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From "Tan N. Le (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (YARN-6223) [Umbrella] Natively support GPU configuration/discovery/scheduling/isolation on YARN
Date Wed, 26 Jul 2017 18:31:01 GMT

    [ https://issues.apache.org/jira/browse/YARN-6223?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16102067#comment-16102067

Tan N. Le commented on YARN-6223:

Hi Wangda Tan,

Does this feature have a working version yet? I am looking for this feature on Yarn for machine
learning jobs (like Tensorflow).
I wonder whether you can share the source code if it works.


> [Umbrella] Natively support GPU configuration/discovery/scheduling/isolation on YARN
> ------------------------------------------------------------------------------------
>                 Key: YARN-6223
>                 URL: https://issues.apache.org/jira/browse/YARN-6223
>             Project: Hadoop YARN
>          Issue Type: New Feature
>            Reporter: Wangda Tan
>            Assignee: Wangda Tan
>         Attachments: YARN-6223.Natively-support-GPU-on-YARN-v1.pdf, YARN-6223.wip.1.patch,
YARN-6223.wip.2.patch, YARN-6223.wip.3.patch
> As varieties of workloads are moving to YARN, including machine learning / deep learning
which can speed up by leveraging GPU computation power. Workloads should be able to request
GPU from YARN as simple as CPU and memory.
> *To make a complete GPU story, we should support following pieces:*
> 1) GPU discovery/configuration: Admin can either config GPU resources and architectures
on each node, or more advanced, NodeManager can automatically discover GPU resources and architectures
and report to ResourceManager 
> 2) GPU scheduling: YARN scheduler should account GPU as a resource type just like CPU
and memory.
> 3) GPU isolation/monitoring: once launch a task with GPU resources, NodeManager should
properly isolate and monitor task's resource usage.
> For #2, YARN-3926 can support it natively. For #3, YARN-3611 has introduced an extensible
framework to support isolation for different resource types and different runtimes.
> *Related JIRAs:*
> There're a couple of JIRAs (YARN-4122/YARN-5517) filed with similar goals but different
> For scheduling:
> - YARN-4122/YARN-5517 are all adding a new GPU resource type to Resource protocol instead
of leveraging YARN-3926.
> For isolation:
> - And YARN-4122 proposed to use CGroups to do isolation which cannot solve the problem
listed at https://github.com/NVIDIA/nvidia-docker/wiki/GPU-isolation#challenges such as minor
device number mapping; load nvidia_uvm module; mismatch of CUDA/driver versions, etc.

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