Slurm Workload manager is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small Linux clusters. As a cluster workload manager, Slurm has three key functions.
Bioinformatics Center uses unmodified version of Slurm on sampo.uef.fi computing cluster. This guarantees that the most of the tutorials and guides found from the Internet are applicable as-is. The most obvious starting place to search for usage information is documentation section of the Slurm own website Slurm Workload Manager.
In this example we will run simple MATLAB code on one computing node.
% Creates a 10x10 Magic square M = magic(10); M
Here we have specified the batch script with few basic options. It is important to reserve the amount of RAM that you'll need and estimate the runtime of your code. Optionally you can give name for your job.
#!/bin/bash #SBATCH --ntasks 1 # Number of task #SBATCH --time 5 # Runtime in minutes. #SBATCH --mem=2000 # Reserve 2 GB RAM for the job #SBATCH --partition serial # Partition to submit module load matlab/R2018b # load modules matlab -nodisplay < matlab.m # Execute the script
User can submit the job to the compute queue with the sbatch command.
User can monitor the state of the job with the squeue command. JOBID is provided by the sbatch commmand when the job is submitted.
squeue -j <jobid>
Scontrol command gives some information about the job, queue (partition) or the compute nodes. This tool can also modify various parameters of submitted job (runtime for example).
scontrol show node
scontrol show node
scontrol show partition
scontrol show job <jobid>
scontrol update jobid=<job_id> TimeLimit=<new_timelimit>
Seff command will give the report of the completed job on how much resources it consumed. The reported information are CPU wall time, job runtime and memory usage.