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We are pleased to announce the availability of Slurm versions 25.11.6 and 25.05.8.
by Marshall Garey 14 May '26

14 May '26

We are pleased to announce the availability of Slurm versions 25.11.6 and 25.05.8. Fixes in these releases primarily cover various stability issues when reconfiguring or shutting down and improved support for newer libraries and compilers. The 25.11.6 release also includes a performance fix for scheduling with topology/block and a regression from 25.11.4 that could cause a "No records archived...but some found" message when archiving job data. The full list of changes are available in the CHANGELOG files for each version: https://github.com/SchedMD/slurm/blob/slurm-25.11/CHANGELOG/slurm-25.11.md https://github.com/SchedMD/slurm/blob/slurm-25.05/CHANGELOG/slurm-25.05.md Slurm can be downloaded from: https://github.com/SchedMD/slurm/releases -- Marshall Garey Senior System Software Engineer NVIDIA

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Technical Update: Native Slurm Simulation Environment Successfully Configured
by sami sami 14 May '26

14 May '26

Hi All, I am currently working on a single Linux machine running *Ubuntu 25.10* and am looking to conduct performance testing on the *Slurm backfill algorithm*. My objective is to simulate a cluster environment consisting of *1,024 nodes*. While researching existing solutions, I found that many modern Slurm-simulator implementations (such as various plugin-based designs) rely heavily on *Docker and Docker Compose*. However, I would like to avoid using containerization and instead run the simulation natively on my host OS. I understand that older versions of the Slurm source code included a native sim directory that allowed for simulations without external dependencies like Docker. Given this, I have the following technical questions: - *Native Compatibility:* Is it still feasible to compile and run a Slurm simulator natively on Ubuntu 25.10? - *Version Recommendations:* Would you recommend using a specific legacy version of Slurm that still contains the original simulation files, or is there a way to port that functionality to a more recent release? - *Configuration:* Are there specific build flags or configuration steps required to enable the simulated node environment (1,024 nodes) on a single machine without triggering the overhead of containerized networking? I would appreciate any guidance or documentation you could provide on achieving a high-node-count simulation in a "bare-metal" Linux environment. Best regards,

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inconsistent 'Requested node configuration is not available' error
by Paul Raines 14 May '26

14 May '26

In my cluster right now we have: $ sinfo ... pubgpu-req up 7-00:00:00 7 mix cobra,l40s-[01,03],luisa,rtx-03,sevilla,shelob pubgpu-req up 7-00:00:00 5 idle fiber,glaurung,gothmog,l40s-02,leo The following works fine: $ srun -p pubgpu-req -A sysadm --nodelist=cobra,l40s-02 --gres=gpu:1 -N 1 \ --ntasks-per-node=1 --mem=1G --time=1:00:00 --cpus-per-task=4 --pty /bin/bash srun: tres_per_node => gres/gpu:1 cobra[0]:~$ exit exit However just change the order of the nodelist and you get $ srun -p pubgpu-req -A sysadm --nodelist=l40s-02,cobra --gres=gpu:1 -N 1 \ --ntasks-per-node=1 --mem=1G --time=1:00:00 --cpus-per-task=4 --pty /bin/bash srun: tres_per_node => gres/gpu:1 srun: error: Unable to create step for job 8255390: Requested node configuration is not available More experimentation with this and it appears nodelist HAS to be in alphabetical order $ srun -p pubgpu-req -A sysadm --nodelist=l40s-02,leo,fiber \ --gres=gpu:1 -N 1 --ntasks-per-node=1 --mem=1G --time=1:00:00 \ --cpus-per-task=4 --pty /bin/bash srun: tres_per_node => gres/gpu:1 srun: error: Unable to create step for job 8255401: Requested node configuration is not available $ srun -p pubgpu-req -A sysadm --nodelist=fiber,l40s-02,leo \ --gres=gpu:1 -N 1 --ntasks-per-node=1 --mem=1G --time=1:00:00 \ --cpus-per-task=4 --pty /bin/bash srun: tres_per_node => gres/gpu:1 fiber[0]:~$ Surely there is no good reason for this? --------------------------------------------------------------- Paul Raines http://help.nmr.mgh.harvard.edu MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging 149 (2301) 13th Street Charlestown, MA 02129 USA The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Mass General Brigham Compliance HelpLine at https://www.massgeneralbrigham.org/complianceline <https://www.massgeneralbrigham.org/complianceline> . Please note that this e-mail is not secure (encrypted). If you do not wish to continue communication over unencrypted e-mail, please notify the sender of this message immediately. Continuing to send or respond to e-mail after receiving this message means you understand and accept this risk and wish to continue to communicate over unencrypted e-mail.

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SLURM config option to not tie up a host completely.
by Ron Gould 08 May '26

08 May '26

I have a user asking about a SLURM config setting that would allow a job to not tie up a node's unused resources, thereby allowing another job to run concurrently. User: On our cluster, our Fluent GPU jobs each use only 1 of the 2 GPUs on GPUServer[1,2]. Currently the node is fully allocated to whichever job lands on it first, leaving the second GPU, 38 CPU cores, and 270+ GB of RAM idle. Has anyone dealt with this? What options would facilitate this? Are there any gotchas or pitfalls?

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Moving a Slurm database from one slurm database host to another
by James A Allsopp 08 May '26

08 May '26

Hi, We'd like to move our Slurm database from its existing machine running mariadb-server-5.5.68 to another running mariadb-server-10.5.29-3, both of which are running slurm 24.11.7. We dumped the database successfully from the old server, reimported it into the new server using mysqldump and *mysql < db_dump.sql*. The new slurmdbd service was then started. The clusters have different names so there were a few inconsistencies, but when we started the new slurm cluster, we could see the jobs according to sacct (using the -M option) matched those of the original cluster, but none of the associated job steps were shown. I manually logged into the new database and could see the jobs in the job_table but it looked like the foreign key link had been broken in the step table as there were entries in that table. Am I missing some information about how to export and import properly? I was wondering if the import had triggered auto-increment on keys and that was breaking things? Ideally, we'd like to change the name of the cluster as well. Is that just a matter of altering the prefix on the relevant tables, which is something I can do by hand on the database dump before reimporting? For instance, changing the table <old_name>_event_table to <new_cluster_name>_event_table. Thanks James -- Dr James Allsopp | Research Platforms team IT Services | University of Sheffield I do not work Tuesday and Wednesday 3-5pm. I also send emails at odd times, but respond at your convenience.

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Slurm release candidate version 26.05.0rc1 is available for testing
by Tim Wickberg 07 May '26

07 May '26

We are pleased to announce the availability of Slurm release candidate 26.05.0rc1. To highlight some new features coming in 26.05: - New "srun --async" step mode that submits step processes to stepmgr to queue and eventually launch. This avoids issues with keeping a large number of srun processes backgrounded to queue up future step-based workflows. (This was previously described as "mini-batch" in the Slurm roadmap presentations.) - New topology/ring and topology/torus3d topology plugins. These implement a single-dimensional and three-dimensional topology respectively. - Slurm REST API - Add support for creating/updating/removing partitions, and for viewing the active slurmctld and slurmdbd configurations. - Dynamic Memory Resizing. A job can now release memory (and have the cgroup limits updated) using 'scontrol update' while running. A new "sbatch --mem-update=<margin>@<delay>" option can also automatically reduce the memory limit to the current usage plus a given margin percentage after a specified time. - Add topology-based sorting for node ranks when using dynamic nodes with the topology plugins. This is also available generically for topology/flat (no topology) with a new alpha_step_rank option. - Add an optimized single-node path through the scheduling logic for increased performance. - Expanded the openmetrics (Prometheus) nodes, partitions, and jobs endpoints with gpu allocation statistics. This is the first release candidate of the upcoming 26.05 release series, and represents the end of development for this release, and a finalization of the RPC and state file formats. If any issues are identified with this release candidate, please report them through https://support.schedmd.com against the 26.05.x version and we will address them before the first production 26.05.0 release is made. Please note that the release candidates are not intended for production use. A preview of the updated documentation can be found at https://slurm.schedmd.com/archive/slurm-master/ . Slurm can be downloaded from https://github.com/SchedMD/slurm/releases. The changelog for 26.05 can be found here: https://github.com/SchedMD/slurm/blob/master/CHANGELOG/slurm-26.05.md -- Tim Wickberg Director, System Software, Slurm + Slinky, NVIDIA

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cgroup/v2 regression in 25.11.2 — memory.peak read disabled after first task
by Emyr James 06 May '26

06 May '26

Dear all, Heads-up for anyone running 25.11.2 with cgroup/v2 + jobacct_gather/cgroup: there's a regression in the recent series that effectively disables memory.peak accounting for every task after the first one per slurmstepd. The commit is f2d05c08e6 ("cgroup/v2 - Remove static qualifier from variable", ticket 23646, cherry-picked from e1835a1602). It dropped static from memory_peak_interface in cgroup_p_task_get_acct_data while leaving interfaces_checked static. The function now looks like: bool memory_peak_interface = false; static bool interfaces_checked = false; ... if (!interfaces_checked) { memory_peak_interface = cgroup_p_has_feature(CG_MEMCG_PEAK); interfaces_checked = true; } ... if (memory_peak_interface) { common_cgroup_get_param(..., "memory.peak", ...); } interfaces_checked persists across calls; memory_peak_interface no longer does. So the feature-probe block runs exactly once. From the second call onward memory_peak_interface is a fresh stack-local set to false, and the memory.peak read in the second if is skipped. stats->memory_peak ends up INFINITE64 for every task except the first one ever sampled. User-visible effect: MaxRSS in sacct stops reflecting the kernel-tracked peak and falls back to polling memory.current — which, at typical jobacct_gather intervals, routinely misses short-lived peaks. Which is of course exactly the problem memory.peak was added to solve (see the 2024 thread that prompted the original implementation: https://groups.google.com/g/slurm-users/c/BX1_4bztrJA) One-line fix is to put static back on memory_peak_interface. Or, arguably more robust, drop the interfaces_checked cache entirely and run the feature probe on every call — the cost is one access()-equivalent per accounting poll, basically free. he original v2 implementation in ba34862a40 was great, thanks for that — this looks like a small static-qualifier slip on the way through a cleanup. Cheers, Emyr James Head of Scientific IT CRG - Centre for Genomic Regulation

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slurmdbd and slurmctld prevent alma9 login
by Pols, Maarten 06 May '26

06 May '26

Dear Community, Our Slurm cluster has been running without any issues for several months on version 25.05.3. Last Friday, we experienced a power outage which required us to restart the server. After the restart, we were unable to log in to the master node. Eventually, we managed to access the system via a safe mode workaround. Through a process of elimination, we identified the slurmdbd and slurmctld services as the root cause of the issue. Would you happen to have any idea what might have caused this behavior? We have since upgraded to version 25.11.5, which appears to be running smoothly. However, we would still like to understand the underlying cause of the problem. Thank you in advance for your help. Kind regards, Maarten

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Jobs canceling when nodes become unreachable – need guidance
by Pharthiphan Asokan 05 May '26

05 May '26

Hi, We’re seeing an issue where jobs submitted via salloc are automatically cancelled when a compute node becomes temporarily unreachable. Our goal is to keep jobs pending or requeued instead of being cancelled outright when a node drops offline briefly Slurm sometimes cancels the job rather than requeuing it when the node is marked DOWN/ DRAIN/ DRAINING*. Is there a recommended configuration or additional parameter that ensures jobs remain pending/requeued until the node returns, rather than being cancelled? Any insights or examples from similar setups would be greatly appreciated. Regards, Pharthiphan

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How to track solver usage in Slurm
by fernando.seguro＠rtx.com 23 Apr '26

23 Apr '26

I don't see an easy way of tracking this in slurm. I tried using the --comment="slover" directive, but this gets mapped to the "derived_es" column in the database, which is reserved for job info on errors, from what I read. This would make a good enhancement request. Where would I submit that? Something like: SBATCH --solver=fluent or SBATCH --solver=LSDyna This would be very helpful for tracking solver usage without having to use the job-name. Great for reporting. Please let me know if someone else has requested this previously. If anyone has figured out a way to do it, please share. thanks

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