Vinod Kumar Vavilapalli resolved YARN-6223.
    Resolution: Fixed

> [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
>            Priority: Major
>             Fix For: 3.1.0
>         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 solutions:
> 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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