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// 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.
//
// Author: vitus@google.com (Michael Vitus)
#ifndef CERES_INTERNAL_CONTEXT_IMPL_H_
#define CERES_INTERNAL_CONTEXT_IMPL_H_
// This include must come before any #ifndef check on Ceres compile options.
// clang-format off
#include "ceres/internal/config.h"
// clang-format on
#include <string>
#include "ceres/context.h"
#include "ceres/internal/disable_warnings.h"
#include "ceres/internal/export.h"
#ifndef CERES_NO_CUDA
#include "cublas_v2.h"
#include "cuda_runtime.h"
#include "cusolverDn.h"
#include "cusparse.h"
#endif // CERES_NO_CUDA
#include "ceres/thread_pool.h"
namespace ceres::internal {
class CERES_NO_EXPORT ContextImpl final : public Context {
public:
ContextImpl();
~ContextImpl() override;
ContextImpl(const ContextImpl&) = delete;
void operator=(const ContextImpl&) = delete;
// When compiled with C++ threading support, resize the thread pool to have
// at min(num_thread, num_hardware_threads) where num_hardware_threads is
// defined by the hardware. Otherwise this call is a no-op.
void EnsureMinimumThreads(int num_threads);
ThreadPool thread_pool;
#ifndef CERES_NO_CUDA
// Note on Ceres' use of CUDA Devices on multi-GPU systems:
// 1. On a multi-GPU system, if nothing special is done, the "default" CUDA
// device will be used, which is device 0.
// 2. If the user masks out GPUs using the CUDA_VISIBLE_DEVICES environment
// variable, Ceres will still use device 0 visible to the program, but
// device 0 will be the first GPU indicated in the environment variable.
// 3. If the user explicitly selects a GPU in the host process before calling
// Ceres, Ceres will use that GPU.
// Note on Ceres' use of CUDA Streams:
// Most of operations on the GPU are performed using a single stream. In
// those cases DefaultStream() should be used. This ensures that operations
// are stream-ordered, and might be concurrent with cpu processing with no
// additional efforts.
//
// a. Single-stream workloads
// - Only use default stream
// - Return control to the callee without synchronization whenever possible
// - Stream synchronization occurs only after GPU to CPU transfers, and is
// handled by CudaBuffer
//
// b. Multi-stream workloads
// Multi-stream workloads are more restricted in order to make it harder to
// get a race-condition.
// - Should always synchronize the default stream on entry
// - Should always synchronize all utilized streams on exit
// - Should not make any assumptions on one of streams_[] being default
//
// With those rules in place
// - All single-stream asynchronous workloads are serialized using default
// stream
// - Multiple-stream workloads always wait single-stream workloads to finish
// and leave no running computations on exit.
// This slightly penalizes multi-stream workloads, but makes it easier to
// avoid race conditions when multiple-stream workload depends on results of
// any preceeding gpu computations.
// Initializes cuBLAS, cuSOLVER, and cuSPARSE contexts, creates an
// asynchronous CUDA stream, and associates the stream with the contexts.
// Returns true iff initialization was successful, else it returns false and a
// human-readable error message is returned.
bool InitCuda(std::string* message);
void TearDown();
inline bool IsCudaInitialized() const { return is_cuda_initialized_; }
// Returns a human-readable string describing the capabilities of the current
// CUDA device. CudaConfigAsString can only be called after InitCuda has been
// called.
std::string CudaConfigAsString() const;
// Returns the number of bytes of available global memory on the current CUDA
// device. If it is called before InitCuda, it returns 0.
size_t GpuMemoryAvailable() const;
cusolverDnHandle_t cusolver_handle_ = nullptr;
cublasHandle_t cublas_handle_ = nullptr;
// Default stream.
// Kernel invocations and memory copies on this stream can be left without
// synchronization.
cudaStream_t DefaultStream() { return streams_[0]; }
static constexpr int kNumCudaStreams = 2;
cudaStream_t streams_[kNumCudaStreams] = {0};
cusparseHandle_t cusparse_handle_ = nullptr;
bool is_cuda_initialized_ = false;
int gpu_device_id_in_use_ = -1;
cudaDeviceProp gpu_device_properties_;
bool is_cuda_memory_pools_supported_ = false;
int cuda_version_major_ = 0;
int cuda_version_minor_ = 0;
#endif // CERES_NO_CUDA
};
} // namespace ceres::internal
#include "ceres/internal/reenable_warnings.h"
#endif // CERES_INTERNAL_CONTEXT_IMPL_H_