Basics of SLURM Jobs
The Simple Linux Utility for Resource Management (SLURM) is a system providing job scheduling and job management on compute clusters. With SLURM, a user requests resources and submits a job to a queue. The system will then take jobs from queues, allocate the necessary nodes, and execute them.
Do NOT run large, long, multi-threaded, parallel, or CPU-intensive jobs on a front-end login host. All users share the front-end hosts, and running anything but the smallest test job will negatively impact everyone's ability to use Scholar. Always use SLURM to submit your work as a job.
Link to section 'Submitting a Job' of 'Basics of SLURM Jobs' Submitting a Job
The main steps to submitting a job are:
Follow the links below for information on these steps, and other basic information about jobs. A number of example SLURM jobs are also available.
Queues
Link to section 'Scholar Queue' of 'Queues' Scholar Queue
This is the default queue for submitting jobs on Scholar. The maximum walltime on scholar queue is 4 hours.
Link to section 'Long Queue' of 'Queues' Long Queue
If your job requires more than 4 hours to complete, you can submit it to the long queue. The maximum walltime is 3 days. There are only 5 nodes in this queue, so you may have to wait for some time to get access to a node.
Link to section 'GPU Queue' of 'Queues' GPU Queue
If your job needs access to an Nvidia GPU accelerator, then use the gpu queue. The maximum walltime is 4 hours.
Link to section 'Debug Queue' of 'Queues' Debug Queue
The debug queue allows you to quickly start small, short, interactive jobs in order to debug code, test programs, or test configurations. You are limited to one running job at a time in the queue, and you may run up to two compute nodes for 30 minutes. The expectation is that debug jobs should start within a couple of minutes, assuming all of its dedicated nodes are not taken by others.
Link to section 'List of Queues' of 'Queues' List of Queues
To see a list of all queues on Scholar that you may submit to, use the slist command
This lists each queue you can submit to, the number of nodes allocated to the queue, how many are available to run jobs, and the maximum walltime you may request. Options to the command will give more detailed information. This command can be used to get a general idea of how busy an individual queue is and how long you may have to wait for your job to start.
Job Submission Script
To submit work to a SLURM queue, you must first create a job submission file. This job submission file is essentially a simple shell script. It will set any required environment variables, load any necessary modules, create or modify files and directories, and run any applications that you need:
#!/bin/bash
# FILENAME: myjobsubmissionfile
# Loads Matlab and sets the application up
module load matlab
# Change to the directory from which you originally submitted this job.
cd $SLURM_SUBMIT_DIR
# Runs a Matlab script named 'myscript'
matlab -nodisplay -singleCompThread -r myscript
Once your script is prepared, you are ready to submit your job.
Link to section 'Job Script Environment Variables' of 'Job Submission Script' Job Script Environment Variables
Name | Description |
---|---|
SLURM_SUBMIT_DIR | Absolute path of the current working directory when you submitted this job |
SLURM_JOBID | Job ID number assigned to this job by the batch system |
SLURM_JOB_NAME | Job name supplied by the user |
SLURM_JOB_NODELIST | Names of nodes assigned to this job |
SLURM_CLUSTER_NAME | Name of the cluster executing the job |
SLURM_SUBMIT_HOST | Hostname of the system where you submitted this job |
SLURM_JOB_PARTITION | Name of the original queue to which you submitted this job |
Submitting a Job
Once you have a job submission file, you may submit this script to SLURM using the sbatch
command. SLURM will find, or wait for, available resources matching your request and run your job there.
To submit your job to one compute node:
$ sbatch --nodes=1 myjobsubmissionfile
Slurm uses the word 'Account' and the option '-A' to specify different batch queues. To submit your job to a specific queue:
$ sbatch --nodes=1 -A scholar myjobsubmissionfile
By default, each job receives 30 minutes of wall time, or clock time. If you know that your job will not need more than a certain amount of time to run, request less than the maximum wall time, as this may allow your job to run sooner. To request the 1 hour and 30 minutes of wall time:
$ sbatch -t 1:30:00 --nodes=1 -A scholar myjobsubmissionfile
The --nodes
value indicates how many compute nodes you would like for your job.
Each compute node in Scholar has 20 processor cores.
In some cases, you may want to request multiple nodes. To utilize multiple nodes, you will need to have a program or code that is specifically programmed to use multiple nodes such as with MPI. Simply requesting more nodes will not make your work go faster. Your code must support this ability.
To request 2 compute nodes:
$ sbatch --nodes=2 myjobsubmissionfile
By default, jobs on Scholar will share nodes with other jobs.
To submit a job using 1 compute node with 4 tasks, each using the default 1 core and 1 GPU per node:
$ sbatch --nodes=1 --ntasks=4 --gpus-per-node=1 myjobsubmissionfile
If more convenient, you may also specify any command line options to sbatch
from within your job submission file, using a special form of comment:
#!/bin/sh -l
# FILENAME: myjobsubmissionfile
#SBATCH -A myqueuename
#SBATCH --nodes=1
#SBATCH --time=1:30:00
#SBATCH --job-name myjobname
# Print the hostname of the compute node on which this job is running.
/bin/hostname
If an option is present in both your job submission file and on the command line, the option on the command line will take precedence.
After you submit your job with SBATCH
, it may wait in queue for minutes, hours, or even weeks. How long it takes for a job to start depends on the specific queue, the resources and time requested, and other jobs already waiting in that queue requested as well. It is impossible to say for sure when any given job will start. For best results, request no more resources than your job requires.
Once your job is submitted, you can monitor the job status, wait for the job to complete, and check the job output.
Job Dependencies
Dependencies are an automated way of holding and releasing jobs. Jobs with a dependency are held until the condition is satisfied. Once the condition is satisfied jobs only then become eligible to run and must still queue as normal.
Job dependencies may be configured to ensure jobs start in a specified order. Jobs can be configured to run after other job state changes, such as when the job starts or the job ends.
These examples illustrate setting dependencies in several ways. Typically dependencies are set by capturing and using the job ID from the last job submitted.
To run a job after job myjobid has started:
sbatch --dependency=after:myjobid myjobsubmissionfile
To run a job after job myjobid ends without error:
sbatch --dependency=afterok:myjobid myjobsubmissionfile
To run a job after job myjobid ends with errors:
sbatch --dependency=afternotok:myjobid myjobsubmissionfile
To run a job after job myjobid ends with or without errors:
sbatch --dependency=afterany:myjobid myjobsubmissionfile
To set more complex dependencies on multiple jobs and conditions:
sbatch --dependency=after:myjobid1:myjobid2:myjobid3,afterok:myjobid4 myjobsubmissionfile
Holding a Job
Sometimes you may want to submit a job but not have it run just yet. You may be wanting to allow lab mates to cut in front of you in the queue - so hold the job until their jobs have started, and then release yours.
To place a hold on a job before it starts running, use the scontrol hold job command:
$ scontrol hold job myjobid
Once a job has started running it can not be placed on hold.
To release a hold on a job, use the scontrol release job command:
$ scontrol release job myjobid
You find the job ID using the squeue command as explained in the SLURM Job Status section.
Checking Job Status
Once a job is submitted there are several commands you can use to monitor the progress of the job.
To see your jobs, use the squeue -u command and specify your username:
(Remember, in our SLURM environment a queue is referred to as an 'Account')
squeue -u myusername
JOBID ACCOUNT NAME USER ST TIME NODES NODELIST(REASON)
182792 scholar job1 myusername R 20:19 1 scholar-a000
185841 scholar job2 myusername R 20:19 1 scholar-a001
185844 scholar job3 myusername R 20:18 1 scholar-a002
185847 scholar job4 myusername R 20:18 1 scholar-a003
To retrieve useful information about your queued or running job, use the scontrol show job command with your job's ID number. The output should look similar to the following:
scontrol show job 3519
JobId=3519 JobName=t.sub
UserId=myusername GroupId=mygroup MCS_label=N/A
Priority=3 Nice=0 Account=(null) QOS=(null)
JobState=PENDING Reason=BeginTime Dependency=(null)
Requeue=1 Restarts=0 BatchFlag=1 Reboot=0 ExitCode=0:0
RunTime=00:00:00 TimeLimit=7-00:00:00 TimeMin=N/A
SubmitTime=2019-08-29T16:56:52 EligibleTime=2019-08-29T23:30:00
AccrueTime=Unknown
StartTime=2019-08-29T23:30:00 EndTime=2019-09-05T23:30:00 Deadline=N/A
PreemptTime=None SuspendTime=None SecsPreSuspend=0
LastSchedEval=2019-08-29T16:56:52
Partition=workq AllocNode:Sid=mack-fe00:54476
ReqNodeList=(null) ExcNodeList=(null)
NodeList=(null)
NumNodes=1 NumCPUs=2 NumTasks=2 CPUs/Task=1 ReqB:S:C:T=0:0:*:*
TRES=cpu=2,node=1,billing=2
Socks/Node=* NtasksPerN:B:S:C=0:0:*:* CoreSpec=*
MinCPUsNode=1 MinMemoryNode=0 MinTmpDiskNode=0
Features=(null) DelayBoot=00:00:00
OverSubscribe=OK Contiguous=0 Licenses=(null) Network=(null)
Command=/home/myusername/jobdir/myjobfile.sub
WorkDir=/home/myusername/jobdir
StdErr=/home/myusername/jobdir/slurm-3519.out
StdIn=/dev/null
StdOut=/home/myusername/jobdir/slurm-3519.out
Power=
There are several useful bits of information in this output.
JobState
lets you know if the job is Pending, Running, Completed, or Held.RunTime and TimeLimit
will show how long the job has run and its maximum time.SubmitTime
is when the job was submitted to the cluster.- The job's number of Nodes, Tasks, Cores (CPUs) and CPUs per Task are shown.
WorkDir
is the job's working directory.StdOut
andStderr
are the locations of stdout and stderr of the job, respectively.Reason
will show why aPENDING
job isn't running. The above error says that it has been requested to start at a specific, later time.
Checking Job Output
Once a job is submitted, and has started, it will write its standard output and standard error to files that you can read.
SLURM catches output written to standard output and standard error - what would be printed to your screen if you ran your program interactively. Unless you specfied otherwise, SLURM will put the output in the directory where you submitted the job in a file named slurm-
followed by the job id
, with the extension out
. For example slurm-3509.out
. Note that both stdout and stderr will be written into the same file, unless you specify otherwise.
If your program writes its own output files, those files will be created as defined by the program. This may be in the directory where the program was run, or may be defined in a configuration or input file. You will need to check the documentation for your program for more details.
Link to section 'Redirecting Job Output' of 'Checking Job Output' Redirecting Job Output
It is possible to redirect job output to somewhere other than the default location with the --error
and --output
directives:
#!/bin/bash
#SBATCH --output=/home/myusername/joboutput/myjob.out
#SBATCH --error=/home/myusername/joboutput/myjob.out
# This job prints "Hello World" to output and exits
echo "Hello World"
Canceling a Job
To stop a job before it finishes or remove it from a queue, use the scancel command:
scancel myjobid
You find the job ID using the squeue command as explained in the SLURM Job Status section.