SLURM Job Arrays

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To submit a number of identical jobs without having drive the submission with an external script use the SLURM's feature of array jobs.

Note: There is a maximum limit of 3000 jobs per user on HiPerGator.

Submitting array jobs

A job array can be submitted simply by adding

#SBATCH --array=x-y

to the job script where x and y are the array bounds. A job array can also be specified at the command line with

sbatch --array=x-y job_script.sbatch

A job array will then be created with a number of independent jobs a.k.a. array tasks that correspond to the defined array.

SLURM's job array handling is very versatile. Instead of providing a task range a comma-separated list of task numbers can be provided, for example, to rerun a few failed jobs from a previously completed job array as in

sbatch --array=4,8,15,16,23,42  job_script.sbatch

which can be used to quickly rerun the lost tasks from a previous job array for example. Command line options override options in the script, so those can be left unchanged.

Limiting the number of tasks that run at once

To throttle a job array by keeping only a certain number of tasks active at a time use the %N suffix where N is the number of active tasks. For example

#SBATCH -a 1-200%5

will produce a 200 task job array with only 5 tasks active at any given time.

Note that while the symbol used is the % sign, this is the actual number of tasks to be submitted at once.

Using scontrol to modify throttling of running array jobs

Reducing the "ArrayTaskThrottle" count on a running job array will not affect the tasks that have already entered the "RUNNING" state. It will only prevent new tasks from starting until the number or running tasks drops below the new lower threshold.

If you want to change the number of simultaneous tasks of an active job, you can use scontrol:

scontrol update ArrayTaskThrottle=<count> JobId=<jobID>


scontrol update ArrayTaskThrottle=50 JobId=12345

Set ArrayTaskThrottle=0 to eliminate any limit.

Naming output and error files

SLURM uses the %A and %a replacement strings for the master job ID and task ID, respectively.

For example:

#SBATCH --output=Array_test.%A_%a.out
#SBATCH --error=Array_test.%A_%a.error

The error log is optional as both types of logs can be written to the 'output' log.

#SBATCH --output=Array_test.%A_%a.log
if you only use '%A' in the log all array tasks will try to write to a single file. The performance of the run will approach zero asymptotically. Make sure to use both %A and %a in the log file name specification.

Using the array ID Index

SLURM will provide a $SLURM_ARRAY_TASK_ID variable to each task. It can be used inside the job script to handle input and output files for that task.

For instance, for a 100-task job array the input files can be named seq_1.fa, seq_2.fa and so on through seq_100.fa. In a job script for a blastn job they can be referenced as blastn -query seq_${SLURM_ARRAY_TASK_ID}.fa. The output files can be handled in the same way.

One common application of array jobs is to run many input files. While it is easy if the files are numbered as in the example above, this is not needed. If for example you have a folder of 100 files that end in .txt, you can use the following approach to get the name of the file for each task automatically:

file=$(ls *.txt | sed -n ${SLURM_ARRAY_TASK_ID}p)
myscript -in $file

If, alternatively, you use an input file (e.g. 'input.list') with a list of samples/datasets (one per line) to process you can pick an item from the list as follows:


Array ID use in Scripts

When running custom code written in Python or R use the respective module that allows you to read environment variables to read the SLURM array task id of the current job and use it to perform analysis on the correct input file or data column/row. For example:

import sys
jobid = sys.getenv('SLURM_ARRAY_TASK_ID')
task_id <- Sys.getenv("SLURM_ARRAY_TASK_ID")

Extended Example

This shell portion of a SLURM job script sets input and output directories as variables. Then, it sets a RUN variable to the SLURM task id in a job or to a value of '1' if you are running a quick test before submitting a job. The RUN value is used as an index value to pick a full path to a dataset from the input directory, determine the file name, and remove the specified extension to create a value that may represent a sample name to be used in forming an output path. Finally, the automated command is printed to stdout to be recorded in the job log and executed as a command.

Expand to see an explicit example of using SLURM Arrays and automating handling of input and output datasets.



echo "Run: ${RUN}"

module load plink/1.90b3.39

INPUT_PATH=$(ls ${INPUT_DIR}/*.vcf.gz | sed -n ${RUN}p)
INPUT_FILE=$(basename ${INPUT_PATH})
SAMPLE=$(basename ${INPUT_FILE} .vcf.gz)

read -d '' cmd << EOF
plink \
--vcf ${INPUT_PATH} \
--out ${OUTPUT_DIR}/${SAMPLE} \
--allow-no-sex \
echo ${cmd}

eval ${cmd}

Running many short tasks

While SLURM array jobs make it easy to run many similar tasks, if each task is short (seconds or even a few minutes), array jobs quickly bog down the scheduler and more time is spent managing jobs than actually doing any work for you. This also negatively impacts other users.

If you have hundreds or thousands of tasks, it is unlikely that a simple array job is the best solution. That does not mean that array jobs are not helpful in these cases, but that a little more thought needs to go into them for efficient use of the resources.

Play icon.png [10 min, 16sec] Watch the video discussing some of the issues and walking through the details of the example script below.

As an example let's imagine I have 5,000 runs of a program to do, with each run taking about 30 seconds to complete. Rather than running an array job with 5,000 tasks, it would be much more efficient to run 5 tasks where each completes 1,000 runs.

Expand to view a sample script to accomplish this by combining array jobs with bash loops.

#SBATCH --job-name=mega_array   # Job name
#SBATCH --mail-type=ALL         # Mail events (NONE, BEGIN, END, FAIL, ALL)
#SBATCH # Where to send mail	
#SBATCH --nodes=1                   # Use one node
#SBATCH --ntasks=1                  # Run a single task
#SBATCH --mem-per-cpu=1gb           # Memory per processor
#SBATCH --time=00:10:00             # Time limit hrs:min:sec
#SBATCH --output=array_%A-%a.out    # Standard output and error log
#SBATCH --array=1-5                 # Array range
# This is an example script that combines array tasks with
# bash loops to process many short runs. Array jobs are convenient
# for running lots of tasks, but if each task is short, they
# quickly become inefficient, taking more time to schedule than
# they spend doing any work and bogging down the scheduler for
# all users. 
pwd; hostname; date

#Set the number of runs that each SLURM task should do

# Calculate the starting and ending values for this task based
# on the SLURM task and the number of runs per task.

# Print the task and run range
echo This is task $SLURM_ARRAY_TASK_ID, which will do runs $START_NUM to $END_NUM

# Run the loop of runs for this task.
for (( run=$START_NUM; run<=END_NUM; run++ )); do
  echo This is SLURM task $SLURM_ARRAY_TASK_ID, run number $run
  #Do your stuff here


Deleting job arrays and tasks

To delete all of the tasks of an array job, use scancel with the job ID:

scancel 292441

To delete a single task, add the task ID:

scancel 292441_5

Controlling Job emails

By default in SLURM, the emails for events BEGIN, END and FAIL apply to the job array as a whole rather than individual tasks. So:


would result in one email per job, not per task. If you want per task emails, specify:


which will send emails for each task in the array.