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Slurm

Slurm Workload Manager is a free and open-source job scheduler for Linux and Unix-like systems, widely used by supercomputers and clusters.

Official slurm documentation: https://slurm.schedmd.com/documentation.html

Slurm on Euler

On Euler, Slurm version 25.05 is used since 13. Jan 2026.

Euler runs jobs non-exclusively on compute nodes. This means multiple jobs can run on the same node at the same time. We do this to maximize resource utilization and efficiency.

Resource Requests

Specify your resource requirements (CPUs, memory, time, etc.) as accurately as possible; as specific as required, as loosely as possible. The smaller a job's footprint, the quicker it will start. Don't specify CPU types, GPU types, partitions, or other specific resources unless your job really depends on them.

Ignore Partitions

Don't specify partitions. Slurm internally uses partitions (queues) to manage resources, but as a user you best ignore them.

GPU Nodes Access

GPU nodes are only available to shareholders, which invest in GPU hardware.

Usage

Main client commands:

  • srun: Get a job allocation and execute an application
  • sbatch: Submit a batch script to Slurm
  • squeue: View the job queue
  • scancel: Remove a job from the queue

Additional commands:

  • salloc: Get a job allocation
  • sacct: View accounting data
  • sbcast: Broadcast file to a job's compute nodes
  • sinfo: View nodes and partitions
  • sstat: Display status information of a running job/step

Custom extensions on Euler:

Web interfaces:

Common options for sbatch and srun:

Option Description
-t, --time=<time> Maximum runtime (default: 1 hour)
-n, --ntasks=<number> Maximum number of tasks (default: 1)
-c, --cpus-per-task=<ncpus> CPUs per task (default: 1)
--mem-per-cpu=<size>[units] Memory per CPU (default: MB)
-N, --nodes=<minnodes> Minimum nodes (default: 1)
--gpus-per-task=<number> GPUs per task (default: 0)
--x11 Enable X11 forwarding
--tmp=<size>[units] Temporary disk space (default: 0)
-o, --output=<filename> Output file for job stdout (default: slurm-%j.out)
-e, --error=<filename> Output file for job stderr (default: slurm-%j.err)
--wrap=<command_string> Wrap command string in a shell script
-A, --account=<share_name> Specify the account to charge the job to (default: your default account)
-d, --dependency=<dependency> Specify job dependencies (e.g., afterok:<job_id>)

Jobs inherit the environment variables from the shell that submits them.

Interactive sessions

To start an interactive session, use srun with the --pty option: 

srun --pty bash
--pty allocates a pseudo-terminal for the session, allowing you to interact with the shell as if it were a local terminal. You can specify additional options like --ntasks, --cpus-per-task, etc. to customize the resources.

This is very useful for debugging or running commands interactively on a compute node.

Submitting parallel jobs (srun)

To submit a parallel job, use srun with the --ntasks option:

srun --ntasks=5 --cpus-per-task=8 nproc

8
8
8
8
8
This command runs nproc in 5 tasks, each with 8 CPUs. The nproc command prints the number of available CPUs in the current task.

Submitting batch jobs (sbatch)

To submit a batch job, create a script file (e.g., batch_script.txt) with the following content:

#!/bin/bash
#SBATCH --ntasks=5
#SBATCH --cpus-per-task=8
srun nproc
Then submit the script using sbatch:

sbatch batch_script.txt

sbatch will put the job in the queue and execute it when resources are available. The output will be written to a file named slurm-<job_id>.out in the current directory. sbatch does not wait for the job to finish; it returns immediately after submitting the job; use --wait to make it wait. (You can check the job status with squeue.)

Note: The #SBATCH directives must be placed before the first executable command in the script.

Note: Without srun, the job will not run in parallel across all tasks. It will only run the command once, using the total resources requested.

Submitting job arrays (sbatch --array)

A job array allows you to submit multiple similar jobs with a single command. This is useful for running the same job with different parameters or datasets.

sbatch --array=1-10 batch_script.txt
This command submits 10 jobs, each with a different index (1 to 10). You can access the index in the script using the environment variable $SLURM_ARRAY_TASK_ID.

You can find the possible options for job arrays in the Slurm documentation.

Submitting MPI jobs

Slurm supports MPI (Message Passing Interface) jobs. See https://slurm.schedmd.com/mpi_guide.html#open_mpi for more information.

Submitting GPU jobs

GPU Nodes Access

GPU nodes are only available to shareholders, which invest in GPU hardware.

To submit a job that requires GPUs, use the --gpus option:

srun --gpus=1 nvidia-smi
This command requests 1 GPU and runs nvidia-smi to display GPU information. You can also specify the type(s) of GPU(s) you want to use, e.g., --gpus=a100,v100:1 for 1x A100 or 1x V100 GPU.

GPU Model Slurm Identifier
Nvidia RTX 2080 Ti rtx_2080
Nvidia TITAN RTX nvidia_titan_rtx
Nvidia Quadro RTX 6000 rtx_6000
Nvidia RTX 3090 rtx_3090
Nvidia Tesla A100 (40 GB) a100
Nvidia Tesla A100 (80 GB) a100_80gb
Nvidia RTX 4090 rtx_4090
Nvidia RTX Pro 6000 pro_6000

Nvidia RTX Pro 6000

Programs compiled with CUDA 12 libraries will not run on Blackwell GPUs such as the Nvidia RTX Pro 6000. Since CUDA 13 is relatively new and not used yet by many programs, we opted to not open the new RTX Pro 6000 GPUs to all jobs since we expect most would fail.

Only batch jobs explicitly requesting the RTX Pro 6000 GPU can therefore run on these nodes, e.g., 

srun --gpus:pro_6000:1 my_cuda13_program
expectedly until mid-2026.

Accounting and Shares

If you are a member of multiple shareholder groups, you can select which group a job should be scheduled and accounted to, by passing slurm the option -A <share_name>. To configure a default group, specify the following in your ~/.slurm/defaults file (create it if it does not exist and replace <share_name> with your preferred default share): 

account=<share_name>
The public share, which is open to all members of ETH, is named "public".

Custom extensions on Euler

myjobs

Use myjobs -j <job_id> to view detailed information of a job. It provides a human-friendly summary of Slurm jobs, improving on squeue's output.

Example of a pending job

$ myjobs -j 6038307
Job information
 Job ID                          : 6038307
 Status                          : PENDING
 Running on node                 : None assigned
 User                            : nmarounina
 Shareholder group               : es_cdss
 Slurm partition (queue)         : gpu.24h
 Command                         : script.sbatch
 Working directory               : /cluster/home/nmarounina
Requested resources
 Requested runtime               : 08:00:00
 Requested cores (total)         : 12
 Requested nodes                 : 1
 Requested memory (total)        : 120000 MiB
Job history
 Submitted at                    : 2023-01-09T15:56:09
 Started at                      : Job did not start yet
 Queue waiting time              : 8 s
 Resource usage
 Wall-clock                      : 
 Total CPU time                  : -
 CPU utilization                 : - %
 Total resident memory           : - MiB
 Resident memory utilization     : - %

Example of a running job

$ myjobs -j 6038307
Job information
 Job ID                          : 6038307
 Status                          : RUNNING
 Running on node                 : eu-g3-022
 User                            : nmarounina
 Shareholder group               : es_cdss
 Slurm partition (queue)         : gpu.24h
 Command                         : script.sbatch
 Working directory               : /cluster/home/nmarounina
Requested resources
 Requested runtime               : 08:00:00
 Requested cores (total)         : 12
 Requested nodes                 : 1
 Requested memory (total)        : 120000 MiB
Job history
 Submitted at                    : 2023-01-09T15:56:09
 Started at                      : 2023-01-09T15:56:38
 Queue waiting time              : 29 s
 Resource usage
 Wall-clock                      : 00:00:36
 Total CPU time                  : 00:00:00
 CPU utilization                 : 0%
 Total resident memory           : 2.94 MiB
 Resident memory utilization     : 0%

my_share_info

Use my_share_info to list the shareholder groups you belong to.

Example output

$ my_share_info
You are a member of the following shareholder groups on Euler:
es_example
es_euler

get_inefficient_jobs

Use get_inefficient_jobs to find jobs that are running inefficiently, i.e. using more resources than requested.

Example output

$ get_inefficient_jobs
Looking for user dohofer
37279906
37301756
37301756
37301756
37301756
37305670
37305759
37306347
37306347
37306347
37306347
37306347
37306347
37306347
37306347
37498300
37602385

Average CPU used (higher better): 12.1% (equivalent to wasting 4.0 cores)
Average system RAM used (higher better): 25.2% (equivalent to wasting 14.0 GB)
Average GPU used (higher better): 100.0% (equivalent to wasting 0.0 GPUs)
Average GPU RAM used (higher better): 100.0% (equivalent to wasting 0.0 GB)
CPU to GPU ratio (lower better): 0.0% (equivalent to 0.0 GPUs blocked)
RAM to GPU ratio (lower better): 0.0% (equivalent to 0.0 GPUs blocked)
Number of short jobs (lower better): 1

Known issues

ReqNodeNotAvail

Sometimes Slurm reports that requested nodes are not available and lists some nodes. It looks something like this: 

JOBID PARTITION  NAME    USER   ST       TIME  NODES NODELIST(REASON)
12345 normal.12  my_job  myname PD       0:00      1 (ReqNodeNotAvail, UnavailableNodes:eu-a2p-[001,103],eu-g9-091-2)
If you have not requested these nodes explicitly, this message by Slurm is misleading. The job is actually waiting in the queue. No user action is required; just patience.