/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/fluid/platform/device_context.h" #include #include #include #include #include "paddle/fluid/memory/memory.h" namespace paddle { namespace platform { DeviceContextPool* DeviceContextPool::pool = nullptr; platform::DeviceContext* DeviceContextPool::Get(const platform::Place& place) { auto it = device_contexts_.find(place); if (it == device_contexts_.end()) { PADDLE_THROW( "'Place' is not supported, Please re-compile with WITH_GPU " "option"); } return it->second.get(); } DeviceContextPool::DeviceContextPool( const std::vector& places) { PADDLE_ENFORCE_GT(places.size(), 0); using PtrType = std::unique_ptr; std::set set; for (auto& p : places) { set.insert(p); } for (auto& p : set) { if (platform::is_cpu_place(p)) { #ifdef PADDLE_WITH_MKLDNN device_contexts_.emplace( p, PtrType(new MKLDNNDeviceContext(boost::get(p)))); #else device_contexts_.emplace( p, PtrType(new CPUDeviceContext(boost::get(p)))); #endif } else if (platform::is_gpu_place(p)) { #ifdef PADDLE_WITH_CUDA device_contexts_.emplace( p, PtrType(new CUDADeviceContext(boost::get(p)))); #else PADDLE_THROW( "'CUDAPlace' is not supported, Please re-compile with WITH_GPU " "option"); #endif } else if (platform::is_cuda_pinned_place(p)) { #ifdef PADDLE_WITH_CUDA device_contexts_.emplace( p, PtrType(new CUDAPinnedDeviceContext(boost::get(p)))); #else PADDLE_THROW( "'CUDAPlace' is not supported, Please re-compile with WITH_GPU " "option"); #endif } } } CPUDeviceContext::CPUDeviceContext() { eigen_device_.reset(new Eigen::DefaultDevice()); } CPUDeviceContext::CPUDeviceContext(CPUPlace place) : place_(place) { eigen_device_.reset(new Eigen::DefaultDevice()); } Eigen::DefaultDevice* CPUDeviceContext::eigen_device() const { return eigen_device_.get(); } Place CPUDeviceContext::GetPlace() const { return place_; } #ifdef PADDLE_WITH_CUDA class EigenCudaStreamDevice : public Eigen::StreamInterface { public: EigenCudaStreamDevice() : scratch_(nullptr), semaphore_(nullptr) { Eigen::initializeDeviceProp(); } ~EigenCudaStreamDevice() override {} void Reinitialize(const cudaStream_t* cuda_stream, CUDAPlace place) { stream_ = cuda_stream; place_ = place; device_prop_ = &Eigen::m_deviceProperties[place.device]; } const cudaStream_t& stream() const override { return *stream_; } const cudaDeviceProp& deviceProperties() const override { return *device_prop_; } void* allocate(size_t num_bytes) const override { return paddle::memory::Alloc(place_, num_bytes); } void deallocate(void* buffer) const override { paddle::memory::Free(place_, buffer); } void* scratchpad() const override { if (scratch_ == NULL) { scratch_ = allocate(Eigen::kCudaScratchSize + sizeof(unsigned int)); } return scratch_; } unsigned int* semaphore() const override { if (semaphore_ == NULL) { char* scratch = static_cast(scratchpad()) + Eigen::kCudaScratchSize; semaphore_ = reinterpret_cast(scratch); PADDLE_ENFORCE( cudaMemsetAsync(semaphore_, 0, sizeof(unsigned int), *stream_)); } return semaphore_; } private: CUDAPlace place_; const cudaStream_t* stream_; // not owned; const cudaDeviceProp* device_prop_; // not owned; mutable void* scratch_; mutable unsigned int* semaphore_; }; class CudnnHolder { public: CudnnHolder(const cudaStream_t* stream, const CUDAPlace& place) : stream_(stream), place_(place), workspace_(nullptr), workspace_len_(0) { PADDLE_ENFORCE(dynload::cudnnCreate(&cudnn_handle_)); PADDLE_ENFORCE(dynload::cudnnSetStream(cudnn_handle_, stream_)); } cudnnHandle_t get_cudnn_handle() const { return cudnn_handle_; } void* get_workspace(size_t required_len) { if (required_len > workspace_len_) { void* new_workspace = paddle::memory::Alloc(place_, required_len); if (workspace_ != nullptr) { // Maybe someone is using the current workspace PADDLE_ENFORCE(cudaStreamSynchronize(stream_)); PADDLE_ENFORCE(cudaGetLastError()); paddle::memory::Free(place_, workspace_); } workspace_ = new_workspace; workspace_len_ = required_len; } return workspace_ } ~CudnnHolder() { PADDLE_ENFORCE(dynload::cudnnDestroy(cudnn_handle_)); } private: cudnnHandle_t cudnn_handle_; void* workspace_; size_t workspace_len_; const cudaStream_t* stream_; // not owned; const CUDAPlace place_; }; CUDADeviceContext::CUDADeviceContext(CUDAPlace place) : place_(place), cudnn_holder_(nullptr) { SetDeviceId(place_.device); compute_capability = GetCUDAComputeCapability(place_.device); multi_process = GetCUDAMultiProcessors(place_.device); max_threads_per_mp = GetCUDAMaxThreadsPerMultiProcessor(place_.device); PADDLE_ENFORCE(cudaStreamCreate(&stream_)); eigen_stream_.reset(new EigenCudaStreamDevice()); eigen_stream_->Reinitialize(&stream_, place); eigen_device_.reset(new Eigen::GpuDevice(eigen_stream_.get())); PADDLE_ENFORCE(dynload::cublasCreate(&cublas_handle_)); PADDLE_ENFORCE(dynload::cublasSetStream(cublas_handle_, stream_)); if (dynload::HasCUDNN()) { cudnn_holder_.reset(new CudnnHolder(&stream_, place)); } } CUDADeviceContext::~CUDADeviceContext() { SetDeviceId(place_.device); Wait(); PADDLE_ENFORCE(dynload::cublasDestroy(cublas_handle_)); eigen_stream_.reset(); eigen_device_.reset(); PADDLE_ENFORCE(cudaStreamDestroy(stream_)); } Place CUDADeviceContext::GetPlace() const { return place_; } void CUDADeviceContext::Wait() const { PADDLE_ENFORCE(cudaStreamSynchronize(stream_)); PADDLE_ENFORCE(cudaGetLastError()); } int CUDADeviceContext::GetComputeCapability() const { return compute_capability; } int CUDADeviceContext::GetMaxPhysicalThreadCount() const { return multi_process * max_threads_per_mp; } Eigen::GpuDevice* CUDADeviceContext::eigen_device() const { return eigen_device_.get(); } cublasHandle_t CUDADeviceContext::cublas_handle() const { return cublas_handle_; } cudnnHandle_t CUDADeviceContext::cudnn_handle() const { return cudnn_holder_->get_cudnn_handle(); } void* cudnn_workspace(size_t required_len) const { return cudnn_holder_->get_workspace(required_len); } cudaStream_t CUDADeviceContext::stream() const { return stream_; } CUDAPinnedDeviceContext::CUDAPinnedDeviceContext() { eigen_device_.reset(new Eigen::DefaultDevice()); } CUDAPinnedDeviceContext::CUDAPinnedDeviceContext(CUDAPinnedPlace place) : place_(place) { eigen_device_.reset(new Eigen::DefaultDevice()); } Eigen::DefaultDevice* CUDAPinnedDeviceContext::eigen_device() const { return eigen_device_.get(); } Place CUDAPinnedDeviceContext::GetPlace() const { return place_; } #endif #ifdef PADDLE_WITH_MKLDNN MKLDNNDeviceContext::MKLDNNDeviceContext(CPUPlace place) : CPUDeviceContext(place), engine_(mkldnn::engine::cpu, 0), p_blobs_() { p_blobs_.reset(new std::unordered_map>()); } void MKLDNNDeviceContext::SetBlob(const std::string& name, std::shared_ptr data) const { std::unordered_map>* p; p = p_blobs_.get(); auto it = p->find(name); if (it == p->end()) { (*p)[name] = data; // create new blob } else { it->second = data; // set data to existing blob } return; } std::shared_ptr MKLDNNDeviceContext::GetBlob( const std::string& name) const { std::unordered_map>* p; p = p_blobs_.get(); auto it = p->find(name); if (it != p->end()) { return it->second; } return nullptr; } #endif } // namespace platform } // namespace paddle