slurm-users December 2025

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15 participants
13 discussions

Problems with salloc
by Gestió Servidors 10 Dec '25

10 Dec '25

Hello, I am getting some problems with "salloc" execution. My cluster is running SLURM v23.11.0. I'm going to explain problems: 1. My first problem is that until some previous version (I can't remember what version exactly), when I ran a "salloc", I got a console inside the assigned host. Then, I could execute whatever I wanted. However, now, after execute "salloc" (without forcing host), SLURM always tries to assign me the last host where a job has been executed. But if that host is now powered off, salloc waits and waits but not tries to connect to other host 2. Second problem is that previous execution gives me a host (the host is powered on), my session continues in the allocation host, not in the assigned host. So if I want to execute some program, I need to run with "srun". Is there anyway to go directly to the assigned host? 3. Third problem is a question. How can I limit the hosts where I (as cluster admin) allow to run a "salloc"? For example, I would like that when a user runs a "salloc", it were execute always in a partition with "x" hosts, avoiding SLURM to assign me a host of the list of hosts. Thanks.

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Invalid generic resource (gres) specification after RMA
by Lee 04 Dec '25

04 Dec '25

Good afternoon, I have a cluster that is managed by Base Command Manager (v10) and it has several Nvidia DGXs. dgx09 is a problem child. The entire node was RMA'd and now it no longer behaves the same as my other DGXs. I think the below symptoms are caused by a single underlying issue. *Symptoms : * 1. When I look at our 8 non-MIG DGXs, via `scontrol show node=dgxXY | grep Gres`, 7/8 DGXs report "Gres=gpu:*H100*:8(S:0-1)" while dgx09 reports " Gres=gpu:*h100*:8(S:0-1)" 2. When I submit a job to this node, I get : $ srun --reservation=g09_test --gres=gpu:2 --pty bash srun: error: Unable to create step for job 105035: Invalid generic resource (gres) specification ### No job is running on the node, yet AllocTRES shows consumed resources... $ scontrol show node=dgx09 | grep -i AllocTRES *AllocTRES=gres/gpu=2* ### dgx09 : /var/log/slurmd contains no information ### slurmctld shows : root@h01:# grep 105035 /var/log/slurmctld [2025-11-13T07:44:56.380] sched: _slurm_rpc_allocate_resources JobId=105035 NodeList=dgx09 usec=3420 [2025-11-13T07:44:56.482] _job_complete: JobId=105035 WTERMSIG 1 [2025-11-13T07:44:56.483] _job_complete: JobId=105035 done *Configuration : * 1. gres.conf : # This section of this file was automatically generated by cmd. Do not edit manually! # BEGIN AUTOGENERATED SECTION -- DO NOT REMOVE AutoDetect=NVML NodeName=dgx[01,02] Name=gpu Type=1g.20gb Count=32 AutoDetect=NVML NodeName=dgx[03-10] Name=gpu Type=h100 Count=8 AutoDetect=NVML # END AUTOGENERATED SECTION -- DO NOT REMOVE 2. grep NodeName slurm.conf root@h01:# grep NodeName slurm.conf NodeName=dgx[01,02] RealMemory=2063937 Boards=1 SocketsPerBoard=2 CoresPerSocket=56 ThreadsPerCore=2 MemSpecLimit=30017 Gres=gpu:1g.20gb:32 Feature=location=local NodeName=dgx03-10] RealMemory=2063937 Boards=1 SocketsPerBoard=2 CoresPerSocket=56 ThreadsPerCore=2 MemSpecLimit=30017 Gres=gpu:H100:8 Feature=location=local 3. What slurmd detects on dgx09 root@dgx09:~# slurmd -C NodeName=dgx09 CPUs=224 Boards=1 SocketsPerBoard=2 CoresPerSocket=56 ThreadsPerCore=2 RealMemory=2063937 UpTime=8-00:39:10 root@dgx09:~# slurmd -G slurmd: gpu/nvml: _get_system_gpu_list_nvml: 8 GPU system device(s) detected slurmd: Gres Name=gpu Type=h100 Count=1 Index=0 ID=7696487 File=/dev/nvidia0 Cores=0-55 CoreCnt=224 Links=-1,0,0,0,0,0,0,0 Flags=HAS_FILE,HAS_TYPE,ENV_NVML slurmd: Gres Name=gpu Type=h100 Count=1 Index=1 ID=7696487 File=/dev/nvidia1 Cores=0-55 CoreCnt=224 Links=0,-1,0,0,0,0,0,0 Flags=HAS_FILE,HAS_TYPE,ENV_NVML slurmd: Gres Name=gpu Type=h100 Count=1 Index=2 ID=7696487 File=/dev/nvidia2 Cores=0-55 CoreCnt=224 Links=0,0,-1,0,0,0,0,0 Flags=HAS_FILE,HAS_TYPE,ENV_NVML slurmd: Gres Name=gpu Type=h100 Count=1 Index=3 ID=7696487 File=/dev/nvidia3 Cores=0-55 CoreCnt=224 Links=0,0,0,-1,0,0,0,0 Flags=HAS_FILE,HAS_TYPE,ENV_NVML slurmd: Gres Name=gpu Type=h100 Count=1 Index=4 ID=7696487 File=/dev/nvidia4 Cores=56-111 CoreCnt=224 Links=0,0,0,0,-1,0,0,0 Flags=HAS_FILE,HAS_TYPE,ENV_NVML slurmd: Gres Name=gpu Type=h100 Count=1 Index=5 ID=7696487 File=/dev/nvidia5 Cores=56-111 CoreCnt=224 Links=0,0,0,0,0,-1,0,0 Flags=HAS_FILE,HAS_TYPE,ENV_NVML slurmd: Gres Name=gpu Type=h100 Count=1 Index=6 ID=7696487 File=/dev/nvidia6 Cores=56-111 CoreCnt=224 Links=0,0,0,0,0,0,-1,0 Flags=HAS_FILE,HAS_TYPE,ENV_NVML slurmd: Gres Name=gpu Type=h100 Count=1 Index=7 ID=7696487 File=/dev/nvidia7 Cores=56-111 CoreCnt=224 Links=0,0,0,0,0,0,0,-1 Flags=HAS_FILE,HAS_TYPE,ENV_NVML *Questions : * 1. As far as I can tell, dgx09 is identical to all my non-MIG DGX nodes in terms of configuration and hardware. Why does scontrol report it having 'h100' with a lower case 'h' unlike the other dgxs which report with an upper case 'H'? 2. Why is dgx09 not accepting GPU jobs and afterwards it artificially thinks that there are GPUs allocated even though no jobs are on the node? 3. Are there additional tests / configurations that I can do to probe the differences between dgx09 and all my other nodes? Best regards, Lee

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Doubts Regarding Definition of Metrics AveRSS and AveDiskWrite
by Manuel G. Marciani 03 Dec '25

03 Dec '25

Hello, fellow users: I have been using Slurm for the past three years, but recently I bumped into a doubt. I am using Slurm's (version 23.02.7) collected metrics (jobacct_gather/linux) to do a performance analysis of an application. I have read the documentation regarding the metrics (https://slurm.schedmd.com/sacct.html) but still find the Ave* metrics confusing, and more specifically the AveRSS and AveDiskWrite. AveDiskWrite is defined as "Average number of bytes written by all tasks in job." So, if I double the workload, which say that it had x avediskwrite, I should observe 2x. So far it is what I observed. But, then, if I double the resources while maintaining the workload I observe again x, and not 2x. So my suspicion is that the metric is the sum of written bytes across time, then divided by the number of nodes. But then with AveRSS, defined as "Average resident set size of all tasks in job," I observe what I expected with AveDiskWrite. That is, that this metric scales with the workload irrespective of the resources it has available. So I am not sure what the "Ave" references here. I would be thankful if someone could clarify the behavior, and even more grateful if someone could point me where in the code these metrics are aggregated and processed to be stored in the database. Many thanks, Manu. -- Manuel G. Marciani - マルシアニ·マヌエル First Stage Reseacher at Computational Earth Sciences (CES) - Earth Sciences Department Barcelona Supercomputing Center - Centro Nacional de Supercomputación Ph.D Student at Departament d'Arquitectura de Computadors (DAC) - Facultat d'Informàtica de Barcelona (FIB) Universitat Politècnica de Catalunya (UPC) BSC building Plaça Eusebi Güell, 1-3, 08034 Barcelona, Spain Desk BSC-PL0-6-20/8 mail to: manuel.gimenez(a)bsc.es mail to: manuel.gimenez.de.castro(a)upc.edu mail to: manuel.marciani(a)a.riken.jp mail to: manuel.gimenez.de.castro.marciani(a)hu-berlin.de

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