June 2024 - slurm-users - lists.schedmd.com

JWKS File Update - Reread File
by Pedro Daniel Da Rocha Santos 06 Jun '24

06 Jun '24

Hello everyone, I am currently implementing a service to monitor for jwks key rotation. If a change is detected, the jwks file is updated. Is it enough to use "scontrol reconfigure" to reread the jwks file? Or does it require a full restart of the slurmctl daemon? Thanks in advance for the inputs. Best regards, Pedro D.R. Santos Specialist, Ph.D., High Performance Computing Vestas Technology Centre Porto Vestas Wind Systems A/S +351 924 241 907 pddro(a)vestas.com<mailto:pddro@vestas.com> http://www.vestas.com<http://www.vestas.com/> Company reg. name: Vestas Wind Systems A/S This e-mail is subject to our e-mail disclaimer statement. Please refer to www.vestas.com/legal/notice<http://www.vestas.com/legal/notice> If you have received this e-mail in error please contact the sender. Vestas will as part of your communication, interaction and business relationship with us collect and process personal data about you. You can read more about Vestas' collection and processing of your personal data and your rights as a data subject in our Privacy Policy<https://www.vestas.com/en/about/profile/privacy-policy>. Classification: Restricted

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diagnosing why interactive/non-interactive job waits are so long with State=MIXED
by Robert Kudyba 05 Jun '24

05 Jun '24

At the moment we have 2 nodes that are having long wait times. Generally this is when the nodes are fully allocated. What would be the other reasons if there is still enough available memory and CPU available, that a job would take so long? Slurm version is 23.02.4 via Bright Computing. Note the compute nodes have hyperthreading enabled but that should be irrelevant. Is there a way to determine what else could be holding jobs up? srun --pty -t 0-01:00:00 --nodelist=node001 --gres=gpu:1 -A ourts -p short /bin/bash srun: job 672204 queued and waiting for resources scontrol show node node001 NodeName=m001 Arch=x86_64 CoresPerSocket=48 CPUAlloc=24 CPUEfctv=192 CPUTot=192 CPULoad=20.37 AvailableFeatures=location=local ActiveFeatures=location=local Gres=gpu:A6000:8 NodeAddr=node001 NodeHostName=node001 Version=23.02.4 OS=Linux 5.14.0-70.13.1.el9_0.x86_64 #1 SMP PREEMPT Thu Apr 14 12:42:38 EDT 2022 RealMemory=1031883 AllocMem=1028096 FreeMem=222528 Sockets=2 Boards=1 State=MIXED ThreadsPerCore=2 TmpDisk=0 Weight=1 Owner=N/A MCS_label=N/A Partitions=ours,short BootTime=2024-04-29T16:18:30 SlurmdStartTime=2024-05-18T16:48:11 LastBusyTime=2024-06-03T10:49:49 ResumeAfterTime=None CfgTRES=cpu=192,mem=1031883M,billing=192,gres/gpu=8 AllocTRES=cpu=24,mem=1004G,gres/gpu=2,gres/gpu:a6000=2 CapWatts=n/a CurrentWatts=0 AveWatts=0 ExtSensorsJoules=n/s ExtSensorsWatts=0 ExtSensorsTemp=n/s grep 672204 /var/log/slurmctld [2024-06-04T15:50:35.627] sched: _slurm_rpc_allocate_resources JobId=672204 NodeList=(null) usec=852

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Re: Problems with gres.conf
by Gestió Servidors 05 Jun '24

05 Jun '24

Hi, my GPU testing system (named “gpu-node”) is a simple computer with one socket and a processor " Intel(R) Core(TM) i7 CPU 950 @ 3.07GHz". Executing "lscpu", I can see there are 4 cores per socket, 2 threads per core and 8 CPUs: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Byte Order: Little Endian CPU(s): 8 On-line CPU(s) list: 0-7 Thread(s) per core: 2 Core(s) per socket: 4 Socket(s): 1 NUMA node(s): 1 Vendor ID: GenuineIntel CPU family: 6 Model: 26 Model name: Intel(R) Core(TM) i7 CPU 950 @ 3.07GHz My “gres.conf” file is: NodeName=gpu-node Name=gpu Type=GeForce-GTX-TITAN-X File=/dev/nvidia0 CPUs=0-1 NodeName=gpu-node Name=gpu Type=GeForce-GTX-TITAN-Black File=/dev/nvidia1 CPUs=2-3 Running “numactl -H” in “gpu-node” host, reports: available: 1 nodes (0) node 0 cpus: 0 1 2 3 4 5 6 7 node 0 size: 7809 MB node 0 free: 6597 MB node distances: node 0 0: 10 CPUs are assigned 0-1 for first GPU and 2-3 for second GPU. However, “lscpu” shows 8 CPUs… If I rewrite “gres.conf” in this way: NodeName=gpu-node Name=gpu Type=GeForce-GTX-TITAN-X File=/dev/nvidia0 CPUs=0-3 NodeName=gpu-node Name=gpu Type=GeForce-GTX-TITAN-Black File=/dev/nvidia1 CPUs=4-7 when I run “scontrol reconfigure”, slurmctld log reports this error message: [2024-06-05T11:42:18.558] error: _node_config_validate: gres/gpu: invalid GRES core specification (4-7) on node gpu-node So I think SLURM only can get physical cores and not threads, so my node only can serve 4 cores (in “lspcu”) but in gres.conf I need to write “CPUs”, not “Cores”… isn’t it? But if “numactl -H” shows 8 CPUs, why I can use this 8 CPUs in “gres.conf”? Sorry about this large email. Thanks.

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Problems with gres.conf
by Gestió Servidors 04 Jun '24

04 Jun '24

Hello, I am trying to rewrite my gres.conf file. Before changes, this file was just like this: NodeName=node-gpu-1 AutoDetect=off Name=gpu Type=GeForceRTX2070 File=/dev/nvidia0 Cores=0-11 NodeName=node-gpu-1 AutoDetect=off Name=gpu Type=GeForceGTX1080Ti File=/dev/nvidia1 Cores=12-23 NodeName=node-gpu-2 AutoDetect=off Name=gpu Type=GeForceGTX1080Ti File=/dev/nvidia0 Cores=0-11 NodeName=node-gpu-2 AutoDetect=off Name=gpu Type=GeForceGTX1080 File=/dev/nvidia1 Cores=12-23 NodeName=node-gpu-3 AutoDetect=off Name=gpu Type=GeForceRTX3080 File=/dev/nvidia0 Cores=0-11 NodeName=node-gpu-4 AutoDetect=off Name=gpu Type=GeForceRTX3080 File=/dev/nvidia0 Cores=0-7 # you can seee that nodes node-gpu-1 and node-gpu-2 have two GPUs each one, whereas nodes node-gpu-3 and node-gpu-4 have only one GPU each one And my slurmd.conf was this: [...] AccountingStorageTRES=gres/gpu GresTypes=gpu NodeName=node-gpu-1 CPUs=24 SocketsPerBoard=2 CoresPerSocket=6 ThreadsPerCore=2 RealMemory=96000 TmpDisk=47000 Gres=gpu:GeForceRTX2070:1,gpu:GeForceGTX1080Ti:1 NodeName=node-gpu-2 CPUs=24 SocketsPerBoard=2 CoresPerSocket=6 ThreadsPerCore=2 RealMemory=96000 TmpDisk=47000 Gres=gpu:GeForceGTX1080Ti:1,gpu:GeForceGTX1080:1 NodeName=node-gpu-3 CPUs=12 SocketsPerBoard=1 CoresPerSocket=6 ThreadsPerCore=2 RealMemory=23000 Gres=gpu:GeForceRTX3080:1 NodeName=node-gpu-4 CPUs=8 SocketsPerBoard=1 CoresPerSocket=4 ThreadsPerCore=2 RealMemory=7800 Gres=gpu:GeForceRTX3080:1 NodeName=node-worker-[0-22] CPUs=12 SocketsPerBoard=1 CoresPerSocket=6 ThreadsPerCore=2 RealMemory=47000 [...] With this configuration, all seems works fine, except slurmctld.log reports: [...] error: _node_config_validate: gres/gpu: invalid GRES core specification (0-11) on node node-gpu-3 error: _node_config_validate: gres/gpu: invalid GRES core specification (12-23) on node node-gpu-1 error: _node_config_validate: gres/gpu: invalid GRES core specification (12-23) on node node-gpu-2 error: _node_config_validate: gres/gpu: invalid GRES core specification (0-7) on node node-gpu-4 [...] However, even these errors, users can submit jobs and request GPUs resources. Now, I have tried to reconfigure gres.conf and slurmd.conf in this way: gres.conf: Name=gpu Type=GeForceRTX2070 File=/dev/nvidia0 Name=gpu Type=GeForceGTX1080Ti File=/dev/nvidia1 Name=gpu Type=GeForceGTX1080Ti File=/dev/nvidia0 Name=gpu Type=GeForceGTX1080 File=/dev/nvidia1 Name=gpu Type=GeForceRTX3080 File=/dev/nvidia0 Name=gpu Type=GeForceRTX3080 File=/dev/nvidia0 # there is no NodeName attribute slurmd.conf: [...] NodeName=node-gpu-1 SocketsPerBoard=2 CoresPerSocket=6 ThreadsPerCore=2 RealMemory=96000 TmpDisk=47000 Gres=gpu:GeForceRTX2070:1,gpu:GeForceGTX1080Ti:1 NodeName=node-gpu-2 SocketsPerBoard=2 CoresPerSocket=6 ThreadsPerCore=2 RealMemory=96000 TmpDisk=47000 Gres=gpu:GeForceGTX1080Ti:1,gpu:GeForceGTX1080:1 NodeName=node-gpu-3 SocketsPerBoard=1 CoresPerSocket=6 ThreadsPerCore=2 RealMemory=23000 Gres=gpu:GeForceRTX3080:1 NodeName=node-gpu-4 SocketsPerBoard=1 CoresPerSocket=4 ThreadsPerCore=2 RealMemory=7800 Gres=gpu:GeForceRTX3080:1 NodeName=node-worker-[0-22] SocketsPerBoard=1 CoresPerSocket=6 ThreadsPerCore=2 RealMemory=47000 # there is no CPUs attribute [...] With this new configuration, nodes with GPU start correctly slurmd.service daemon, but nodes without GPU (node-worker-[0-22]) can't start slurmd.service daemon and returns this error: [...] error: Waiting for gres.conf file /dev/nvidia0 fatal: can't stat gres.conf file /dev/nvidia0: No such file or directory [...] It seems SLURM is waiting that "node-workers" have also an nvidia GPU but not, theses nodes haven't GPU... So, where is my configuration error? I have read in https://slurm.schedmd.com/gres.conf.html about syntax and examples but it seems I'm doing some wrong. Thanks!!

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Tracking GPU utilization with sacct
by Robertson, Jordan 03 Jun '24

03 Jun '24

Hi all, I’m trying to pull (and understand) some GPU usage metrics for historical purposes, and dug into sacct’s TRES reporting a bit. We have AccountingStorageTRES=gres/gpu set in slurm.conf so we do see gres/gpuutil and gres/gpumem numbers available, but I’m struggling to find Slurm-side documentation that describes the units of these values. In looking at the code for gpu_nvml.c it seems the “nvmlDeviceGetProcessUtilization” function is being used and returns units in percentages, but I’m lost on the rest of the calculation. Does anyone know if these units are percentages, and how they are calculated for the final job record, especially wrt multi-GPU jobs with a bunch of processes/moving parts? For context I’ve been looking at TRESUsageInTot and TRESUsageInAve so far. Also we’re currently running Slurm v23.02.6 Thanks in advance! -- Jordan Robertson Preferred pronouns: he/him/his Technology Architect | Research Technology Services DigITs, Technology Division Memorial Sloan Kettering Cancer Center 929-687-1066 robertj8(a)mskcc.org<mailto:robertj8@mskcc.org> ===================================================================== Please note that this e-mail and any files transmitted from Memorial Sloan Kettering Cancer Center may be privileged, confidential, and protected from disclosure under applicable law. If the reader of this message is not the intended recipient, or an employee or agent responsible for delivering this message to the intended recipient, you are hereby notified that any reading, dissemination, distribution, copying, or other use of this communication or any of its attachments is strictly prohibited. If you have received this communication in error, please notify the sender immediately by replying to this message and deleting this message, any attachments, and all copies and backups from your computer. Disclaimer ID:MSKCC

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