[GitHub] [spark] tgravescs commented on a change in pull request #24374: [SPARK-27366][CORE] Support GPU Resources in Spark job scheduling

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tgravescs commented on a change in pull request #24374: [SPARK-27366][CORE] Support GPU Resources in Spark job scheduling
URL: https://github.com/apache/spark/pull/24374#discussion_r287148845
 
 

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 File path: core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala
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 @@ -335,9 +339,10 @@ private[spark] class TaskSchedulerImpl(
     for (i <- 0 until shuffledOffers.size) {
       val execId = shuffledOffers(i).executorId
       val host = shuffledOffers(i).host
-      if (availableCpus(i) >= CPUS_PER_TASK) {
+      if (availableCpus(i) >= CPUS_PER_TASK &&
+        resourceMeetTaskRequirements(availableResources(i))) {
         try {
-          for (task <- taskSet.resourceOffer(execId, host, maxLocality)) {
+          for (task <- taskSet.resourceOffer(execId, host, maxLocality, availableResources(i))) {
             tasks(i) += task
             val tid = task.taskId
             taskIdToTaskSetManager.put(tid, taskSet)
 
 Review comment:
   I think its a bit out of place that we are decrementing the addresses  available in the resourceOffer function since everything else does its bookkeeping right here.  I don't think that is a blocker for this though and the way 

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