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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (IGNITE-10133) ML: Switch to per-node TensorFlow worker strategy
Date Wed, 07 Nov 2018 14:45:00 GMT

    [ https://issues.apache.org/jira/browse/IGNITE-10133?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16678319#comment-16678319
] 

ASF GitHub Bot commented on IGNITE-10133:
-----------------------------------------

Github user dmitrievanthony closed the pull request at:

    https://github.com/apache/ignite/pull/5249


> ML: Switch to per-node TensorFlow worker strategy
> -------------------------------------------------
>
>                 Key: IGNITE-10133
>                 URL: https://issues.apache.org/jira/browse/IGNITE-10133
>             Project: Ignite
>          Issue Type: Improvement
>          Components: ml
>    Affects Versions: 2.8
>            Reporter: Anton Dmitriev
>            Assignee: Anton Dmitriev
>            Priority: Major
>             Fix For: 2.8
>
>
> Currently we start TensorFlow worker process per every cache partition. In case node
is equipped by GPU and TensorFlow uses this GPU it acquires all GPU memory. If two worker
processes try to acquire all GPU memory they will fail.
> To eliminate this problem and allow users utilizing GPU during the training we need
to switch to per-node strategy. It means we need to start one TensorFlow worker process per
node, not per partition.



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