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Paddle/paddle/fluid/memory/allocation/allocator_facade.cc

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// 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 <map>
#include <vector>
#include "paddle/fluid/memory/allocation/aligned_allocator.h"
#include "paddle/fluid/memory/allocation/allocator_facade.h"
#include "paddle/fluid/memory/allocation/auto_increment_allocator.h"
#include "paddle/fluid/memory/allocation/best_fit_allocator.h"
#include "paddle/fluid/memory/allocation/conditional_allocator.h"
#include "paddle/fluid/memory/allocation/cpu_allocator.h"
#include "paddle/fluid/memory/allocation/locked_allocator.h"
#include "paddle/fluid/memory/allocation/naive_managed_allocator.h"
#include "paddle/fluid/memory/allocation/pinned_allocator.h"
#include "paddle/fluid/memory/allocation/zero_size_allocator.h"
#include "paddle/fluid/platform/cuda_device_guard.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/place.h"
#ifdef PADDLE_WITH_CUDA
#include "paddle/fluid/memory/allocation/cuda_allocator.h"
#endif
namespace paddle {
namespace memory {
namespace allocation {
// TODO(yy): Dirty code here. This class should be configurable in runtime.
class CPUManagedAllocator : public ManagedAllocator {
public:
CPUManagedAllocator()
: normal_allocator_(NaiveManagedAllocator::Create(
std::unique_ptr<Allocator>(new CPUAllocator()))),
communication_allocator_(NaiveManagedAllocator::Create(
std::unique_ptr<Allocator>(new CPUPinnedAllocator()))) {}
std::unique_ptr<Allocation> Allocate(size_t size, Attr attr) override {
if (attr == kCommunication) {
return communication_allocator_->Allocate(size, attr);
} else {
return normal_allocator_->Allocate(size, attr);
}
}
std::shared_ptr<Allocation> AllocateShared(size_t size, Attr attr) override {
if (attr == kCommunication) {
return communication_allocator_->AllocateShared(size, attr);
} else {
return normal_allocator_->AllocateShared(size, attr);
}
}
bool IsAllocThreadSafe() const override { return true; }
private:
std::shared_ptr<ManagedAllocator> normal_allocator_;
std::shared_ptr<ManagedAllocator> communication_allocator_;
};
#ifdef PADDLE_WITH_CUDA
// TODO(yy): Dirty code here. This class should be configurable in runtime.
class CUDAManagedAllocator : public ManagedAllocator {
public:
explicit CUDAManagedAllocator(int dev_id) {
platform::CUDADeviceGuard guard(dev_id);
max_chunk_size_ = platform::GpuMaxChunkSize();
raw_allocator_ = NaiveManagedAllocator::Create(std::unique_ptr<Allocator>(
new CUDAAllocator(platform::CUDAPlace(dev_id))));
default_allocator_ = std::make_shared<AutoIncrementAllocator>(
[this] { return std::move(BestFitAllocatorCreator()); });
auto* cond_allocator = new ConditionalAllocator();
cond_allocator
->AddAllocator(
[this](size_t size, Attr attr) { return size < max_chunk_size_; },
default_allocator_)
.AddAllocator(
[](size_t size, Attr attr) {
return true; // default case
},
raw_allocator_);
default_allocator_.reset(cond_allocator);
}
~CUDAManagedAllocator() {
// Specify destruct order.
default_allocator_.reset();
chunks_.clear();
raw_allocator_.reset();
}
std::unique_ptr<Allocation> Allocate(size_t size, Attr attr) override {
return default_allocator_->Allocate(size, attr);
}
std::shared_ptr<Allocation> AllocateShared(size_t size, Attr attr) override {
return default_allocator_->AllocateShared(size, attr);
}
std::shared_ptr<ManagedAllocator> BestFitAllocatorCreator() {
chunks_.emplace_back(raw_allocator_->Allocate(max_chunk_size_));
auto* allocation = chunks_.back().get();
return std::make_shared<AlignedAllocator<64u>>(
NaiveManagedAllocator::Create(
std::unique_ptr<Allocator>(new BestFitAllocator(allocation))));
}
bool IsAllocThreadSafe() const override { return true; }
private:
size_t max_chunk_size_;
std::vector<std::unique_ptr<Allocation>> chunks_;
std::shared_ptr<ManagedAllocator> raw_allocator_;
std::shared_ptr<ManagedAllocator> default_allocator_;
};
#endif
class AllocatorFacadePrivate {
public:
std::map<platform::Place, std::shared_ptr<ManagedAllocator>> allocators_;
~AllocatorFacadePrivate() = default;
AllocatorFacadePrivate() {
InitCPUAllocator();
InitCUDAAllocator();
WrapZeroSizeAllocator();
}
private:
void InitCPUAllocator() {
allocators_[platform::CPUPlace()] = std::make_shared<CPUManagedAllocator>();
}
void InitCUDAAllocator() {
#ifdef PADDLE_WITH_CUDA
for (int dev_id = 0; dev_id < platform::GetCUDADeviceCount(); ++dev_id) {
allocators_[platform::CUDAPlace(dev_id)] =
std::make_shared<CUDAManagedAllocator>(dev_id);
}
#endif
}
void WrapZeroSizeAllocator() {
for (auto& pair : allocators_) {
pair.second =
std::make_shared<ZeroSizeAllocator>(pair.second, pair.first);
}
}
};
// Pimpl. Make interface clean.
AllocatorFacade::AllocatorFacade() : m_(new AllocatorFacadePrivate()) {}
AllocatorFacade::~AllocatorFacade() { delete m_; }
AllocatorFacade& AllocatorFacade::Instance() {
static AllocatorFacade instance;
return instance;
}
std::shared_ptr<Allocation> AllocatorFacade::AllocShared(
const platform::Place& place, size_t size, Allocator::Attr attr) {
return m_->allocators_[place]->AllocateShared(size, attr);
}
std::unique_ptr<Allocation> AllocatorFacade::Alloc(const platform::Place& place,
size_t size,
Allocator::Attr attr) {
return m_->allocators_[place]->Allocate(size, attr);
}
} // namespace allocation
} // namespace memory
} // namespace paddle