/* 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" #ifdef PADDLE_WITH_CUDA #include "paddle/fluid/framework/rw_lock.h" #endif 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(); } const std::vector DeviceContextPool::GetAllDeviceContexts() const { std::vector all_device_ctx; all_device_ctx.reserve(device_contexts_.size()); for (auto& dev_ctx : device_contexts_) { all_device_ctx.emplace_back(dev_ctx.second.get()); } return all_device_ctx; } 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); } VLOG(3) << "pool start"; 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 VLOG(3) << "cpu context start"; device_contexts_.emplace( p, PtrType(new CPUDeviceContext(boost::get(p)))); #endif } else if (platform::is_gpu_place(p)) { #ifdef PADDLE_WITH_CUDA VLOG(3) << "gpu context start"; 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 VLOG(3) << "gpu pin start"; 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 } VLOG(3) << "pool finish"; } } 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) : workspace_(nullptr), workspace_len_(0), stream_(stream), place_(place) { PADDLE_ENFORCE(dynload::cudnnCreate(&cudnn_handle_)); PADDLE_ENFORCE(dynload::cudnnSetStream(cudnn_handle_, *stream_)); } cudnnHandle_t cudnn_handle() const { return cudnn_handle_; } void RunFunc(const std::function& cudnn_func, size_t required_workspace_len) { std::lock_guard lock(mtx_); if (required_workspace_len > workspace_len_) { ReallocateWorkspace(required_workspace_len); } cudnn_func(workspace_); } ~CudnnHolder() { PADDLE_ENFORCE(dynload::cudnnDestroy(cudnn_handle_)); if (workspace_ != nullptr) { paddle::memory::Free(place_, workspace_); } } private: void ReallocateWorkspace(size_t required_workspace_len) { if (required_workspace_len <= workspace_len_) { return; } if (workspace_ != nullptr) { // Maybe someone is using the current workspace PADDLE_ENFORCE(cudaStreamSynchronize(*stream_)); paddle::memory::Free(place_, workspace_); } workspace_ = paddle::memory::Alloc(place_, required_workspace_len); workspace_len_ = required_workspace_len; } cudnnHandle_t cudnn_handle_; void* workspace_; size_t workspace_len_; const cudaStream_t* stream_; // not owned; const CUDAPlace place_; std::mutex mtx_; }; 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)); } driver_version_ = GetCUDADriverVersion(place_.device); runtime_version_ = GetCUDARuntimeVersion(place_.device); LOG(INFO) << "device: " << place_.device << ", CUDA Capability: " << compute_capability_ << ", Driver Version: " << driver_version_ / 1000 << "." << (driver_version_ % 100) / 10 << ", Runtime Version: " << runtime_version_ / 1000 << "." << (runtime_version_ % 100) / 10; #ifndef _WIN32 callback_manager_.reset(new StreamCallbackManager(stream_)); #endif // NOT WIN32 } CUDADeviceContext::~CUDADeviceContext() { SetDeviceId(place_.device); Wait(); WaitStreamCallback(); 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_->cudnn_handle(); } void CUDADeviceContext::RunCudnnFuncWithWorkspace( const std::function& cudnn_func, size_t workspace_len) const { cudnn_holder_->RunFunc(cudnn_func, workspace_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_blobmap_() { p_blobmap_.reset(new BlobMap()); p_mutex_.reset(new std::mutex()); } namespace { // Current thread's id. thread_local int cur_thread_id = 0; } void set_cur_thread_id(int tid) { cur_thread_id = tid; } int get_cur_thread_id(void) { return cur_thread_id; } void MKLDNNDeviceContext::SetBlob(const std::string& name, std::shared_ptr data) const { BlobMap* pMap = p_blobmap_.get(); std::shared_ptr pBlob = nullptr; int tid = platform::get_cur_thread_id(); std::lock_guard lock(*p_mutex_.get()); // Find KeyBlob for current thread auto map_it = pMap->find(tid); if (map_it == pMap->end()) { // 1st time to set blob in current thread pBlob = std::shared_ptr(new KeyBlob()); (*pMap)[tid] = pBlob; } else { pBlob = map_it->second; } // Find Key in found (or newly created) KeyBlob auto key_it = pBlob->find(name); if (key_it == pBlob->end()) { (*pBlob)[name] = data; // create new blob } else { key_it->second = data; // set data to existing blob } // lock will be automatically released when out of scope return; } std::shared_ptr MKLDNNDeviceContext::GetBlob( const std::string& name) const { BlobMap* pMap = p_blobmap_.get(); std::shared_ptr pBlob = nullptr; int tid = platform::get_cur_thread_id(); std::lock_guard lock(*p_mutex_.get()); // Find KeyBlob for current thread firstly auto map_it = pMap->find(tid); if (map_it == pMap->end()) return nullptr; pBlob = map_it->second; // Find Blob via name auto key_it = pBlob->find(name); if (key_it == pBlob->end()) return nullptr; // lock will be automatically released when out of scope return key_it->second; } #endif } // namespace platform } // namespace paddle