Job submission with SLURM

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The three ways to access computing resources are

  1. Submit a job through command line
  2. Submit a job through a job bash script using #SBATCH pragmas
  3. Get an interactive session on a compute node

Basic job submission

A basic job submission command consists of three parts:

sbatch SLURM options Job

where

sbatch   is the SLURM submit command.
SLURM options   are for requesting resources and defining job-related options.
Job   is a computing job to be submitted.


Here is an example:

sbatch -n 1 --time=04:00:00 --mem-per-cpu=4096 --wrap="python myscript.py"

When the job is submitted, LSF shows job's information:

$ sbatch -n 1 --time=04:00:00 --mem-per-cpu=4096 --wrap="python myscript.py"
Submitted batch job 3582287

The output includes a unique JobID, e.g., 3582287.

Note: The JobID is important for monitoring or reporting issues. It is also integrated in the name of the SLURM output file. Please don't delete the SLURM output file unless you are sure that the job was running fine.

Job

A job can be one of the following:

Job Command Examples of job submission command
a single Linux command cmd sbatch --wrap="ls"
a command or program with its arguments cmd arg1 arg2 sbatch --wrap="echo hello"
multiple commands "cmd1 ; cmd2" sbatch --wrap="date; pwd; ls -l"
piped command "cmd1 | cmd2" wc -l"
a command with I/O redirection, quote "cmd<in >out" sbatch --wrap="du -sk /scratch > du.out"
a here document, passed via "<<" << EOF ... EOF
a shell script, passed via "<" < script sbatch < hello.sh


SLURM options

Requesting resources

Resources Format Default values
Maximum run time --time HH:MM:SS 04:00:00 (4h), max. 360h
Number of processors -n nprocs 1 processor
Memory --mem-per-cpu=1024 1024 MB per core
Local scratch space --tmp=1024 1024 MB

Note: Please note that users cannot request the full memory of a node, as some of the memory is reserved for the operating system of the compute nodes that runs in memory. Therefore if a user for instance requests 256 GiB of memory, then job will not be dispatched to a node with 256 GiB of memory, but on a node with 512 GiB memory or more. As a general rule, jobs that request ~3% less memory than a node has can run on that node type. For instance, on a node with 256 GiB of memory, you can request up to 256*0.97 GiB = 248.32 GiB.

Note: Unlike memory, the batch system does not reserve any disk space for this scratch directory by default. If your job is expected to write large amounts of temporary data (say, more than 250 MB) into $TMPDIR — or anywhere in the local /scratch file system — you must request enough scratch space

Other SLURM options

-o outfile append job’s standard output to outfile
-e errfile append job’s error messages to errfile
-J jobname assign a jobname to the job
--mail-type=BEGIN,END,FAIL send an email when the job begins/ends/fails

SLURM-LSF submission line advisor can assist your to find SLURM options you need.

Job script and #SBATCH pragmas

Create a job script called job_script.sbatch

#!/bin/bash
#SBATCH -n 24                     # 24 cores
#SBATCH --time 08:00:00                   # 8-hour run-time
#SBATCH --mem-per-cpu=4000     # 4000 MB per core
#SBATCH -J analysis1
#SBATCH -o analysis1.out
#SBATCH -e analysis1.err
#SBATCH --mail-type=END,FAIL

source /cluster/apps/local/env2lmod.sh  # Switch to the new software stack
module load gcc/6.3.0 openmpi/4.0.2     # Load modules
cd /path/to/execution/folder            # Change directory
mpirun myprogram arg1                   # Execute the program

Submit a job

$ sbatch < job_script.bsub

The options specified on the command line take precedence over the options in the job script.

$ sbatch -n 36 < job_script.bsub

Interactive session on a compute node

To run a quick test or a benchmark, you can request an interactive session on a compute node by using

srun --pty

For example:

[nmarounina@eu-login-43 ~]$ srun -n 4 --time=01:00:00 --pty bash
srun: job 3634650 queued and waiting for resources
srun: job 3634650 has been allocated resources
[nmarounina@eu-a2p-074 ~]$ 

Further reading

Helper


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