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?
--- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org