[jira] [Updated] (YARN-5517) Add GPU as a resource type for scheduling
[ https://issues.apache.org/jira/browse/YARN-5517?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Steve Loughran updated YARN-5517: - Target Version/s: (was: 2.7.1) Component/s: scheduler Summary: Add GPU as a resource type for scheduling (was: Add GPU as a resource type for scheduling on branch-2.7.1) > Add GPU as a resource type for scheduling > - > > Key: YARN-5517 > URL: https://issues.apache.org/jira/browse/YARN-5517 > Project: Hadoop YARN > Issue Type: Improvement > Components: scheduler >Reporter: Jaeboo Jeong > Attachments: RM-scheduler_metrics.jpg, YARN-5517-branch-2.7.1.patch, > aggregate_resource_allocation.jpg, container_example.jpg > > > Currently YARN only support scheduling based on memory and cpu. > There is the issue(YARN-3926) which proposed to extend the YARN resource > model. > And there is the issue(YARN-4122) to add support for GPU as a resource using > docker. > But these issues didn’t release yet so I just added GPU resource type like > memory and cpu. > I don’t consider GPU isolation like YARN-4122. > The properties for GPU resource type is similar to cpu core. > mapred-default.xml > mapreduce.map.gpu.cores (default 0) > mapreduce.reduce.gpu.cores(default 0) > yarn.app.mapreduce.am.resource.gpu-cores (default 0) > yarn-default.xml > yarn.scheduler.minimum-allocation-gcores (default 0) > yarn.scheduler.maximum-allocation-gcores (default 8) > yarn.nodemanager.resource.gcores (default 0) > I attached the patch for branch-2.7.1 -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Updated] (YARN-5517) Add GPU as a resource type for scheduling on branch-2.7.1
[ https://issues.apache.org/jira/browse/YARN-5517?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jaeboo Jeong updated YARN-5517: --- Attachment: YARN-5517-branch-2.7.1.patch > Add GPU as a resource type for scheduling on branch-2.7.1 > - > > Key: YARN-5517 > URL: https://issues.apache.org/jira/browse/YARN-5517 > Project: Hadoop YARN > Issue Type: Improvement >Reporter: Jaeboo Jeong > Attachments: YARN-5517-branch-2.7.1.patch > > > Currently YARN only support scheduling based on memory and cpu. > There is the issue(YARN-3926) which proposed to extend the YARN resource > model. > And there is the issue(YARN-4122) to add support for GPU as a resource using > docker. > But these issues didn’t release yet so I just added GPU resource type like > memory and cpu. > I don’t consider GPU isolation like YARN-4122. > The properties for GPU resource type is similar to cpu core. > mapred-default.xml > mapreduce.map.gpu.cores (default 0) > mapreduce.reduce.gpu.cores(default 0) > yarn.app.mapreduce.am.resource.gpu-cores (default 0) > yarn-default.xml > yarn.scheduler.minimum-allocation-gcores (default 0) > yarn.scheduler.maximum-allocation-gcores (default 8) > yarn.nodemanager.resource.gcores (default 0) > I attached the patch for branch-2.7.1 -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
[jira] [Updated] (YARN-5517) Add GPU as a resource type for scheduling on branch-2.7.1
[ https://issues.apache.org/jira/browse/YARN-5517?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jaeboo Jeong updated YARN-5517: --- Attachment: RM-scheduler_metrics.jpg aggregate_resource_allocation.jpg container_example.jpg > Add GPU as a resource type for scheduling on branch-2.7.1 > - > > Key: YARN-5517 > URL: https://issues.apache.org/jira/browse/YARN-5517 > Project: Hadoop YARN > Issue Type: Improvement >Reporter: Jaeboo Jeong > Attachments: RM-scheduler_metrics.jpg, YARN-5517-branch-2.7.1.patch, > aggregate_resource_allocation.jpg, container_example.jpg > > > Currently YARN only support scheduling based on memory and cpu. > There is the issue(YARN-3926) which proposed to extend the YARN resource > model. > And there is the issue(YARN-4122) to add support for GPU as a resource using > docker. > But these issues didn’t release yet so I just added GPU resource type like > memory and cpu. > I don’t consider GPU isolation like YARN-4122. > The properties for GPU resource type is similar to cpu core. > mapred-default.xml > mapreduce.map.gpu.cores (default 0) > mapreduce.reduce.gpu.cores(default 0) > yarn.app.mapreduce.am.resource.gpu-cores (default 0) > yarn-default.xml > yarn.scheduler.minimum-allocation-gcores (default 0) > yarn.scheduler.maximum-allocation-gcores (default 8) > yarn.nodemanager.resource.gcores (default 0) > I attached the patch for branch-2.7.1 -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: yarn-issues-unsubscr...@hadoop.apache.org For additional commands, e-mail: yarn-issues-h...@hadoop.apache.org
