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author | A. Unique TensorFlower <gardener@tensorflow.org> | 2018-07-09 01:49:04 -0700 |
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committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-07-09 01:54:33 -0700 |
commit | 955e356e4c69d3fce4ac2bac5966671e964f9627 (patch) | |
tree | 95183ec6d5122e5dae704b8a80796f01dfa1b85a /tensorflow/stream_executor/event.h | |
parent | caf711b6be448d46354e0cbef23989fa837efcf7 (diff) |
[SE,XLA] Switch to using multiple streams in xla_device_context
Instead of having one stream for compute, host-to-device and device-to-host transfers, switch to having separate streams, just like the GPU does.
Add a se::Event field to XlaTensor to allow accurate inter-stream dependencies to be created.
As part of this:
- Fix TransferManager::TransferLiteralFrom/ToDevice to correctly make generated substreams wait on their master stream.
- Fix Stream::BlockHostUntilDone() to not block on or return substreams. This behavior is completely broken and not only nondeterministically returns substreams to the pool but causes indefinite hangs with the HostStream.
PiperOrigin-RevId: 203726543
Diffstat (limited to 'tensorflow/stream_executor/event.h')
-rw-r--r-- | tensorflow/stream_executor/event.h | 3 |
1 files changed, 3 insertions, 0 deletions
diff --git a/tensorflow/stream_executor/event.h b/tensorflow/stream_executor/event.h index 1f37262c78..9cc87a7c12 100644 --- a/tensorflow/stream_executor/event.h +++ b/tensorflow/stream_executor/event.h @@ -61,6 +61,9 @@ class Event { // Returns a pointer to the underlying platform-specific implementation. internal::EventInterface* implementation() { return implementation_.get(); } + Event(Event&&) = default; + Event& operator=(Event&&) = default; + private: friend class Stream; |