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Support synchronous training with parameter servers using Distribution Strategies #27725

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yuefengz opened this issue Apr 10, 2019 · 7 comments
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comp:dist-strat Distribution Strategy related issues type:feature Feature requests

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@yuefengz
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yuefengz commented Apr 10, 2019

System information

  • TensorFlow version (you are using): TF 2.0
  • Are you willing to contribute it (Yes/No): Yes

Describe the feature and the current behavior/state.
Right now we have MirroredStrategy and MultiWorkerMirroredStrategy for synchronous training where variables and ops are all replicated and all-reduce is used for gradient aggregation. We also have ParameterServerStrategy where gradient updates from workers are purely asynchronous since SyncReplicasOptimizer is buggy and has been deprecated.

We would like to first collect use cases where synchronous training with MirroredStrategy and MultiWorkerMirroredStrategy is not ideal and synchronous training with parameter servers is necessary.

If this feature is necessary and important enough, we will then use this issue to track the progress of the development of this feature.

We have a separate feature request to support large embeddings with MirroredStrategy and MultiWorkerMirroredStrategy: #27726

Will this change the current api? How?
Yes.

Who will benefit with this feature?
Those who use distributed training.

Any Other info.
N/A

@yuefengz yuefengz self-assigned this Apr 10, 2019
@josh11b josh11b added comp:dist-strat Distribution Strategy related issues type:feature Feature requests labels Apr 10, 2019
@shendiaomo
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What's the progress of this issue?

1 similar comment
@liyi193328
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What's the progress of this issue?

@neuzxy
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neuzxy commented Feb 21, 2020

This feature is promising. What's the progress of this issue? @yuefengz

@yuefengz
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We will send out a RFC for PSStrategy soon.

@liyi193328
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There is any plan? Thanks @yuefengz

@sahiltyagi4
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@yuefengz any developments on this ?

@Mesilenceki
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hi , Is there some progress with this issue?

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