| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2018 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) |
| |
| #include "ceres/context_impl.h" |
| |
| #include <string> |
| |
| #include "ceres/internal/config.h" |
| #include "ceres/stringprintf.h" |
| #include "ceres/wall_time.h" |
| |
| #ifndef CERES_NO_CUDA |
| #include "cublas_v2.h" |
| #include "cuda_runtime.h" |
| #include "cusolverDn.h" |
| #endif // CERES_NO_CUDA |
| |
| namespace ceres::internal { |
| |
| ContextImpl::ContextImpl() = default; |
| |
| #ifndef CERES_NO_CUDA |
| void ContextImpl::TearDown() { |
| if (cusolver_handle_ != nullptr) { |
| cusolverDnDestroy(cusolver_handle_); |
| cusolver_handle_ = nullptr; |
| } |
| if (cublas_handle_ != nullptr) { |
| cublasDestroy(cublas_handle_); |
| cublas_handle_ = nullptr; |
| } |
| if (cusolver_handle_ != nullptr) { |
| cusparseDestroy(cusparse_handle_); |
| cusparse_handle_ = nullptr; |
| } |
| if (stream_ != nullptr) { |
| cudaStreamDestroy(stream_); |
| stream_ = nullptr; |
| } |
| is_cuda_initialized_ = false; |
| } |
| |
| std::string ContextImpl::CudaConfigAsString() const { |
| return ceres::internal::StringPrintf( |
| "======================= CUDA Device Properties ======================\n" |
| "Cuda version : %d.%d\n" |
| "Device ID : %d\n" |
| "Device name : %s\n" |
| "Total GPU memory : %6.f MiB\n" |
| "GPU memory available : %6.f MiB\n" |
| "Compute capability : %d.%d\n" |
| "Warp size : %d\n" |
| "Max threads per block: %d\n" |
| "Max threads per dim : %d %d %d\n" |
| "Max grid size : %d %d %d\n" |
| "Multiprocessor count : %d\n" |
| "====================================================================", |
| cuda_version_major_, |
| cuda_version_minor_, |
| gpu_device_id_in_use_, |
| gpu_device_properties_.name, |
| gpu_device_properties_.totalGlobalMem / 1024.0 / 1024.0, |
| GpuMemoryAvailable() / 1024.0 / 1024.0, |
| gpu_device_properties_.major, |
| gpu_device_properties_.minor, |
| gpu_device_properties_.warpSize, |
| gpu_device_properties_.maxThreadsPerBlock, |
| gpu_device_properties_.maxThreadsDim[0], |
| gpu_device_properties_.maxThreadsDim[1], |
| gpu_device_properties_.maxThreadsDim[2], |
| gpu_device_properties_.maxGridSize[0], |
| gpu_device_properties_.maxGridSize[1], |
| gpu_device_properties_.maxGridSize[2], |
| gpu_device_properties_.multiProcessorCount); |
| } |
| |
| size_t ContextImpl::GpuMemoryAvailable() const { |
| size_t free, total; |
| cudaMemGetInfo(&free, &total); |
| return free; |
| } |
| |
| bool ContextImpl::InitCuda(std::string* message) { |
| if (is_cuda_initialized_) { |
| return true; |
| } |
| CHECK_EQ(cudaGetDevice(&gpu_device_id_in_use_), cudaSuccess); |
| int cuda_version; |
| CHECK_EQ(cudaRuntimeGetVersion(&cuda_version), cudaSuccess); |
| cuda_version_major_ = cuda_version / 1000; |
| cuda_version_minor_ = (cuda_version % 1000) / 10; |
| CHECK_EQ(cudaGetDeviceProperties(&gpu_device_properties_, |
| gpu_device_id_in_use_), cudaSuccess); |
| VLOG(3) << "\n" << CudaConfigAsString(); |
| EventLogger event_logger("InitCuda"); |
| if (cublasCreate(&cublas_handle_) != CUBLAS_STATUS_SUCCESS) { |
| *message = "CUDA initialization failed because " |
| "cuBLAS::cublasCreate failed."; |
| cublas_handle_ = nullptr; |
| return false; |
| } |
| event_logger.AddEvent("cublasCreate"); |
| if (cusolverDnCreate(&cusolver_handle_) != CUSOLVER_STATUS_SUCCESS) { |
| *message = "CUDA initialization failed because " |
| "cuSolverDN::cusolverDnCreate failed."; |
| TearDown(); |
| return false; |
| } |
| event_logger.AddEvent("cusolverDnCreate"); |
| if (cusparseCreate(&cusparse_handle_) != CUSPARSE_STATUS_SUCCESS) { |
| *message = "CUDA initialization failed because " |
| "cuSPARSE::cusparseCreate failed."; |
| TearDown(); |
| return false; |
| } |
| event_logger.AddEvent("cusparseCreate"); |
| if (cudaStreamCreateWithFlags(&stream_, cudaStreamNonBlocking) != |
| cudaSuccess) { |
| *message = "CUDA initialization failed because " |
| "CUDA::cudaStreamCreateWithFlags failed."; |
| TearDown(); |
| return false; |
| } |
| event_logger.AddEvent("cudaStreamCreateWithFlags"); |
| if (cusolverDnSetStream(cusolver_handle_, stream_) != |
| CUSOLVER_STATUS_SUCCESS || |
| cublasSetStream(cublas_handle_, stream_) != CUBLAS_STATUS_SUCCESS || |
| cusparseSetStream(cusparse_handle_, stream_) != CUSPARSE_STATUS_SUCCESS) { |
| *message = "CUDA initialization failed because SetStream failed."; |
| TearDown(); |
| return false; |
| } |
| event_logger.AddEvent("SetStream"); |
| is_cuda_initialized_ = true; |
| return true; |
| } |
| #endif // CERES_NO_CUDA |
| |
| ContextImpl::~ContextImpl() { |
| #ifndef CERES_NO_CUDA |
| TearDown(); |
| #endif // CERES_NO_CUDA |
| } |
| void ContextImpl::EnsureMinimumThreads(int num_threads) { |
| #ifdef CERES_USE_CXX_THREADS |
| thread_pool.Resize(num_threads); |
| #endif // CERES_USE_CXX_THREADS |
| } |
| } // namespace ceres::internal |