BwForCluster MLS&WISO Production Slurm

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Revision as of 17:32, 5 October 2020 by S Richling (talk | contribs) (Partitions)
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1 General information about Slurm

2 Slurm Command Overview

Slurm commands Brief explanation
sbatch Submits a job and queues it in an input queue
squeue Displays information about active, eligible, blocked, and/or recently completed jobs
scontrol Displays detailed job state information
scancel Cancels a job

3 Job Submission

Batch jobs are submitted with the command:

$ sbatch <job-script>

A job script contains options for Slurm in lines beginning with #SBATCH as well as your commands which you want to execute on the compute nodes. For example:

#SBATCH --partition=single
#SBATCH --ntasks=1
#SBATCH --time=00:20:00
#SBATCH --mem=1gb
echo 'Hello world'

This jobs requests requests one core (--ntasks=1) and 1 GB memory (--mem=1gb) for 20 minutes (--time=00:20:00) on nodes provided by the partition 'single'.

If you want to convert Moab batch scripts to Slurm, you can find general information on this page. Specific information for the usage of Slurm on bwForCluster MLS&WISO Production is included in the following chapters.

3.1 Partitions

On bwForCluster MLS&WISO Production it is necessary to request a partition with '--partition=<partition_name>' on job submission. Within a partition job allocations are routed automatically to the most suitable compute node(s) for the requested resources (e.g. amount of nodes and cores, memory, number of GPUs). The devel partition is the default partition, if no partition is requested.

The partitions devel, single, and gpu-single are operated in shared mode, i.e. jobs from different users can run on the same node. Jobs can get exclusive access to compute nodes in these partitions with the "--exclusive" option. The partitions multi and gpu-multi are operated in exclusive mode. Jobs in these partitions automatically get exclusive access to the requested compute nodes.

When choosing the partition gpu-single or gpu-multi, the number of GPUs must be requested with the option "--gres=gpu:<number-of-gpus>".

Partition Node Access Policy Node Types Default Limits
devel shared standard ntasks=1, time=00:10:00, mem-per-cpu=1gb nodes=1, time=00:30:00
single shared standard, best, best-sky, best-cas, fat, fat-ivy ntasks=1, time=00:30:00, mem-per-cpu=1gb nodes=1, time=120:00:00
multi job exclusive standard, best, best-sky, best-cas nodes=2, time=00:30:00 nodes=128, time=48:00:00
gpu-single shared gpu, gpu-sky, gpu-cas ntasks=1, time=00:30:00, mem-per-cpu=1gb nodes=1, time=48:00:00
gpu-multi job exclusive gpu nodes=2, time=00:30:00 nodes=18, time=48:00:00

3.2 Constraints

If a job requires a certain Intel architecture, the architecture of compute nodes can be explicitly requested with "--constraint=<constraint_name>".

Constraint Meaning
ivy request nodes with architecture Ivy Bridge
has request nodes with architecture Haswell
sky request nodes with architecture Sky Lake
cas request nodes with architecture Cascade Lake

3.3 Examples

Here you can find some examples for resource requests in batch jobs. Most partitions allow the allocation of various node types. If you need a certain node types, adapt the memory request, the number of cores per nodes, and/or use the "--constraint" option.

3.3.1 Serial Programs

#SBATCH --partition=single
#SBATCH --ntasks=1
#SBATCH --time=120:00:00
#SBATCH --mem=4gb


  • Jobs with "--mem" below 60gb can run on all node types associated with the single partition.
  • If you increase the memory request, less node types may be available for the job.
  • If you need best nodes only, request for example more memory "--mem=70gb" and use "--constraint=has" to exclude standard as well as best-sky, best-cas, and fat-ivy nodes.

3.3.2 Multi-threaded Programs

#SBATCH --partition=single
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=16
#SBATCH --time=01:30:00
#SBATCH --mem=50gb


  • Jobs with "--ntasks-per-node" up to 16 and "--mem" below 60gb can run on all node types associated with the single partition.
  • If you increase "--ntasks-per-node" or "--mem", less node types may be available for the job, see 'Number of Cores' and 'Working Memory' in the CPU Nodes Hardware table.

3.3.3 MPI Programs

#SBATCH --partition=multi
#SBATCH --nodes=2
#SBATCH --ntasks-per-node=16
#SBATCH --time=12:00:00
#SBATCH --mem=50gb


  • "--mem" requests the memory per node.
  • Jobs with "--nodes=" up to 2, --ntasks-per-node" up to 16, and "--mem" below 60gb can run on all node types associated with the multi partition.
  • If you increase "--nodes", "--ntasks-per-node", or "--mem", less node types may be available for the job, see 'Number of Cores' and 'Working Memory' in the CPU Nodes Hardware table.

3.3.4 GPU Programs

#SBATCH --partition=gpu-single
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=40
#SBATCH --gres=gpu:4
#SBATCH --time=12:00:00
#SBATCH --mem=200gb


  • The number of GPUs is requested with the option "--gres=gpu:<number-of-gpus>"
  • It is also possible to request a certain GPU type with the option "--gres:gpu:<number-of-gpus>:<gpu-type>". For <gpu-type> put the 'GPU Type' listed in the last line of the GPU Nodes Hardware table.

4 Interactive Jobs

Interactive jobs must NOT run on the logins nodes, however resources for interactive jobs can be requested using srun. The following example requests an interactive session on 1 core for 2 hours:

$ srun --partition=single --ntasks=1 --time=2:00:00 --pty /bin/bash

After execution of this command wait until the queueing system has granted you the requested resources. Once granted you will be automatically logged on the allocated compute node.

If you use applications or tools which provide a GUI, enable X-forwarding for your interactive session with:

$ srun --partition=single --ntasks=1 --time=2:00:00 --pty /bin/bash --x11

Once the walltime limit has been reached you will be automatically logged out from the compute node.

5 Job Monitoring

5.1 Information about submitted jobs

For an overview of your submitted jobs use the command:


To get detailed information about a specific jobs use the command:

scontrol show job <jobid>

5.2 Interactive access to running jobs

If you like to see what happens on the compute node(s), you can enter access the allocated resources of a running job with:

$ srun --jobid=[jobid] --pty /bin/bash

Commands like 'top' show you the most busy processes on the node. To exit 'top' type 'q'.

To monitor your GPU processes use the command 'nvidia-smi'.

6 Job Feedback

Information will be provided soon.

7 Overview about free resources

Information will be provided soon.