SLURM user guide

💡 Please have a look at your tutorial for beginners: tutorials/snakemake

SLURM is the queue manager used on the ABiMS HPC Cluster. You must use SLURM to submit jobs to the cluster.

All the commands presented in this guide are to be used from the host ssh.sb-roscoff.fr

SLURM partitions and nodes

The ABiMS HPC Cluster is organized into several SLURM partitions. Each partition gathers a set of compute nodes that have similar usage.

Partitions	Time out	Max resources / user	Purpose
`fast`	<= 24 hours	cpu=300, mem=1500GB	Default - Regular jobs
`long`	<= 30 days	cpu=300, mem=1500GB	Long jobs
`bigmem`	<= 60 days	mem=2500GB	On demand - For jobs requiring a lot of RAM
`clc`	<= 30 days	cpu=300, mem=1500GB	On demand - Access CLC Assembly Cell
`gpu`	<= 10 days	cpu=300, mem=1500GB	On demand - Access GPU cards

The default values

Param	Default value
`--mem`	2GB
`--cpus`	1

Submitting a job to the cluster

They are two commands to submit a job to the cluster:

srun to run jobs interactively sbatch to submit a batch job

Submit a job using `srun`

To learn more about the srun command, see the official documentation

Usage: stand alone

The job will start immediately after you execute the srun command. The outputs are returned to the terminal. You have to wait until the job has terminated before starting a new job. This works with ANY command.

srun hostname

💡 This example will show you that the job is running on one node and not on the login node.

Usage: interactif

If an interaction is needed:

module load r
srun --mem 20GB --pty R

--pty: will keep the interaction possible
--mem 20GB: will allow 20GB of memory to your job instead of the 2GB by default

Submit a job using `sbatch`

To learn more about the sbatch command, see the official documentation

Usage

The job starts when resources are available. The command only returns the job id. The outputs are sent to file(s). This works ONLY with shell scripts. The batch script may be given to sbatch through a file name on the command line, or if no file name is specified, sbatch will read in a script from standard input.

Batch scripts rules

The script can contain srun commands. Each srun is a job step. The script must start with shebang (#!) followed by the path of the interpreter

#!/bin/bash

#!/usr/bin/env python

The execution parameters can be set within the shell bowtie2.sbatch itself:

#!/bin/bash
#
#SBATCH --mem 40GB
srun bowtie2 -x hg19 -1 sample_R1.fq.gz -2 sample_R2.fq.gz -S sample_hg19.sam

sbatch bowtie2.sbatch

The scripts can contain slurm options just after the shebang but before the script commands → #SBATCH

Note that the syntax #SBATCH is important and doesn't contain any ! (as in the Shebang)

Advice: We recommend to set as many parameters as you can in the script to keep a track of your execution parameters for a future submission.

Execution parameters

These parameters are common to the commands srun and sbatch.

Parameters for log

#!/bin/bash
#
#SBATCH -o slurm.%N.%j.out  # STDOUT file with the Node name and the Job ID
#SBATCH -e slurm.%N.%j.err  # STDERR file with the Node name and the Job ID

Parameters to control the job

--partition=<partition_names>, -p

Request a specific partition for the resource allocation. Each partition (queue in SGE) have their own limits: time, memory, nodes ...

--mem=<size[units]>

Specify the real memory required per node. The default units is MB (Default: 2GB)

The job is killed if it exceeds the limit

Note that you can use the variable $SLURM_MEM_PER_NODE in the command line to synchronize the software settings and the resource allocated.

--time=<time>, -t

Set a limit on the total run time of the job allocation.

Acceptable time formats include "minutes", "minutes:seconds", "hours:minutes:seconds", "days-hours", "days-hours:minutes" and "days-hours:minutes:seconds".

Parameters for multithreading

--cpus-per-task=<ncpus>, --cpus, -c

Request a number of CPUs (default 1)

Note that you can use the variable $SLURM_CPUS_PER_TASK in the command line to avoid mistake between the resource allocated and the job.

#!/bin/bash
#
#SBATCH --cpus-per-task=8

srun bowtie2 --threads $SLURM_CPUS_PER_TASK -x hg19 -1 sample_R1.fq.gz -2 sample_R2.fq.gz -S sample_hg19.sam

Job information on running job

List a user's current jobs:

squeue -u <username>

List a user's running jobs:

squeue -u <username> -t RUNNING

List a user's pending jobs:

squeue -u <username> -t PENDING

View accounting information for all user's job for the current day :

sacct --format=JobID,JobName,User,Submit,ReqCPUS,ReqMem,Start,NodeList,State,CPUTime,MaxVMSize%15 -u <username>

View accounting information for all user's job for the 2 last days (it worth an alias) :

sacct -a -S $(date --date='2 days ago' +%Y-%m-%dT%H:%M) --format=JobID,JobName,User%15,Partition,ReqCPUS,ReqMem,State,Start,End,CPUTime,MaxVMSize -u <username>

List detailed job information:

scontrol show -dd jobid=<jobid>

Manage jobs

To cancel/stop a job:

scancel <jobid>

To cancel all jobs for a user:

scancel -u <username>

To cancel all pending jobs for a user:

scancel -t PENDING -u <username>

Job information on ended job

Jobs that do not respect their resource reservation can be killed automatically by the cluster. On the contrary, it is not relevant to reserve too many resources.

You can obtain post-mortem information for your jobs.

`acct`

SLURM incorporates a mechanism to track the resource consumption of each job.

The sacct command is used to query the SLURM database to track resource consumption:

To consult the basic information of a job:

sacct -j $job_id

Display detailed information about a job:

sacct --format=JobID,JobName,User%15,Partition,ReqCPUS,ReqMem,MaxVMSize%15,State,Start,End,CPUTime,NodeList -j $job_id

💡 Advice: you can create an alias in your ~/.bashrc

alias sacctReq='sacct --format=JobID,JobName,User%15,Partition,ReqCPUS,ReqMem,MaxVMSize%15,State,Start,End,CPUTime,NodeList'

`seff`

seff takes a jobid and reports on the efficiency of that job's cpu and memory utilization

seff $job_id