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| author |  A. Unique TensorFlower <gardener@tensorflow.org> | 2018-09-28 14:08:25 -0700 |
|---|---|---|
| committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-09-28 14:34:43 -0700 |
| commit | f83da5b0aa37ba55c1b2eaa093e6d043b73f5982 (patch) | |
| tree | d28c727251f910dc0c7b7a6184286919d436e88f /tensorflow/core/protobuf | |
| parent | 1724d155f00b49bc817189247cbfb0df2092a9da (diff) | |
Introduce the abstraction of RunHandler which each DirectSession can use for
the duration of a single RunInternal() call from RunHandlerPool. It is used for
running inter-op closures with a global scheduler (which in the future) to
improve both median and tail latency (for use-cases like CPU inference).
In the case that global pools aren't used, this change should be a no-op.
PiperOrigin-RevId: 214992852
Diffstat (limited to 'tensorflow/core/protobuf')
| -rw-r--r-- | tensorflow/core/protobuf/config.proto | 5 |
1 files changed, 5 insertions, 0 deletions
diff --git a/tensorflow/core/protobuf/config.proto b/tensorflow/core/protobuf/config.proto index 85cd02350a..104ab039cb 100644 --- a/tensorflow/core/protobuf/config.proto +++ b/tensorflow/core/protobuf/config.proto @@ -453,6 +453,11 @@ message RunOptions { // same group_key value (in a distributed computation where tasks // run disjoint graphs). int64 collective_graph_key = 1; + // If true, then operations (using the inter-op pool) across all + // session::run() calls will be centrally scheduled, optimizing for (median + // and tail) latency. + // Consider using this option for CPU-bound workloads like inference. + bool use_run_handler_pool = 2; }; Experimental experimental = 8; |