Github user tnachen commented on a diff in the pull request:
https://github.com/apache/spark/pull/14644#discussion_r78002761
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosCoarseGrainedSchedulerBackend.scala
---
@@ -103,6 +103,7 @@ private[spark] class MesosCoarseGrainedSchedulerBackend(
private val stateLock = new ReentrantLock
val extraCoresPerExecutor = conf.getInt("spark.mesos.extra.cores", 0)
+ val maxGpus = conf.getInt("spark.mesos.gpus.max", 0)
--- End diff --
My thoughts was that by only allowing a Boolean flag a spark job either
uses all GPUs from a host or not, which it won't be able to have different GPu
devices shared by different jobs. By specifying a limit at least there is
ability to let a job specify how much GPUs it should grab per node. thoughts?
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