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Slurm management of Lenovo SD665 V3 dual-server trays?
by Ole Holm Nielsen 26 Aug '24

26 Aug '24

We're experimenting with ways to manage our new racks of Lenovo SD665 V3 dual-server trays with Direct Water Cooling (further information is in our Wiki page https://wiki.fysik.dtu.dk/ITwiki/Lenovo_SD665_V3/ ) Management problems arise because 2 servers share a tray with common power and water cooling. This wouldn't be so bad if it weren't for Lenovo's NVIDIA/Mellanox SharedIO Infiniband adapters, where the left-hand node's IB adapter is a client of the right-hand node's adapter. So we can't reboot or power down the right-hand node without killing any MPI jobs that happen to be using the left-hand node. My question is if other Slurm sites owning Lenovo dual-server trays with SharedIO Infiniband adapters have developed some clever ways of handling such node pairs a single entity somehow? Is there anything we should configure on the Slurm side to make such nodes easier to manage? Thanks for sharing any insights, Ole -- Ole Holm Nielsen PhD, Senior HPC Officer Department of Physics, Technical University of Denmark

2 5

How to select a container runtime system?
by wdennis＠nec-labs.com 23 Aug '24

23 Aug '24

We are getting a few calls to support container workloads on our Slurm cluster; I want to support these user's usecases, so am looking into it now. The problem for me is, I'm not super-familiar with container runtimes excepting (regular rootful) Docker... I see that any Slurm-compatible runtime must be "rootless", so that takes out the integration with regular Docker. How does one choose between the many options (from what I gather, Apptainer/Singularity, Podman, and rootless Docker seem to be the most widely-used.) We also have to support GPUs in these containers, but I assume that any of these can support that. Can anyone tell me what the most popular Slurm-compatible container runtime may be, and plusses/minuses of the three I mentioned above? Thanks!

2 1

Slurmdbd purge and reported downtime
by Davide DelVento 23 Aug '24

23 Aug '24

I am confused by the reported amount of Down and PLND Down by sreport. According to it, our cluster would have had a significant amount of downtime, which I know didn't happen (or, according to the documentation "time that slurmctld was not responding", see https://slurm.schedmd.com/sreport.html) Could it be my purge settings causing this problem? How can I check (maybe in some logs, maybe in the future) if actually slurmctld was not responding? The expected long-term numbers should be less than the ones reported for last month when we had an issue with a few nodes.... Thanks! [davide@login ~]$ grep Purge /opt/slurm/slurmdbd.conf #JobPurge=12 #StepPurge=1 PurgeEventAfter=1month PurgeJobAfter=12month PurgeResvAfter=1month PurgeStepAfter=1month PurgeSuspendAfter=1month [davide@login ~]$ sreport -t percent -T cpu,mem cluster utilization start=2/1/22 -------------------------------------------------------------------------------- Cluster Utilization 2022-02-01T00:00:00 - 2024-08-21T23:59:59 Usage reported in Percentage of Total -------------------------------------------------------------------------------- Cluster TRES Name Allocated Down PLND Down Idle Planned Reported --------- -------------- --------------- --------------- -------------- ---------------- --------- ---------------- cluster cpu 19.50% 12.07% 3.92% 64.36% 0.15% 100.03% cluster mem 16.13% 13.17% 4.56% 66.13% 0.00% 99.99% [davide@login ~]$ sreport -t percent -T cpu,mem cluster utilization start=2/1/23 -------------------------------------------------------------------------------- Cluster Utilization 2023-02-01T00:00:00 - 2024-08-21T23:59:59 Usage reported in Percentage of Total -------------------------------------------------------------------------------- Cluster TRES Name Allocated Down PLND Down Idle Planned Reported --------- -------------- --------------- --------------- -------------- --------------- --------- ---------------- cluster cpu 28.74% 18.80% 6.44% 45.77% 0.24% 100.02% cluster mem 22.52% 20.54% 7.38% 49.55% 0.00% 99.98% [davide@login ~]$ sreport -t percent -T cpu,mem cluster utilization start=2/1/24 -------------------------------------------------------------------------------- Cluster Utilization 2024-02-01T00:00:00 - 2024-08-21T23:59:59 Usage reported in Percentage of Total -------------------------------------------------------------------------------- Cluster TRES Name Allocated Down PLND Down Idle Planned Reported --------- -------------- -------------- --------------- -------------- --------------- -------- --------------- cluster cpu 29.92% 24.88% 17.73% 27.45% 0.02% 100.00% cluster mem 20.07% 28.60% 19.57% 31.76% 0.00% 100.00% [davide@login ~]$ sreport -t percent -T cpu,mem cluster utilization start=8/8/24 -------------------------------------------------------------------------------- Cluster Utilization 2024-08-08T00:00:00 - 2024-08-21T23:59:59 Usage reported in Percentage of Total -------------------------------------------------------------------------------- Cluster TRES Name Allocated Down PLND Dow Idle Planned Reported --------- -------------- ------------- ------------ -------- -------------- -------- -------------- cluster cpu 15.96% 2.53% 0.00% 81.51% 0.00% 100.00% cluster mem 9.18% 2.22% 0.00% 88.60% 0.00% 100.00% [davide@login ~]$ sreport -t percent -T cpu,mem cluster utilization start=7/7/24 -------------------------------------------------------------------------------- Cluster Utilization 2024-07-07T00:00:00 - 2024-08-21T23:59:59 Usage reported in Percentage of Total -------------------------------------------------------------------------------- Cluster TRES Name Allocated Down PLND Dow Idle Planned Reported --------- -------------- -------------- ------------- -------- -------------- -------- -------------- cluster cpu 27.07% 2.57% 0.00% 70.34% 0.02% 100.00% cluster mem 17.35% 2.26% 0.00% 80.40% 0.00% 100.00%

2 2

trying to figure out how to troubleshoot cloud node resume/suspend
by Alex Chekholko 23 Aug '24

23 Aug '24

Hi all, I have a cloud cluster running in GCP that seems to have gotten stuck in a state where the slurmctld will not start/stop compute nodes, it just sits there with thousands of jobs in the queue and only a few compute nodes up and running (out of thousands). I can try to kick it by setting node states to drain/resume/power_up/power_down, whatever, nothing seems to happen. In slurmctld.log I get stuff like this: 2024-08-22 16:44:31,761 INFO: created 1 instances: nodes=hpcmarjola-computenodeset-384 but then in resume.log there is no corresponding entry One hypothesis I have is that it's taking like 30+mins to spin up a new node, but I know GCP doesn't take that long to create the VM, so how can I troubleshoot more what the slurm resume script is doing? e.g. I saw in the log: [2024-08-22T16:39:57.151] powering up node hpcmarjola-computenodeset-7 [2024-08-22T16:59:10.371] Node hpcmarjola-computenodeset-7 now responding I tried setting SlurmctldDebug = verbose #instead of info, so it prints power / resume status messages to the log And I see things like this: [2024-08-23T16:40:29.006] node hpcmarjola-computenodeset-1068 not resumed by ResumeTimeout(600) - marking down and power_save [2024-08-23T16:40:29.006] requeue job JobId=184535_503(185038) due to failure of node hpcmarjola-computenodeset-1068 [2024-08-23T16:40:29.006] Requeuing JobId=184535_503(185038) [2024-08-23T16:40:29.007] POWER: power_save: waking nodes hpcmarjola-computenodeset-[2154-2156] [2024-08-23T16:40:29.007] POWER: power_save: handle failed nodes hpcmarjola-computenodeset-[1065-1068] I'll try bumping this value but that seems crazy high: ResumeTimeout=2400 slurm 23.11.7 I read through these pages: https://slurm.schedmd.com/power_save.html my config files (generated by gcp hpc toolkit scripts): topology.conf: SwitchName=nodeset-root Switches=computenodeset SwitchName=computenodeset Nodes=hpcmarjola-computenodeset-[0-4999] cloud.conf: PrivateData=cloud LaunchParameters=enable_nss_slurm,use_interactive_step SlurmctldParameters=cloud_dns,enable_configless,idle_on_node_suspend SchedulerParameters=bf_continue,salloc_wait_nodes,ignore_prefer_validation SuspendProgram=/slurm/scripts/suspend.py ResumeProgram=/slurm/scripts/resume.py ResumeFailProgram=/slurm/scripts/suspend.py ResumeRate=2 ResumeTimeout=600 SuspendRate=2 SuspendTimeout=600 TreeWidth=16 TopologyPlugin=topology/tree NodeSet=x-login Feature=x-login PartitionName=x-login Nodes=x-login State=UP DefMemPerCPU=1 Hidden=YES RootOnly=YES NodeName=DEFAULT State=UNKNOWN RealMemory=126832 Boards=1 SocketsPerBoard=1 CoresPerSocket=8 ThreadsPerCore=1 CPUs=8 NodeName=hpcmarjola-computenodeset-[0-4999] State=CLOUD NodeSet=computenodeset Nodes=hpcmarjola-computenodeset-[0-4999] PartitionName=compute Nodes=computenodeset State=UP DefMemPerCPU=15854 SuspendTime=600 Oversubscribe=Exclusive PowerDownOnIdle=NO Default=YES ResumeTimeout=600 SuspendTimeout=600 SuspendExcParts=x-login slurm.conf: # slurm.conf # https://slurm.schedmd.com/slurm.conf.html # https://slurm.schedmd.com/configurator.html ProctrackType=proctrack/cgroup SlurmctldPidFile=/var/run/slurm/slurmctld.pid SlurmdPidFile=/var/run/slurm/slurmd.pid TaskPlugin=task/affinity,task/cgroup MaxNodeCount=64000 # # # SCHEDULING SchedulerType=sched/backfill SelectType=select/cons_tres SelectTypeParameters=CR_Core_Memory # # # LOGGING AND ACCOUNTING AccountingStoreFlags=job_comment JobAcctGatherFrequency=30 JobAcctGatherType=jobacct_gather/cgroup SlurmctldDebug=info SlurmdDebug=info DebugFlags=Power # # # TIMERS MessageTimeout=60 ################################################################################ # vvvvv WARNING: DO NOT MODIFY SECTION BELOW vvvvv # ################################################################################ SlurmctldHost=hpcmarjola-controller(internal-cloud-dns-redacted) AuthType=auth/munge AuthInfo=cred_expire=120 AuthAltTypes=auth/jwt CredType=cred/munge MpiDefault=none ReturnToService=2 SlurmctldPort=6820-6830 SlurmdPort=6818 SlurmdSpoolDir=/var/spool/slurmd SlurmUser=slurm StateSaveLocation=/var/spool/slurm # # # LOGGING AND ACCOUNTING AccountingStorageType=accounting_storage/slurmdbd AccountingStorageHost=hpcmarjola-controller ClusterName=hpcmarjola SlurmctldLogFile=/var/log/slurm/slurmctld.log SlurmdLogFile=/var/log/slurm/slurmd-%n.log # # # GENERATED CLOUD CONFIGURATIONS include cloud.conf ################################################################################ # ^^^^^ WARNING: DO NOT MODIFY SECTION ABOVE ^^^^^ # ################################################################################ MaxArraySize = 200001 MaxJobCount = 200001

1 0

Manually initiating a DB purge
by Sid Young 22 Aug '24

22 Aug '24

G'Day all, I have 3 years worth of job records in the slurm DB and we do not have any need to actually track anything at this stage, I would like to keep 12months worth of jobs so I need to purge 2 years worth at some point.. Is there a command to issue via scontrol to kick off a SlurmPurge using the values in the slurmdbd.conf file (currently these are 1000days, so I can see a few dozen records disappear before I shorten it to 365days in incremental steps). Sid

2 4

active reservation lost when increasing the duration
by Danny Marc Rotscher 22 Aug '24

22 Aug '24

Dear All, we are running Slurm 23.11.8 and I loose an active reservation and the jobs running in that reservation, when I tried to increase the duration of that reservation. I only want to tell you, that you may not run into the same problem. Kind regards, Danny Rotscher

1 0

Slurm hanging behavior
by Richard Yang 20 Aug '24

20 Aug '24

Hello Slurm community, We are using slurm as the system to deploy training jobs on a large gpu cluster, but encounter a strange behavior. As new comers, we wonder if this is a known behavior. Below is some more info: * We are running a relatively older version 22.0.5 * At relatively higher load, we encountered hanging. It is particularly puzzling in the following sense: assume we have nodelist1 with 6 hosts and nodelist2 with 7 hosts. We run simple ‘hostname’. Deploying on nodelist1 alone or nodelusr2 alone will be fine, but with all 13 hosts, the debug messages show that the execution hang after showing that the last task done. It then hangs for exactly 180 seconds. Does anyone know the potential issue? We sure be happy to post more config details or debug messages. Thank you so much! Richard

1 0

Access to --constraint=<arg> in Lua cli_filter?
by Kevin Buckley 20 Aug '24

20 Aug '24

If I supply a --constraint=<arg> option to an sbatch/salloc/srun, does the arg appear inside any object that a Lua CLI Filter could access? I've tried this basic check if is_unset(options['constraint']) then slurm_errorf('constraint is unset ') end and seen that that object is, indeed, unset. Kevin

2 2

Unable to run sequential jobs simultaneously on the same node
by Arko Roy 20 Aug '24

20 Aug '24

I want to run 50 sequential jobs (essentially 50 copies of the same code with different input parameters) on a particular node. However, as soon as one of the jobs gets executed, the other 49 jobs get killed immediately with exit code 9. The jobs are not interacting and are strictly parallel. However, if the 50 jobs run on 50 different nodes, it runs successfully. Can anyone please help with possible fixes? I see a discussion almost along the similar lines in https://groups.google.com/g/slurm-users/c/I1T6GWcLjt4 But could not get the final solution. -- Arko Roy Assistant Professor School of Physical Sciences Indian Institute of Technology Mandi Kamand, Mandi Himachal Pradesh - 175 005, India Email: arko(a)iitmandi.ac.in Web: https://faculty.iitmandi.ac.in/~arko/

5 7

sreport syntax for TRES/GPU usage
by Robert Kudyba 16 Aug '24

16 Aug '24

In a 25 node heterogeneous cluster with 4 different types of GPUs, to get granular to see which GPUs were used most over a time period we have to set AccountingStorageTRES to something like: AccountingStorageTRES=gres/gpu,gres/gpu:rtx8000,gres/gpu:v100s,gres/gpu:a40,gres/gpu:a100 Unfortunately it's currently at: AccountingStorageTRES=gres/gpu At least all nodes have the same GPU within each node. What are some good options to sreport to get details on usage over a year, e.g., percentage of CPU vs GPU, which partitions/accounts used the most GPUs, etc. From this example: sreport -tminper -t Percent cluster utilization --tres="cpu,gres/gpu" start=2023-07-01 -------------------------------------------------------------------------------- Cluster Utilization 2023-07-01T00:00:00 - 2024-08-15T23:59:59 Usage reported in Percentage of Total -------------------------------------------------------------------------------- Cluster TRES Name Allocated Down PLND Dow Idle Reserved Reported --------- -------------- ----------- ---------- -------- ----------- ---------- ----------- cluster cpu 43.81% 2.87% 0.00% 48.35% 4.97% 99.86% cluster gres/gpu 50.36% 3.59% 0.00% 46.05% 0.00% 100.38% Is that showing that 50% of all jobs were run with GPUs? How do we read the Idle column? Why does Reported show > 100% for gres?

1 0

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