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| Original file line number | Diff line number | Diff line change |
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| // Copyright (c) 2024 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/distributed/collective/async_load.h" | ||
| #include "paddle/phi/common/memory_utils.h" | ||
|
|
||
| namespace paddle { | ||
| namespace distributed { | ||
|
|
||
| AsyncLoad::Task::Task(const Place& place) | ||
| : load_event_(place, platform::GenerateDeviceEventFlag()), | ||
| task_place_(place) {} | ||
|
|
||
| AsyncLoad::Task::~Task() {} | ||
|
|
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| bool AsyncLoad::Task::IsCompleted() { return load_event_.Query(); } | ||
|
|
||
| void AsyncLoad::Task::Synchronize() { | ||
| const auto* calc_ctx = | ||
| platform::DeviceContextPool::Instance().Get(task_place_); | ||
| load_event_.Wait(platform::Place2DeviceType(task_place_), calc_ctx); | ||
| } | ||
|
|
||
| void AsyncLoad::Task::UpdateWaitChain(const phi::DeviceContext& ctx) { | ||
| load_event_.Record(&ctx); | ||
| } | ||
|
|
||
| std::shared_ptr<AsyncLoad::Task> AsyncLoad::CreateTask(const Place& place) { | ||
| return std::make_shared<AsyncLoad::Task>(place); | ||
| } | ||
|
|
||
| void AsyncLoad::SyncCalcuStream(const Place& place, | ||
| phi::GPUContext* ctx, | ||
| platform::DeviceEvent& calc_event) { // NOLINT | ||
| const auto* calc_ctx = static_cast<phi::GPUContext*>( | ||
| platform::DeviceContextPool::Instance().Get(place)); | ||
| calc_event.Record(calc_ctx); | ||
| calc_event.Wait(platform::Place2DeviceType(place), ctx); | ||
| } | ||
|
|
||
| std::shared_ptr<AsyncLoad::Task> AsyncLoad::Offload( | ||
| phi::DenseTensor* dst, const phi::DenseTensor& src) { | ||
| // GPU -> GPUPinned | ||
| const auto& place = src.place(); | ||
|
|
||
| PADDLE_ENFORCE_EQ( | ||
| platform::is_gpu_place(place), | ||
| true, | ||
| platform::errors::InvalidArgument( | ||
| "AsyncLoad::Offload only support GPU -> GPUPinned now.")); | ||
|
|
||
| dst->Resize(src.dims()); | ||
| auto size = src.numel() * phi::SizeOf(src.dtype()); | ||
| auto* dev_ctx = static_cast<phi::GPUContext*>( | ||
| platform::DeviceContextPool::Instance().Get(place)); | ||
| auto* dst_ptr = dev_ctx->Alloc(dst, src.dtype(), size, true); | ||
| auto* src_ptr = src.data(); | ||
|
|
||
| // 1. wait calc stream to finish | ||
| std::string key = "load"; | ||
|
|
||
| if (!is_initialized_) { | ||
| is_initialized_ = true; | ||
| gpu_place_ = place; | ||
| place_to_calc_event_.emplace( | ||
| key, platform::DeviceEvent(place, platform::GenerateDeviceEventFlag())); | ||
| load_ctx_ = std::move(std::make_unique<phi::GPUContext>(place)); | ||
| } | ||
| SyncCalcuStream(gpu_place_, load_ctx_.get(), place_to_calc_event_.at(key)); | ||
|
|
||
| // 2. copy data from src to dst | ||
| auto stream = load_ctx_->stream(); | ||
| phi::memory_utils::Copy( | ||
| dst->place(), dst_ptr, src.place(), src_ptr, size, stream); | ||
|
|
||
| // 3. record event on offload stream | ||
| auto task = CreateTask(place); | ||
| task->UpdateWaitChain(*load_ctx_); | ||
| return task; | ||
| } | ||
|
|
||
| std::shared_ptr<AsyncLoad::Task> AsyncLoad::Reload( | ||
| phi::DenseTensor* dst, const phi::DenseTensor& src) { | ||
| // GPUPinned -> GPU | ||
| const auto& place = src.place(); | ||
| PADDLE_ENFORCE_EQ( | ||
| platform::is_cuda_pinned_place(place), | ||
| true, | ||
| platform::errors::InvalidArgument( | ||
| "AsyncLoad::Reload only support GPUPinned -> GPU now.")); | ||
|
|
||
| PADDLE_ENFORCE_EQ(is_initialized_, | ||
| true, | ||
| platform::errors::PreconditionNotMet( | ||
| "You should call Offload before Reload.")); | ||
|
|
||
| auto* dev_ctx = static_cast<phi::GPUContext*>( | ||
| platform::DeviceContextPool::Instance().Get(gpu_place_)); | ||
|
|
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| dst->Resize(src.dims()); | ||
| auto size = src.numel() * phi::SizeOf(src.dtype()); | ||
| auto* dst_ptr = dev_ctx->Alloc(dst, src.dtype(), size, false); | ||
| auto* src_ptr = src.data(); | ||
|
|
||
| // 1. wait calc stream to finish | ||
| std::string key = "load"; | ||
|
|
||
| SyncCalcuStream(gpu_place_, load_ctx_.get(), place_to_calc_event_.at(key)); | ||
|
|
||
| // 2. copy data from src to dst | ||
| auto stream = load_ctx_->stream(); | ||
| phi::memory_utils::Copy( | ||
| dst->place(), dst_ptr, src.place(), src_ptr, size, stream); | ||
|
|
||
| // 3. record event on offload stream | ||
| auto task = CreateTask(gpu_place_); | ||
| task->UpdateWaitChain(*load_ctx_); | ||
| return task; | ||
| } | ||
|
|
||
| } // namespace distributed | ||
| } // namespace paddle |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,70 @@ | ||
| // Copyright (c) 2023 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 | ||
|
|
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| #include <chrono> | ||
| #include <memory> | ||
| #include <string> | ||
| #include <unordered_map> | ||
| #include <vector> | ||
|
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| #include "paddle/common/enforce.h" | ||
| #include "paddle/common/errors.h" | ||
| #include "paddle/fluid/platform/device_event_base.h" | ||
| #include "paddle/phi/core/dense_tensor.h" | ||
| #include "paddle/phi/core/device_context.h" | ||
| #include "paddle/phi/core/tensor_utils.h" | ||
|
|
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| namespace paddle { | ||
| namespace distributed { | ||
|
|
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| using Place = phi::Place; | ||
|
|
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| class AsyncLoad { | ||
| public: | ||
| class Task { | ||
| public: | ||
| explicit Task(const Place& place); | ||
| virtual ~Task(); | ||
| bool IsCompleted(); | ||
| void Synchronize(); | ||
| void UpdateWaitChain(const phi::DeviceContext& ctx); | ||
|
|
||
| private: | ||
| platform::DeviceEvent load_event_; // event on offload stream | ||
| Place task_place_; | ||
| }; | ||
|
|
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| std::shared_ptr<AsyncLoad::Task> Offload(phi::DenseTensor* dst, | ||
| const phi::DenseTensor& src); | ||
|
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| void PrepareLoadEnv(const std::string& key, const Place& place); | ||
| void SyncCalcuStream(const Place& place, | ||
| phi::GPUContext* ctx, | ||
| platform::DeviceEvent& calc_event); // NOLINT | ||
| std::shared_ptr<AsyncLoad::Task> Reload(phi::DenseTensor* dst, | ||
| const phi::DenseTensor& src); | ||
|
|
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| private: | ||
| std::unordered_map<std::string, platform::DeviceEvent> | ||
| place_to_calc_event_; // event on calc stream | ||
| bool is_initialized_{false}; | ||
| std::unique_ptr<phi::GPUContext> load_ctx_; | ||
| Place gpu_place_; | ||
| std::shared_ptr<AsyncLoad::Task> CreateTask(const Place& place); | ||
| }; | ||
|
|
||
| } // namespace distributed | ||
| } // namespace paddle |
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