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https://issues.apache.org/jira/browse/SPARK-24615?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16554742#comment-16554742
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Imran Rashid commented on SPARK-24615:
--------------------------------------

hi, just catching up here -- agree with a lot of Tom's concerns.  There are a 
lot of corner cases we'd need to think about.  Eg., you mentioned joins, that 
in general they have stage boundaries -- but then again you might in some cases 
have a shared partitioner, which would remove the stage boundary.  And then 
there are other cases like {{zip()}}.

What if you had two rdds in one stage with conflicting requirements?  Eg. they 
request different accelerator types, and no node in the cluster has both 
available?  Would you fail?  Or introduce a stage boundary?  I think failing is 
fine, it would be OK if we require the user to put in their own boundary there 
(eg. by writing to hdfs) just want to think it through.

> Accelerator-aware task scheduling for Spark
> -------------------------------------------
>
>                 Key: SPARK-24615
>                 URL: https://issues.apache.org/jira/browse/SPARK-24615
>             Project: Spark
>          Issue Type: Improvement
>          Components: Spark Core
>    Affects Versions: 2.4.0
>            Reporter: Saisai Shao
>            Assignee: Saisai Shao
>            Priority: Major
>              Labels: Hydrogen, SPIP
>
> In the machine learning area, accelerator card (GPU, FPGA, TPU) is 
> predominant compared to CPUs. To make the current Spark architecture to work 
> with accelerator cards, Spark itself should understand the existence of 
> accelerators and know how to schedule task onto the executors where 
> accelerators are equipped.
> Current Spark’s scheduler schedules tasks based on the locality of the data 
> plus the available of CPUs. This will introduce some problems when scheduling 
> tasks with accelerators required.
>  # CPU cores are usually more than accelerators on one node, using CPU cores 
> to schedule accelerator required tasks will introduce the mismatch.
>  # In one cluster, we always assume that CPU is equipped in each node, but 
> this is not true of accelerator cards.
>  # The existence of heterogeneous tasks (accelerator required or not) 
> requires scheduler to schedule tasks with a smart way.
> So here propose to improve the current scheduler to support heterogeneous 
> tasks (accelerator requires or not). This can be part of the work of Project 
> hydrogen.
> Details is attached in google doc. It doesn't cover all the implementation 
> details, just highlight the parts should be changed.
>  
> CC [~yanboliang] [~merlintang]



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