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https://issues.apache.org/jira/browse/YARN-7481?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Chen Qingcha updated YARN-7481:
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Attachment: hadoop-2.7.2.gpu-port-20180711.patch
> Gpu locality support for Better AI scheduling
> ---------------------------------------------
>
> Key: YARN-7481
> URL: https://issues.apache.org/jira/browse/YARN-7481
> Project: Hadoop YARN
> Issue Type: New Feature
> Components: api, RM, yarn
> Affects Versions: 2.7.2
> Reporter: Chen Qingcha
> Priority: Major
> Fix For: 2.7.2
>
> Attachments: GPU locality support for Job scheduling.pdf,
> hadoop-2.7.2.gpu-port-20180710.patch,
> hadoop-2.7.2.gpu-port-20180710_old.patch,
> hadoop-2.7.2.gpu-port-20180711.patch, hadoop-2.7.2.gpu-port.patch,
> hadoop-2.9.0.gpu-port.patch, hadoop_2.9.0.patch
>
> Original Estimate: 1,344h
> Remaining Estimate: 1,344h
>
> We enhance Hadoop with GPU support for better AI job scheduling.
> Currently, YARN-3926 also supports GPU scheduling, which treats GPU as
> countable resource.
> However, GPU placement is also very important to deep learning job for better
> efficiency.
> For example, a 2-GPU job runs on gpu {0,1} could be faster than run on gpu
> {0, 7}, if GPU 0 and 1 are under the same PCI-E switch while 0 and 7 are not.
> We add the support to Hadoop 2.7.2 to enable GPU locality scheduling, which
> support fine-grained GPU placement.
> A 64-bits bitmap is added to yarn Resource, which indicates both GPU usage
> and locality information in a node (up to 64 GPUs per node). '1' means
> available and '0' otherwise in the corresponding position of the bit.
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