/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. 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. */ #pragma once #include #include #include "paddle/memory/memcpy.h" #include "paddle/memory/memory.h" #include "paddle/platform/device_context.h" #include "paddle/platform/enforce.h" #include "paddle/platform/place.h" namespace paddle { namespace framework { /** * @brief Vector support both cpu and gpu. * host vector lifetime is same with Vector * device vector is lazily malloc and modified. */ template class Vector : public std::vector { public: /* NOTE(dzhwinter): * Data always store and modified on Host. * If the data is modified when use cuda_data interface, * You need to call the CopyFromCUDA explicitly to synchronize data. * */ enum class kDataPosition { kDataOnHost = 0, kDataOnDevice = 1, }; public: using std::vector::vector; Vector() {} Vector(const std::vector &v) : std::vector(v) {} // NOLINT virtual ~Vector() { #ifdef PADDLE_WITH_CUDA if (cuda_ptr_ != nullptr) { memory::Free(place_, static_cast(cuda_ptr_)); } #endif } T *cuda_data() { CopyToCUDA(); PADDLE_ENFORCE_NOT_NULL( cuda_ptr_, "No data or Insufficient CUDA memory to allocation"); return static_cast(cuda_ptr_); } T *data() { return std::vector::data(); } const T *data() const { return std::vector::data(); } void CopyToCUDA(); void CopyFromCUDA(); void CopyToPeer(platform::Place); private: void *cuda_ptr_ = nullptr; size_t cuda_size_ = 0; /*The DataPosition is unused now, if we want support random access from cpu and cuda, we need to overload all the vector method */ kDataPosition position_ = kDataPosition::kDataOnHost; platform::CUDAPlace place_; }; template void Vector::CopyToCUDA() { #ifdef PADDLE_WITH_CUDA if (cuda_ptr_ == nullptr) { cuda_ptr_ = memory::Alloc(place_, this->size() * sizeof(T)); } platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance(); auto *cuda_ctx = pool.GetByPlace(place_); memory::Copy(place_, static_cast(cuda_ptr_), platform::CPUPlace(), static_cast(this->data()), this->size() * sizeof(T), cuda_ctx->stream()); cuda_ctx->Wait(); cuda_size_ = this->size(); #endif } template void Vector::CopyFromCUDA() { #ifdef PADDLE_WITH_CUDA platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance(); auto *cuda_ctx = pool.GetByPlace(place_); if (cuda_ptr_ == nullptr) { LOG(WARNING) << "No uncommited cuda data."; return; } this->resize(cuda_size_); memory::Copy(platform::CPUPlace(), static_cast(this->data()), place_, static_cast(cuda_ptr_), this->size() * sizeof(T), cuda_ctx->stream()); cuda_ctx->Wait(); #endif } template void Vector::CopyToPeer(platform::Place peer_place) { if (platform::is_cpu_place(peer_place)) { return; } #ifdef PADDLE_WITH_CUDA auto *cuda_ctx = platform::DeviceContextPool::Instance().GetByPlace(place_); void *peer_cuda_ptr_ = memory::Alloc( boost::get(peer_place), this->size() * sizeof(T)); memory::Copy(boost::get(peer_place), static_cast(peer_cuda_ptr_), place_, static_cast(cuda_ptr_), this->size() * sizeof(T), cuda_ctx->stream()); cuda_ctx->Wait(); memory::Free(place_, static_cast(cuda_ptr_)); place_ = boost::get(peer_place); cuda_ptr_ = peer_cuda_ptr_; #endif } template class Vector; template class Vector; template class Vector; template class Vector; } // namespace framework } // namespace paddle