Merge pull request #14791 from Yancey1989/parallel_graph_mode
[Feature] Add ParallelGraph executor mode in parallelexecutor to improve performancerevert-15207-remove_op_handle_lock_and_fix_var
Yan Xu
6 years ago
committed by
GitHub
commit
a1e60ab19b
@ -0,0 +1,99 @@
|
||||
// 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/framework/details/parallel_ssa_graph_executor.h"
|
||||
|
||||
namespace paddle {
|
||||
namespace framework {
|
||||
namespace details {
|
||||
|
||||
ParallelSSAGraphExecutor::ParallelSSAGraphExecutor(
|
||||
const ExecutionStrategy &strategy, const std::vector<Scope *> &local_scopes,
|
||||
const std::vector<platform::Place> &places,
|
||||
std::vector<std::unique_ptr<ir::Graph>> &&graphs)
|
||||
: strategy_(std::move(strategy)),
|
||||
local_scopes_(std::move(local_scopes)),
|
||||
pool_(places.size() >= 2 ? new ::ThreadPool(places.size()) : nullptr),
|
||||
places_(std::move(places)),
|
||||
graphs_(std::move(graphs)) {
|
||||
PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size());
|
||||
|
||||
// set the correct size of thread pool to each device.
|
||||
strategy_.num_threads_ = strategy_.num_threads_ < places_.size()
|
||||
? 1UL
|
||||
: strategy_.num_threads_ / places_.size();
|
||||
VLOG(1) << "set num_threads: " << strategy_.num_threads_
|
||||
<< " to run the operators of the graph on each device.";
|
||||
for (size_t i = 0; i < places.size(); ++i) {
|
||||
executors_.emplace_back(new details::ThreadedSSAGraphExecutor(
|
||||
strategy_, {local_scopes_[i]}, {places_[i]}, std::move(graphs_[i])));
|
||||
}
|
||||
}
|
||||
|
||||
FeedFetchList ParallelSSAGraphExecutor::Run(
|
||||
const std::vector<std::string> &fetch_tensors) {
|
||||
std::vector<std::future<FeedFetchList>> run_futures;
|
||||
|
||||
std::vector<FeedFetchList> fetch_data;
|
||||
FeedFetchList ret;
|
||||
|
||||
fetch_data.reserve(places_.size());
|
||||
ret.reserve(fetch_tensors.size());
|
||||
exception_holder_.Clear();
|
||||
|
||||
for (size_t i = 0; i < places_.size(); ++i) {
|
||||
auto call = [this, i, &fetch_tensors]() -> FeedFetchList {
|
||||
try {
|
||||
return executors_[i]->Run(fetch_tensors);
|
||||
} catch (...) {
|
||||
exception_holder_.Catch(std::current_exception());
|
||||
}
|
||||
return FeedFetchList();
|
||||
};
|
||||
|
||||
if (pool_) {
|
||||
run_futures.emplace_back(pool_->enqueue(std::move(call)));
|
||||
} else {
|
||||
fetch_data.emplace_back(std::move(call()));
|
||||
}
|
||||
}
|
||||
|
||||
if (pool_) {
|
||||
for (auto &f : run_futures) {
|
||||
if (exception_holder_.IsCaught()) {
|
||||
f.wait();
|
||||
} else {
|
||||
fetch_data.emplace_back(std::move(f.get()));
|
||||
}
|
||||
}
|
||||
}
|
||||
if (exception_holder_.IsCaught()) {
|
||||
exception_holder_.ReThrow();
|
||||
}
|
||||
|
||||
for (size_t fetch_idx = 0; fetch_idx < fetch_tensors.size(); ++fetch_idx) {
|
||||
std::vector<const LoDTensor *> lodtensor_ptrs;
|
||||
lodtensor_ptrs.reserve(local_scopes_.size());
|
||||
for (size_t scope_idx = 0; scope_idx < local_scopes_.size(); ++scope_idx) {
|
||||
lodtensor_ptrs.push_back(&fetch_data.at(scope_idx).at(fetch_idx));
|
||||
}
|
||||
ret.emplace_back();
|
||||
ret.back().MergeLoDTensor(lodtensor_ptrs, platform::CPUPlace());
|
||||
}
|
||||
return ret;
|
||||
}
|
||||
|
||||
} // namespace details
|
||||
} // namespace framework
|
||||
} // namespace paddle
|
||||
@ -0,0 +1,51 @@
|
||||
// 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.
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <string>
|
||||
#include <vector>
|
||||
|
||||
#include "ThreadPool.h"
|
||||
#include "paddle/fluid/framework/details/threaded_ssa_graph_executor.h"
|
||||
|
||||
namespace paddle {
|
||||
namespace framework {
|
||||
namespace details {
|
||||
|
||||
class ParallelSSAGraphExecutor : public SSAGraphExecutor {
|
||||
public:
|
||||
ParallelSSAGraphExecutor(const ExecutionStrategy &strategy,
|
||||
const std::vector<Scope *> &local_scopes,
|
||||
const std::vector<platform::Place> &places,
|
||||
std::vector<std::unique_ptr<ir::Graph>> &&graphs);
|
||||
~ParallelSSAGraphExecutor() final = default;
|
||||
const ir::Graph &Graph() const override { return *graphs_[0]; }
|
||||
|
||||
FeedFetchList Run(const std::vector<std::string> &fetch_tensors) override;
|
||||
|
||||
private:
|
||||
ExecutionStrategy strategy_;
|
||||
std::vector<Scope *> local_scopes_;
|
||||
std::unique_ptr<::ThreadPool> pool_{nullptr};
|
||||
std::vector<platform::Place> places_;
|
||||
std::vector<std::unique_ptr<ir::Graph>> graphs_;
|
||||
|
||||
std::vector<std::unique_ptr<details::ThreadedSSAGraphExecutor>> executors_;
|
||||
ExceptionHolder exception_holder_;
|
||||
};
|
||||
|
||||
} // namespace details
|
||||
} // namespace framework
|
||||
} // namespace paddle
|
||||
Loading…
Reference in new issue