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https://issues.apache.org/jira/browse/SPARK-16574?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15380046#comment-15380046
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Norman He edited comment on SPARK-16574 at 7/15/16 11:30 PM:
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worker rdd is 20 tuples. They are equivalent. no data locality should come into
play here.
was (Author: nhe150):
worker rdd is 40 tuples. They are equivalent. no data locality should come into
play here.
> Distribute computing to each node based on certain hints
> --------------------------------------------------------
>
> Key: SPARK-16574
> URL: https://issues.apache.org/jira/browse/SPARK-16574
> Project: Spark
> Issue Type: Wish
> Reporter: Norman He
>
> 1) I have gpuWorkers RDD like(each node have 2 gpus)
> val nodes= 10
> val gpuCount = 2
> val cross: Array[(Int, Int)] = for( x <- Array.range(0, nodes); y <-
> Array.range(0, gpuCount ) ) yield (x, y)
> var gpuWorkers: RDD[(Int, Int)] = sc.parallelize(cross, nodes * gpuCount)
> 2) when executor runs, I would somehow like to distribute code to each nodes
> based on cross's gpu index(y) so that each machine 2 gpu can be used.
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