How to use Slurm¶
In this page we'll list some common Slurm interactions to run, cancel or monitor jobs.
How to monitor jobs¶
Monitor the status of cluster's nodes¶
The command sinfo can be used to monitor the state of each node, including partitions, time limits, state, and names of the nodes in that partition:
$ sinfo
PARTITION AVAIL TIMELIMIT NODES STATE NODELIST
admin up infinite 1 idle node121
department_only up 3-00:00:00 3 mix node[132-133,135]
department_only up 3-00:00:00 18 idle node[103,112-114,116,120,123-124,126,130,134,137-143]
multicore up 6:00:00 2 idle node[106-107]
students* up 1-00:00:00 11 idle node[108-111,122,145-149,151]
Node states
For a full list of the meaning of each state, refer to Slurm's official docs. Some of the common states are:
*: the node is presently not responding and will not be allocated any new work;ALLOCATED: the node has been allocated to one or more jobs;- {
DOWN,DRAINED,FAIL,INVAL}: the node is unavailable for use. Slurm can automatically place nodes in this state if some failure occurs, so inform an admin ASAP; DRAINING: the node is currently allocated a job, but will not be allocated additional jobs;- {
IDLE,MIXED}: the node is not allocated to any jobs and is available for use; UNKNOWN: the Slurm controller has just started and the node's state has not yet been determined.
Monitor the state of jobs¶
The command squeue can be used to view information about jobs located in the Slurm scheduling queue, including job ID, partition, name, user, state, execution time, node name:
$ squeue
JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON)
326 debug sleep guest R 0:03 1 node123
Job states
The ST column shows the states of the jobs. For a full list of the meaning of each state, refer to Slurm's official docs.
Some of the common states are:
- {
BF,F,NF,PR}: the job has failed to launch or complete; OOM: the job experienced out of memory error;R: the job is running;CG: the job is in the process of completing. Some processes on some nodes may still be active.
How to submit jobs¶
How to submit a non-interactive job¶
A non-interactive job can be run using srun <commands>.
You have to remember to use the -p or --partition flag, alongside the requirements of the job.
A job with no requirements can be run without further arguments:
$ srun -p <partition> bash -c "echo 'It works! My name is:'; hostname"
It works! My name is:
node116
A job with certain requirements needs all necessary resources to be specified:
$ srun -p <partition> --gpus=2 bash -c "echo 'It works! Here is a summary of my GPUs:'; nvidia-smi"
It works! Here is a brief of my GPUs:
Tue Mar 11 16:13:07 2025
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 570.86.16 Driver Version: 570.86.16 CUDA Version: 12.8 |
|-----------------------------------------+------------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 Quadro RTX 6000 Off | 00000000:41:00.0 Off | 0 |
| N/A 27C P8 20W / 250W | 1MiB / 23040MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
| 1 Quadro RTX 6000 Off | 00000000:C1:00.0 Off | 0 |
| N/A 25C P8 13W / 250W | 1MiB / 23040MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+
Read Slurm's official docs for a list of all the available flags. Some common requirements are the following:
--gpus: the minimum number of GPUs the node must have to run the job;--mem: the real memory required per node, in MBs;
How to submit a non-interactive container¶
You can do it using Singularity.
An interactive job can be run using srun singularity run <container_path> <commands>.
In this example, the hostname command will be executed into the pytorch container run on a node:
$ srun singularity run docker://pytorch/pytorch:2.6.0-cuda12.6-cudnn9-devel hostname
INFO: Using cached SIF image
==========
== CUDA ==
==========
CUDA Version 12.6.3
Container image Copyright (c) 2016-2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
This container image and its contents are governed by the NVIDIA Deep Learning Container License.
By pulling and using the container, you accept the terms and conditions of this license:
https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license
A copy of this license is made available in this container at /NGC-DL-CONTAINER-LICENSE for your convenience.
WARNING: The NVIDIA Driver was not detected. GPU functionality will not be available.
Use the NVIDIA Container Toolkit to start this container with GPU support; see
https://docs.nvidia.com/datacenter/cloud-native/ .
node111
How to submit an interactive container¶
You can do it using Singularity.
An interactive job can be run using srun --pty singularity shell <container_path>, where the --pty flag spawns a pseudo-terminal.
In this example, the pytorch container will be executed on a node with 2 GPUs.
The --nv flag tells Singularity to mount the GPUs:
$ srun --gpus=2 --pty singularity shell --nv docker://pytorch/pytorch:2.6.0-cuda12.6-cudnn9-devel
INFO: Using cached SIF image
Singularity> nvidia-smi
Wed Mar 19 16:15:07 2025
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 570.124.06 Driver Version: 570.124.06 CUDA Version: 12.8 |
|-----------------------------------------+------------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 Quadro RTX 6000 Off | 00000000:41:00.0 Off | 0 |
| N/A 29C P0 54W / 250W | 1MiB / 23040MiB | 3% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
| 1 Quadro RTX 6000 Off | 00000000:C1:00.0 Off | 0 |
| N/A 29C P0 56W / 250W | 1MiB / 23040MiB | 4% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+
Singularity>
How to cancel jobs¶
Cancel a job by its job ID¶
A particular job can be canceled using the scancel <job_id> command:
$ squeue
JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON)
326 debug sleep debug R 0:03 1 node123
$ scancel 326
$ squeue
JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON)
Cancel all the jobs of a user¶
All the jobs of a user can be canceled using the -u or --user flag, by typing scancel --user <user_id> command: