experiments/STT-tensorflow
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[XLA:GPU] Remove unused Thunk::ShouldBlockFutureThunks function.

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PiperOrigin-RevId: 196206896
This commit is contained in:
Justin Lebar 2018-05-10 19:28:35 -07:00 committed by TensorFlower Gardener
parent 2656548f3e
commit 5a492ef9bb
2 changed files with 1 additions and 33 deletions
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24
tensorflow/compiler/xla/service/gpu/gpu_executable.cc
View File

@ -164,9 +164,6 @@ Status GpuExecutable::ExecuteThunks(
sub_streams, hlo_module_->entry_computation());
uint64 start_micros = tensorflow::Env::Default()->NowMicros();
// The next event enqueued on stream N must not run until the thunk at
// last_blocking_thunk_for_stream[N] completes.
std::map<int32, const Thunk*> last_blocking_thunk_for_stream;
std::map<const Thunk*, std::unique_ptr<se::Event>> thunk_to_finish_event;
for (Thunk* thunk : thunk_schedule_->TotalOrder()) {
TF_RETURN_IF_ERROR(thunk->Initialize(*this));
@ -179,18 +176,10 @@ Status GpuExecutable::ExecuteThunks(
stream->ThenWaitFor(FindOrDie(thunk_to_finish_event, dependency).get());
}
if (last_blocking_thunk_for_stream.count(stream_no)) {
stream->ThenWaitFor(FindOrDie(thunk_to_finish_event,
last_blocking_thunk_for_stream[stream_no])
.get());
last_blocking_thunk_for_stream.erase(stream_no);
}
// If this thunk requests it, wait for all currently-executing thunks to
// finish. This is useful e.g. if the thunk is about to perform autotuning.
if (thunk->ShouldHaltAllActivityBeforeRunning(stream)) {
TF_RETURN_IF_ERROR(main_stream->BlockHostUntilDone());
last_blocking_thunk_for_stream.clear();
}
profiler.StartOperation();
@ -198,22 +187,11 @@ Status GpuExecutable::ExecuteThunks(
<< thunk->hlo_instruction()->ToString() << " on stream "
<< stream_no;
TF_RETURN_IF_ERROR(thunk->ExecuteOnStream(buffer_allocations, stream));
if (thunk_schedule_->Depended(thunk) || thunk->ShouldBlockFutureThunks()) {
if (thunk_schedule_->Depended(thunk)) {
auto finish_event = MakeUnique<se::Event>(main_stream->parent());
finish_event->Init();
stream->ThenRecordEvent(finish_event.get());
thunk_to_finish_event[thunk] = std::move(finish_event);
if (thunk->ShouldBlockFutureThunks()) {
// Set last_blocking_thunk_for_stream on all streams other than this one
// so that all other streams will wait for this thunk to complete before
// executing any events that occur later in the total order.
for (int32 i = 0; i < sub_streams.size() + 1; ++i) {
if (i != stream_no) {
last_blocking_thunk_for_stream[i] = thunk;
}
}
}
}
profiler.FinishOperation(thunk->hlo_instruction());
}

10
tensorflow/compiler/xla/service/gpu/thunk.h
View File

@ -89,16 +89,6 @@ class Thunk {
return false;
}
// Indicates whether thunks scheduled after this one should wait for this one
// to complete before running. For example, a convolution thunk creates a
// scratch allocator, then kicks off a convolution in cudnn via the stream
// executor. When the stream executor call returns, the scratch allocator goes
// out of scope, and the scratch memory is deallocated. In this case, the
// convolution thunk needs to return true so that future thunks wait for the
// convolution thunk to avoid reusing the deallocated memory until the
// convolution thunk is done with it.
virtual bool ShouldBlockFutureThunks() { return false; }
// Execute the kernel for the thunk on the given stream. This method must be
// called after Initialize and can be called multiple times over Thunk's
// lifetime. Stream argument must be non-null.