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https://issues.apache.org/jira/browse/YARN-5517?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Steve Loughran updated YARN-5517:
---------------------------------
Target Version/s: (was: 2.7.1)
Component/s: scheduler
Summary: Add GPU as a resource type for scheduling (was: Add GPU
as a resource type for scheduling on branch-2.7.1)
> Add GPU as a resource type for scheduling
> -----------------------------------------
>
> Key: YARN-5517
> URL: https://issues.apache.org/jira/browse/YARN-5517
> Project: Hadoop YARN
> Issue Type: Improvement
> Components: scheduler
> Reporter: Jaeboo Jeong
> Attachments: RM-scheduler_metrics.jpg, YARN-5517-branch-2.7.1.patch,
> aggregate_resource_allocation.jpg, container_example.jpg
>
>
> Currently YARN only support scheduling based on memory and cpu.
> There is the issue(YARN-3926) which proposed to extend the YARN resource
> model.
> And there is the issue(YARN-4122) to add support for GPU as a resource using
> docker.
> But these issues didn’t release yet so I just added GPU resource type like
> memory and cpu.
> I don’t consider GPU isolation like YARN-4122.
> The properties for GPU resource type is similar to cpu core.
> mapred-default.xml
> mapreduce.map.gpu.cores (default 0)
> mapreduce.reduce.gpu.cores (default 0)
> yarn.app.mapreduce.am.resource.gpu-cores (default 0)
> yarn-default.xml
> yarn.scheduler.minimum-allocation-gcores (default 0)
> yarn.scheduler.maximum-allocation-gcores (default 8)
> yarn.nodemanager.resource.gcores (default 0)
> I attached the patch for branch-2.7.1
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