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CRC Submitting Jobs with SLURM

CRC Submitting Jobs with SLURM

Once you have an executable program and are ready to run it on the compute nodes, you must create a job script that performs the following functions:

  • Use job batch options to request the resources that will be needed (i.e. number of processors, run time, etc.), and
  • Use commands to prepare for execution of the executable (i.e. cd to working directory, source shell environment files, copy input data to a scratch location, copy needed output off of scratch location, clean up scratch files, etc).

After the job script has been constructed you must submit it to the job scheduler for execution. The remainder of this section will describe the anatomy of a job script and how to submit and monitor jobs.

Please note script options are being provided using the long options and not the short options for readability and consistency e.g. --nodes versus -N.

 

 

SLURM Batch Script Options

All jobs must be submitted via a SLURM batch script or invoking sbatch at the command line . See the table below for SLURM submission options.

Option

Description

#SBATCH --job-name=YourJobName

Recommended:  Assigns a job name.  The default is the name of SLURM job script.

#SBATCH --partition=PartitionName

Recommended:  Specify the name of the Partition (queue) to use. Use this to specify the default partition or a special partition i.e. non-condo partiton with which you have access.

#SBATCH --ntasks=2

 Required: The maximum number of tasks per job. Usually used for MPI jobs.

#SBATCH --cpus-per-task=16 Recommended:  The number processes per task. Usually used for OpenMP or multi-threaded jobs.

#SBATCH --time=08:00:00

Required:  The maximum run time needed for this job to run, in days-hh:mm:ss.

#SBATCH --mem-per-cpu=1024M

Recommended: The maximum amount of physical memory used by any single process of the job ([M]ega|[G]iga|[T]era)Bytes.

The value of mem-per-cpu multiplied by cpus on a node (mem-per-cpu X ntasks X cpus-per-task) should not exceed the amount of memory on a node.

 See our FAQ for more details. 

#SBATCH --mail-user=netID@rice.edu Recommended:  Email address for job status messages. Replace netID with your netID as Rice.
#SBATCH --mail-type=ALL Recommended:  SLURM will notify the user via email when the job reaches the following states BEGIN, END, FAIL or REQUEUE.
#SBATCH --nodes=1 --exclusive Optional:  Using both of these options will give your job exclusive access to a node such that no other jobs will use the unallocated resources on the node.
Please see our FAQ for more details on exclusive access.

#SBATCH --output=mypath

Optional:  The full path for the standard output (stdout) and standard error (stderr) "slurm-%j.out" file, where the "%j" is replaced by the job ID.  Current working directory is the default.

#SBATCH --error=mypath

Optional:  The full path for the standard error (stderr) "slurm-%j.out" files. Use this only when you want to separate (stderr) from (stdout). Current working directory is the default.

#SBATCH --export=ALL

Optional:  Exports all environment variables to the job.  See our FAQ for details.

#SBATCH --account=AccountName

#SBATCH --partition=PartitionName

You need to specify the name of the condo account to use a condo on the cluster.

Use the command sacctmgr show assoc user=netID to show which accounts and partitions with which you have access.

#SBATCH --constraint=<feature list> Optional: Constrains job to nodes matching a feature list. Currently available features include processor architectures: ivybridge, broadwell, skylake, cascadelake and fabrics: opath. Features can be combined: --constraint="skylake&opath"
#SBATCH --gres=gpu:1 Optional: Request a number of GPUs per node.

Serial Job Script

A job script may consist of SLURM directives, comments and executable statements. A SLURM directive provides a way of specifying job attributes in addition to the command line options. For example, we could create a myjob.slurm script this way:

myjob.slurm
#!/bin/bash
#SBATCH --job-name=YourJobNameHere
#SBATCH --account=commons
#SBATCH --partition=commons

#SBATCH --ntasks=
1
#SBATCH --mem-per-cpu=1000m
#SBATCH --time=
00:30:00
#SBATCH --mail-user=netID@rice.edu
#SBATCH --mail-type=ALL
echo "My job ran on:" echo $SLURM_NODELIST
if [[ -d $SHARED_SCRATCH/$USER && -w $SHARED_SCRATCH/$USER ]]; then
cd $SHARED_SCRATCH/$USER
srun /path/to/myprogram
fi

This example script will submit a job to the default partition using 1 processor and 1GB of memory per processor, with a maximum run time of 30 minutes.

Definition of --ntasks-per-node

For the clusters the  --ntasks-per-node  option means  tasks per node.

Accurate run time value is strongly recommended

It is important to specify an accurate run time for your job in your SLURM submission script.  Selecting eight hours for jobs that are known to run for much less time may result in the job being delayed by the scheduler due to an overestimation of the time the job needs to run.

How to specify mem

The --mem value represents memory per processor core.  If your --mem value multiplied by the number of tasks (--ntasks-per-node) exceeds the amount of memory per node, your job will not run.  If your job is going to use the entire node, then you should use the --exclusive option instead of the --mem or --ntasks-per-node options (See Here).  It is good practice to specify the --mem option if you are going to be using less than an entire node and thus sharing the node with other jobs.

If you need to debug your program and want to run in interactive mode, the same request above could be constructed like this (via the srun command):

srun --pty --partition=interactive --ntasks=1 --mem=1G --time=00:30:00 $SHELL

For more details on interactive jobs, please see our FAQ on this topic.

SLURM Environment Variables in Job Scripts

When you submit a job, it will inherit several environment variables that are automatically set by SLURM. These environment variables can be useful in your job submission scripts as seen in the examples above. A summary of the most important variables are presented in the table below.

Variable Name

Description

$SHARED_SCRATCH

Location of shared scratch space.  See our FAQ for more details.

$LOCAL_SCRATCH Location of local scratch space on each node.

$SLURM_JOB_NODELIST

Environment variable containing a list of all nodes assigned to the job.

$SLURM_SUBMIT_DIR

Path from where the job was submitted.

Job Launcher (srun)

For jobs that need two or more processors and are compiled with MPI libraries, you must use srun to launch your job.  The job launcher's purpose is to spawn copies of your executable across the resources allocated to your job. We currently support srun for this task and do not support the mpirun or mpiexec launchers. By default srun only needs your executable, the rest of the information will be extracted from SLURM.

The following is an example of how to use srun inside your SLURM batch script. This example will run myMPIprogram as a parallel MPI code on all of the processors allocated to your job by SLURM:

myMPIjob.slurm
#!/bin/bash
#SBATCH --job-name=YourJobNameHere
#SBATCH --account=commons

#SBATCH --partition=commons

#SBATCH --ntasks=
24
#SBATCH --mem-per-cpu=1G

#SBATCH --time=
00:30:00
#SBATCH --mail-user=netID
@rice.edu
#SBATCH --mail-type=ALL
 
echo "My job ran on:" echo $SLURM_NODELIST
if [[ -d $SHARED_SCRATCH/$USER && -w $SHARED_SCRATCH/$USER ]]; then
cd $SHARED_SCRATCH/$USER
srun /path/to/myMPIprogram
fi

This example script will submit a job to the default partition using 24 processor cores and 1GB of memory per processor core, with a maximum run time of 30 minutes.

Your Program must use MPI

The above example assumes that myMPIprogram is a program designed to be parallel (using MPI). If your program has not been parallelized then running on more than one processor will not improve performance and will result in wasted processor time and could result in multiple copies of your program being executed.

The following example will run myMPIprogram on only four processors even if your batch script requested more than four.

srun -n 4 /path/to/myMPIprogram

To ensure that your job will be able to access an mpi runtime, you must load an mpi module before submitting your job as follows:

module load GCC OpenMPI

Submitting and Monitoring Jobs

Once your job script is ready, use sbatch to submit it as follows:

sbatch /path/to/myjob.slurm

This will return a jobID number while the output and error stream of the job will be saved to one file inside the directory where the job was submitted, unless you specified otherwise.

The status of the job can be obtained using SLURM commands.  See the table below for a list of commands:

Command

Description

squeue

Show a detailed list of all submitted jobs.

squeue -j jobID

Show a detailed description of the job given by jobID.

squeue -- start -j jobID

Gives an estimate of the expected start time of the job given by jobID.

There are variations to these commands that can also be useful.  They are described below:

Command

Description

squeue -l

Show a list of all running jobs.

squeue -u username

Show a list of all jobs in queue owned by the user specified by username.

scontrol show job jobID

To get a verbose description of the job given by jobID. The output can be used as a template when you are attempting to modify a job.

There are many different states that a job can be after submission: BOOT_FAIL (BF), CANCELLED (CA), COMPLETED (CD), CONFIGURING (CF), COMPLETING (CG), FAILED (F), NODE_FAIL (NF), PENDING (PD), PREEMPTED (PR), RUNNING (R), SUSPENDED (S), TIMEOUT (TO), or SPECIAL_EXIT (SE). The squeue command with no arguments will list all jobs in their current state.  The most common states are described below.

Running (R): These are jobs that are running.

Pending (PD): These jobs are eligible to run but there is simply not enough resources to allocate to them at this time.

Deleting Jobs

A job can be deleted by using the scancel command as follows:

scancel jobID



Keywords:
CRC Submitting Jobs with SLURM 
Doc ID:
108436
Owned by:
Bryan R. in Rice U
Created:
2021-01-19
Updated:
2024-08-22
Sites:
Rice University