// Copyright (c) 2018 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/memory/allocation/allocator.h" #include #include #include #include #include #include #include "paddle/fluid/memory/allocation/allocator_facade.h" #include "paddle/fluid/memory/allocation/allocator_strategy.h" #include "paddle/fluid/memory/allocation/auto_growth_best_fit_allocator.h" #include "paddle/fluid/memory/allocation/cpu_allocator.h" #include "paddle/fluid/memory/allocation/locked_allocator.h" #include "paddle/fluid/memory/allocation/naive_best_fit_allocator.h" #include "paddle/fluid/memory/allocation/retry_allocator.h" #include "paddle/fluid/platform/cpu_info.h" #include "paddle/fluid/platform/enforce.h" #include "paddle/fluid/platform/place.h" #ifdef PADDLE_WITH_CUDA #include "paddle/fluid/memory/allocation/cuda_allocator.h" #include "paddle/fluid/memory/allocation/pinned_allocator.h" #include "paddle/fluid/platform/cuda_device_guard.h" #include "paddle/fluid/platform/gpu_info.h" #endif DEFINE_int64( gpu_allocator_retry_time, 100, "The retry time (milliseconds) when allocator fails " "to allocate memory. No retry if this value is not greater than 0"); namespace paddle { namespace memory { namespace allocation { class AllocatorFacadePrivate { public: AllocatorFacadePrivate() { auto strategy = GetAllocatorStrategy(); switch (strategy) { case AllocatorStrategy::kNaiveBestFit: { InitNaiveBestFitCPUAllocator(); #ifdef PADDLE_WITH_CUDA for (int dev_id = 0; dev_id < platform::GetCUDADeviceCount(); ++dev_id) { InitNaiveBestFitCUDAAllocator(platform::CUDAPlace(dev_id)); } InitNaiveBestFitCUDAPinnedAllocator(); #endif break; } case AllocatorStrategy::kAutoGrowth: { InitNaiveBestFitCPUAllocator(); #ifdef PADDLE_WITH_CUDA for (int dev_id = 0; dev_id < platform::GetCUDADeviceCount(); ++dev_id) { InitAutoGrowthCUDAAllocator(platform::CUDAPlace(dev_id)); } InitNaiveBestFitCUDAPinnedAllocator(); #endif break; } default: { PADDLE_THROW("Unsupported allocator strategy: %d", static_cast(strategy)); } } InitZeroSizeAllocators(); if (FLAGS_gpu_allocator_retry_time > 0) { WrapCUDARetryAllocator(FLAGS_gpu_allocator_retry_time); } CheckAllocThreadSafe(); } inline const std::shared_ptr& GetAllocator( const platform::Place& place, size_t size) { const auto& allocators = (size > 0 ? allocators_ : zero_size_allocators_); auto iter = allocators.find(place); PADDLE_ENFORCE(iter != allocators.end(), "No such allocator for the place, %s", place); return iter->second; } private: void InitNaiveBestFitCPUAllocator() { allocators_[platform::CPUPlace()] = std::make_shared(platform::CPUPlace()); } #ifdef PADDLE_WITH_CUDA void InitNaiveBestFitCUDAPinnedAllocator() { allocators_[platform::CUDAPinnedPlace()] = std::make_shared(platform::CUDAPinnedPlace()); } void InitNaiveBestFitCUDAAllocator(platform::CUDAPlace p) { allocators_[p] = std::make_shared(p); } void InitAutoGrowthCUDAAllocator(platform::CUDAPlace p) { auto cuda_allocator = std::make_shared(p); allocators_[p] = std::make_shared( cuda_allocator, platform::GpuMinChunkSize()); } #endif class ZeroSizeAllocator : public Allocator { public: explicit ZeroSizeAllocator(platform::Place place) : place_(place) {} bool IsAllocThreadSafe() const override { return true; } protected: Allocation* AllocateImpl(size_t size) override { return new Allocation(nullptr, 0, place_); } void FreeImpl(Allocation* allocation) override { delete allocation; } private: platform::Place place_; }; void InitZeroSizeAllocators() { std::vector places; places.emplace_back(platform::CPUPlace()); #ifdef PADDLE_WITH_CUDA int device_count = platform::GetCUDADeviceCount(); for (int dev_id = 0; dev_id < device_count; ++dev_id) { places.emplace_back(platform::CUDAPlace(dev_id)); } places.emplace_back(platform::CUDAPinnedPlace()); #endif for (auto& p : places) { zero_size_allocators_[p] = std::make_shared(p); } } void CheckAllocThreadSafe() const { for (auto& pair : allocators_) { PADDLE_ENFORCE_EQ(pair.second->IsAllocThreadSafe(), true); } for (auto& pair : zero_size_allocators_) { PADDLE_ENFORCE_EQ(pair.second->IsAllocThreadSafe(), true); } } void WrapCUDARetryAllocator(size_t retry_time) { PADDLE_ENFORCE_GT(retry_time, 0, "Retry time must be larger than 0"); for (auto& pair : allocators_) { if (platform::is_gpu_place(pair.first)) { pair.second = std::make_shared(pair.second, retry_time); } } } private: std::map> allocators_; std::map> zero_size_allocators_; }; // Pimpl. Make interface clean. AllocatorFacade::AllocatorFacade() : m_(new AllocatorFacadePrivate()) {} // delete m_ may cause core dump when the destructor of python in conflict with // cpp. AllocatorFacade::~AllocatorFacade() {} AllocatorFacade& AllocatorFacade::Instance() { static AllocatorFacade instance; return instance; } std::shared_ptr AllocatorFacade::AllocShared( const platform::Place& place, size_t size) { return std::shared_ptr(Alloc(place, size)); } AllocationPtr AllocatorFacade::Alloc(const platform::Place& place, size_t size) { return m_->GetAllocator(place, size)->Allocate(size); } } // namespace allocation } // namespace memory } // namespace paddle