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Paddle/paddle/fluid/memory/allocation/thread_local_allocator.h

106 lines
3.1 KiB

// Copyright (c) 2020 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.
#pragma once
#include <memory>
#include <vector>
#include "paddle/fluid/memory/allocation/allocator.h"
#include "paddle/fluid/memory/detail/buddy_allocator.h"
#include "paddle/fluid/memory/detail/system_allocator.h"
#include "paddle/fluid/platform/gpu_info.h"
namespace paddle {
namespace memory {
namespace allocation {
class ThreadLocalAllocatorImpl;
class ThreadLocalAllocation : public Allocation {
public:
ThreadLocalAllocation(void* ptr, size_t size, platform::Place place)
: Allocation(ptr, size, place) {}
void SetThreadLocalAllocatorImpl(
std::shared_ptr<ThreadLocalAllocatorImpl> allocator) {
allocator_ = allocator;
}
std::shared_ptr<ThreadLocalAllocatorImpl> GetAllocator() {
return allocator_;
}
private:
std::shared_ptr<ThreadLocalAllocatorImpl> allocator_;
};
class ThreadLocalAllocatorImpl
: public std::enable_shared_from_this<ThreadLocalAllocatorImpl> {
public:
explicit ThreadLocalAllocatorImpl(const platform::Place& p);
ThreadLocalAllocation* AllocateImpl(size_t size);
void FreeImpl(ThreadLocalAllocation* allocation);
uint64_t ReleaseImpl();
private:
std::unique_ptr<memory::detail::BuddyAllocator> buddy_allocator_;
platform::Place place_;
};
class ThreadLocalCUDAAllocatorPool {
public:
static ThreadLocalCUDAAllocatorPool& Instance() {
static thread_local ThreadLocalCUDAAllocatorPool pool;
return pool;
}
std::shared_ptr<ThreadLocalAllocatorImpl> Get(int gpu_id);
private:
ThreadLocalCUDAAllocatorPool();
std::vector<int> devices_;
std::vector<std::unique_ptr<std::once_flag>> init_flags_;
std::vector<std::shared_ptr<ThreadLocalAllocatorImpl>> allocators_;
};
class ThreadLocalCUDAAllocator : public Allocator {
public:
explicit ThreadLocalCUDAAllocator(const platform::CUDAPlace& p)
: gpu_id_(p.device) {}
bool IsAllocThreadSafe() const override { return true; }
protected:
Allocation* AllocateImpl(size_t size) override {
return ThreadLocalCUDAAllocatorPool::Instance().Get(gpu_id_)->AllocateImpl(
size);
}
void FreeImpl(Allocation* allocation) override {
auto* tl_allocation = static_cast<ThreadLocalAllocation*>(allocation);
auto allocator_impl = tl_allocation->GetAllocator();
allocator_impl->FreeImpl(tl_allocation);
}
uint64_t ReleaseImpl(const platform::Place& p) override {
return ThreadLocalCUDAAllocatorPool::Instance().Get(gpu_id_)->ReleaseImpl();
}
private:
int gpu_id_;
};
} // namespace allocation
} // namespace memory
} // namespace paddle