Re: [slurm-users] CPU allocation for the GPU jobs.
Thanks Renfro. My scheduling policy is below. SchedulerType=sched/builtin SelectType=select/cons_res SelectTypeParameters=CR_Core AccountingStorageEnforce=associations AccountingStorageHost=192.168.150.223 AccountingStorageType=accounting_storage/slurmdbd ClusterName=hpc JobCompType=jobcomp/slurmdbd JobAcctGatherFrequency=30 JobAcctGatherType=jobacct_gather/linux SlurmctldDebug=5 SlurmdDebug=5 Waittime=0 Epilog=/etc/slurm/slurm.epilog.clean GresTypes=gpu MaxJobCount=500 SchedulerParameters=enable_user_top,default_queue_depth=100 # JOB PRIORITY PriorityType=priority/multifactor PriorityDecayHalfLife=2 PriorityUsageResetPeriod=DAILY PriorityWeightFairshare=50 PriorityFlags=FAIR_TREE let me try changing it to the backfill and will see if it helps. Regards Navin. On Mon, Jul 13, 2020 at 5:16 PM Renfro, Michael wrote: > “The *SchedulerType* configuration parameter specifies the scheduler > plugin to use. Options are sched/backfill, which performs backfill > scheduling, and sched/builtin, which attempts to schedule jobs in a strict > priority order within each partition/queue.” > > https://slurm.schedmd.com/sched_config.html > > If you’re using the builtin scheduler, lower priority jobs have no way to > run ahead of higher priority jobs. If you’re using the backfill scheduler, > your jobs will need specific wall times specified, since the idea with > backfill is to run lower priority jobs ahead of time if and only if they > can complete without delaying the estimated start time of higher priority > jobs. > > On Jul 13, 2020, at 4:18 AM, navin srivastava > wrote: > > Hi Team, > > We have separate partitions for the GPU nodes and only CPU nodes . > > scenario: the jobs submitted in our environment is 4CPU+1GPU as well as > 4CPU only in nodeGPUsmall and nodeGPUbig. so when all the GPU exhausted > and rest other jobs are in queue waiting for the availability of GPU > resources.the job submitted with only CPU is not going through even > though plenty of CPU resources are available but the job which is only > looking CPU, also on pend because of these GPU based jobs( priority of GPU > jobs is higher than CPU one). > > Is there any option here we can do,so that when all GPU resources are > exhausted then it should allow the CPU jobs. Is there a way to deal with > it? or some custom solution which we can think of. There is no issue with > CPU only partitions. > > Below is the my slurm configuration file > > > NodeName=node[1-12] NodeAddr=node[1-12] Sockets=2 CoresPerSocket=10 > RealMemory=128833 State=UNKNOWN > NodeName=node[13-16] NodeAddr=node[13-16] Sockets=2 CoresPerSocket=10 > RealMemory=515954 Feature=HIGHMEM State=UNKNOWN > NodeName=node[28-32] NodeAddr=node[28-32] Sockets=2 CoresPerSocket=28 > RealMemory=257389 > NodeName=node[32-33] NodeAddr=node[32-33] Sockets=2 CoresPerSocket=24 > RealMemory=773418 > NodeName=node[17-27] NodeAddr=node[17-27] Sockets=2 CoresPerSocket=18 > RealMemory=257687 Feature=K2200 Gres=gpu:2 > NodeName=node[34] NodeAddr=node34 Sockets=2 CoresPerSocket=24 > RealMemory=773410 Feature=RTX Gres=gpu:8 > > > PartitionName=node Nodes=node[1-10,14-16,28-33,35] Default=YES > MaxTime=INFINITE State=UP Shared=YES > PartitionName=nodeGPUsmall Nodes=node[17-27] Default=NO MaxTime=INFINITE > State=UP Shared=YES > PartitionName=nodeGPUbig Nodes=node[34] Default=NO MaxTime=INFINITE > State=UP Shared=YES > > Regards > Navin. > > >
Re: [slurm-users] CPU allocation for the GPU jobs.
“The SchedulerType configuration parameter specifies the scheduler plugin to use. Options are sched/backfill, which performs backfill scheduling, and sched/builtin, which attempts to schedule jobs in a strict priority order within each partition/queue.” https://slurm.schedmd.com/sched_config.html If you’re using the builtin scheduler, lower priority jobs have no way to run ahead of higher priority jobs. If you’re using the backfill scheduler, your jobs will need specific wall times specified, since the idea with backfill is to run lower priority jobs ahead of time if and only if they can complete without delaying the estimated start time of higher priority jobs. On Jul 13, 2020, at 4:18 AM, navin srivastava wrote: Hi Team, We have separate partitions for the GPU nodes and only CPU nodes . scenario: the jobs submitted in our environment is 4CPU+1GPU as well as 4CPU only in nodeGPUsmall and nodeGPUbig. so when all the GPU exhausted and rest other jobs are in queue waiting for the availability of GPU resources.the job submitted with only CPU is not going through even though plenty of CPU resources are available but the job which is only looking CPU, also on pend because of these GPU based jobs( priority of GPU jobs is higher than CPU one). Is there any option here we can do,so that when all GPU resources are exhausted then it should allow the CPU jobs. Is there a way to deal with it? or some custom solution which we can think of. There is no issue with CPU only partitions. Below is the my slurm configuration file NodeName=node[1-12] NodeAddr=node[1-12] Sockets=2 CoresPerSocket=10 RealMemory=128833 State=UNKNOWN NodeName=node[13-16] NodeAddr=node[13-16] Sockets=2 CoresPerSocket=10 RealMemory=515954 Feature=HIGHMEM State=UNKNOWN NodeName=node[28-32] NodeAddr=node[28-32] Sockets=2 CoresPerSocket=28 RealMemory=257389 NodeName=node[32-33] NodeAddr=node[32-33] Sockets=2 CoresPerSocket=24 RealMemory=773418 NodeName=node[17-27] NodeAddr=node[17-27] Sockets=2 CoresPerSocket=18 RealMemory=257687 Feature=K2200 Gres=gpu:2 NodeName=node[34] NodeAddr=node34 Sockets=2 CoresPerSocket=24 RealMemory=773410 Feature=RTX Gres=gpu:8 PartitionName=node Nodes=node[1-10,14-16,28-33,35] Default=YES MaxTime=INFINITE State=UP Shared=YES PartitionName=nodeGPUsmall Nodes=node[17-27] Default=NO MaxTime=INFINITE State=UP Shared=YES PartitionName=nodeGPUbig Nodes=node[34] Default=NO MaxTime=INFINITE State=UP Shared=YES Regards Navin.
[slurm-users] CPU allocation for the GPU jobs.
Hi Team, We have separate partitions for the GPU nodes and only CPU nodes . scenario: the jobs submitted in our environment is 4CPU+1GPU as well as 4CPU only in nodeGPUsmall and nodeGPUbig. so when all the GPU exhausted and rest other jobs are in queue waiting for the availability of GPU resources.the job submitted with only CPU is not going through even though plenty of CPU resources are available but the job which is only looking CPU, also on pend because of these GPU based jobs( priority of GPU jobs is higher than CPU one). Is there any option here we can do,so that when all GPU resources are exhausted then it should allow the CPU jobs. Is there a way to deal with it? or some custom solution which we can think of. There is no issue with CPU only partitions. Below is the my slurm configuration file NodeName=node[1-12] NodeAddr=node[1-12] Sockets=2 CoresPerSocket=10 RealMemory=128833 State=UNKNOWN NodeName=node[13-16] NodeAddr=node[13-16] Sockets=2 CoresPerSocket=10 RealMemory=515954 Feature=HIGHMEM State=UNKNOWN NodeName=node[28-32] NodeAddr=node[28-32] Sockets=2 CoresPerSocket=28 RealMemory=257389 NodeName=node[32-33] NodeAddr=node[32-33] Sockets=2 CoresPerSocket=24 RealMemory=773418 NodeName=node[17-27] NodeAddr=node[17-27] Sockets=2 CoresPerSocket=18 RealMemory=257687 Feature=K2200 Gres=gpu:2 NodeName=node[34] NodeAddr=node34 Sockets=2 CoresPerSocket=24 RealMemory=773410 Feature=RTX Gres=gpu:8 PartitionName=node Nodes=node[1-10,14-16,28-33,35] Default=YES MaxTime=INFINITE State=UP Shared=YES PartitionName=nodeGPUsmall Nodes=node[17-27] Default=NO MaxTime=INFINITE State=UP Shared=YES PartitionName=nodeGPUbig Nodes=node[34] Default=NO MaxTime=INFINITE State=UP Shared=YES Regards Navin.
