroutine is called. This
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// is particularly important when using multiple GPU devices on different CPU
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// threads, since active Cuda devices are determined by the cuda runtime on a
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// per-thread basis.
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template <typename T>
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class CudaBuffer {
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public:
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explicit CudaBuffer(ContextImpl* context) : context_(context) {}
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CudaBuffer(ContextImpl* context, int size) : context_(context) {
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Reserve(size);
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}
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CudaBuffer(CudaBuffer&& other)
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: data_(other.data_), size_(other.size_), context_(other.context_) {
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other.data_ = nullptr;
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other.size_ = 0;
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}
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CudaBuffer(const CudaBuffer&) = delete;
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CudaBuffer& operator=(const CudaBuffer&) = delete;
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~CudaBuffer() {
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if (data_ != nullptr) {
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CHECK_EQ(cudaFree(data_), cudaSuccess);
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}
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}
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// Grow the GPU memory buffer if needed to accommodate data of the specified
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// size
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void Reserve(const size_t size) {
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if (size > size_) {
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if (data_ != nullptr) {
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CHECK_EQ(cudaFree(data_), cudaSuccess);
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}
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CHECK_EQ(cudaMalloc(&data_, size * sizeof(T)), cudaSuccess)
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<< "Failed to allocate " << size * sizeof(T)
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<< " bytes of GPU memory";
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size_ = size;
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}
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}
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// Perform an asynchronous copy from CPU memory to GPU memory managed by this
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// CudaBuffer instance using the stream provided.
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void CopyFromCpu(const T* data, const size_t size) {
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Reserve(size);
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CHECK_EQ(cudaMemcpyAsync(data_,
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data,
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size * sizeof(T),
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cudaMemcpyHostToDevice,
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context_->DefaultStream()),
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cudaSuccess);
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}
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// Perform an asynchronous copy from a vector in CPU memory to GPU memory
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// managed by this CudaBuffer instance.
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void CopyFromCpuVector(const std::vector<T>& data) {
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Reserve(data.size());
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CHECK_EQ(cudaMemcpyAsync(data_,
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data.data(),
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data.size() * sizeof(T),
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cudaMemcpyHostToDevice,
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context_->DefaultStream()),
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cudaSuccess);
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}
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// Perform an asynchronous copy from another GPU memory array to the GPU
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// memory managed by this CudaBuffer instance using the stream provided.
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void CopyFromGPUArray(const T* data, const size_t size) {
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Reserve(size);
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CHECK_EQ(cudaMemcpyAsync(data_,
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data,
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size * sizeof(T),
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cudaMemcpyDeviceToDevice,
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context_->DefaultStream()),
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cudaSuccess);
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}
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// Copy data from the GPU memory managed by this CudaBuffer instance to CPU
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// memory. It is the caller's responsibility to ensure that the CPU memory
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// pointer is valid, i.e. it is not null, and that it points to memory of
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// at least this->size() size. This method ensures all previously dispatched
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// GPU operations on the specified stream have completed before copying the
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// data to CPU memory.
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void CopyToCpu(T* data, const size_t size) const {
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CHECK(data_ != nullptr);
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CHECK_EQ(cudaMemcpyAsync(data,
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data_,
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size * sizeof(T),
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cudaMemcpyDeviceToHost,
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context_->DefaultStream()),
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cudaSuccess);
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CHECK_EQ(cudaStreamSynchronize(context_->DefaultStream()), cudaSuccess);
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}
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// Copy N items from another GPU memory array to the GPU memory managed by
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// this CudaBuffer instance, growing this buffer's size if needed. This copy
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// is asynchronous, and operates on the stream provided.
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void CopyNItemsFrom(int n, const CudaBuffer<T>& other) {
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Reserve(n);
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CHECK(other.data_ != nullptr);
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CHECK(data_ != nullptr);
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CHECK_EQ(cudaMemcpyAsync(data_,
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other.data_,
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size_ * sizeof(T),
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cudaMemcpyDeviceToDevice,
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context_->DefaultStream()),
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cudaSuccess);
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}
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// Return a pointer to the GPU memory managed by this CudaBuffer instance.
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T* data() { return data_; }
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const T* data() const { return data_; }
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// Return the number of items of type T that can fit in the GPU memory
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// allocated so far by this CudaBuffer instance.
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size_t size() const { return size_; }
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private:
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T* data_ = nullptr;
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size_t size_ = 0;
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ContextImpl* context_ = nullptr;
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};
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} // namespace ceres::internal
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#endif // CERES_NO_CUDA
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#endif // CERES_INTERNAL_CUDA_BUFFER_H_
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