Using SLURM scheduler

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Usage of the SLURM scheduler


The schedule of the HPCs are CPU hour based. This means that the available core hours are divided between users on a monthly basis. All UNIX users are connected to one or more account. This scheduler account is connected to an HPC project and a UNIX group. HPC jobs can only be sent by using one of the accounts. The core hours are calculated by the multiplication of wall time (time spent running the job) and the CPU cores requested. For example reserving 2 nodes (48 cpu cores) at the NIIFI SC for 30 minutes gives 48 * 30 = 1440 core minutes = 24 core hours. Core hours are measured between the start and and the end of the jobs.

It is very important to be sure the application maximally uses the allocated resources. An empty or non-optimal job will consume allocated core time very fast. If the account run out of the allocated time, no new jobs can be submitted until the beginning of the next accounting period. Account limits are regenerated the beginning of each month.

Information about an account can be listed with the following command:



After executing the command, the following table shows up for Bob. The user can access, and run jobs by using two different accounts (foobar, barfoo). He can see his name marked with * in the table. He shares both accounts with alice (Account column). The consumed core hours for the users are displayed in the second row (Usage), and the consumption for the jobs ran as the account is displayed in the 4th row. The last two row defines the allocated maximum time (Account limit), and the time available for the machine (Available).

Scheduler Account Balance
---------- ----------- + ---------------- ----------- + ------------- -----------
User             Usage |          Account       Usage | Account Limit   Available (CPU hrs)
---------- ----------- + ---------------- ----------- + ------------- -----------
alice                0 |           foobar           0 |             0           0
bob *                0 |           foobar           0 |             0           0

bob *                7 |           barfoo           7 |         1,000         993
alice                0 |           barfoo           7 |         1,000         993

Estimating core time

Before production runs, it is advised to have a core time estimate. The following command can be used for getting estimate:

   sestimate -N NODES -t WALLTIME

where NODES are the number of nodes to be reserved, WALLTIME is the maximal time spent running the job.

It is important to provide the core time to be reserved most precisely, because the scheduler queue the jobs based on this value. Generally, a job with shorter core time will be run sooner. It is advised to check the time used to run the job after completion with sacct command.


Alice want to reserve 2 days 10 hours and 2 nodes, she checks, if she have enough time on her account.

sestimate -N 2 -t 2-10:00:00

Estimated CPU hours: 2784

Unfortunately, she couldn't afford to run this job.

Status information

Jobs in the queue can be listed with squeue command, the status of the cluster can be retrieved with the sinfo command. All jobs sent will get a JOBID. The properties of a job can be retrieved by using this id. Status of a running or waiting job:

   scontrol show job JOBID

All jobs will be inserted into an accounting database. The properties of the completed jobs can be retrieved from this database. Detailed statistics can be viewed by using this command:

   sacct -l -j JOBID

Memory used can be retrieved by using

   smemory JOBID

Disk usage can be retrieved by this command:

   sdisk JOBID


There are 3 jobs in the queue. The first is an array job which is waiting for resources (PENDING). The second is an MPI job running on 4 nodes for 25 minutes now. The third is an OMP run running on one node, just started. The NAME of the jobs can be freely given, it is advised to use short, informative names.

    squeue -l

Wed Oct 16 08:30:07 2013              
591_[1-96]    normal    array    alice  PENDING       0:00     30:00      1 (None)
       589    normal      mpi      bob  RUNNING      25:55   2:00:00      4 cn[05-08]
       590    normal      omp    alice  RUNNING       0:25   1:00:00      1 cn09

This two-node batch job had a typical load of 10GB virtual, and 6.5GB RSS memory per node.

    smemory 430

 MaxVMSize  MaxVMSizeNode  AveVMSize     MaxRSS MaxRSSNode     AveRSS
---------- -------------- ---------- ---------- ---------- ----------
10271792K           cn06  10271792K   6544524K       cn06   6544524K   
10085152K           cn07  10085152K   6538492K       cn07   6534876K 

Checking jobs

It is important to be sure the application fully uses the core time reserved. A running application can be monitored with the following command:

   sjobcheck JOBID


This job runs on 4 nodes. The LOAD group provides information about the general load of the machine, this is more or less equal to the number of cores. The CPU group gives you information about the exact usage. Ideally, values of the User column are over 90. If the value is below that, there is a problem with the application, or it is not optimal, and the run should be ended. This example job fully using ("maxing out") the available resources.

Hostname                     LOAD                       CPU              Gexec  
 CPUs (Procs/Total) [     1,     5, 15min] [  User,  Nice, System, Idle, Wio]
cn08    24 (   25/  529) [ 24.83, 24.84, 20.98] [  99.8,   0.0,   0.2,   0.0,   0.0] OFF
cn07    24 (   25/  529) [ 24.93, 24.88, 20.98] [  99.8,   0.0,   0.2,   0.0,   0.0] OFF
cn06    24 (   25/  529) [ 25.00, 24.90, 20.97] [  99.9,   0.0,   0.1,   0.0,   0.0] OFF
cn05    24 (   25/  544) [ 25.11, 24.96, 20.97] [  99.8,   0.0,   0.2,   0.0,   0.0] OFF

Checking licenses

The used and available licenses can be retrieved with this command:


Checking downtime

In downtime periods, the scheduler doesn't start new jobs, but jobs can be sent. The periods can be retrieved by using the following command:


Running jobs

Running applications in the HPC can be done in batch mode. This means all runs must have a job script containing the resources and commands needed. The parameters of the scheduler (resource definitions) can be given with the #SBATCH directive. Comparison of the schedulers, and the directives available at slurm are available at this table.

Obligatory parameters

The following parameters are obligatory to provide:

#SBATCH --job-name=NAME

where ACCOUNT is the name of the account to use (available accounts can be retrieved with the sbalance command), NAME is the short name of the job, TIME is the maximum walltime using DD-HH:MM:SS syntax. Acceptable time formats include "minutes", "minutes:seconds", "hours:minutes:seconds", "days-hours", "days-hours:minutes" and "days-hours:minutes:seconds".

The following command submit jobs:


If the submission was successful, the following is outputted:

Submitted batch job JOBID

where JOBID is the unique id of the job

The following commmand cancels the job:

   scancel JOBID

Job queues

There are two separate queue (partition) available in the HPC, the test queue and the prod queue. Tha latter is for the production runs, the former is for testing purposes. In the test queue, 1 node can be allocated for the maximum of half hours, The default queue is prod. Test partition can be chosen with the following directive:

#SBATCH --partition=test

Quality of Service (QoS)

There is an option for submitting low priority jobs. These jobs can be interrupted by any normal priority job at any time, but only the half of the time is billed to the account. Interrupted jobs will be automatically queued again. Therefore it is important to only run jobs that can be interrupted at any time, periodically saves their states (checkpoint) and can restart quickly. The default QoS is normal, non-interruptable.

The following directive choses low priority:

#SBATCH --qos=lowpri

Memory settings

1000 MB memory is allocated for 1 CPU core by default, more can be allocated with the following directive:

#SBATCH --mem-per-cpu=MEMORY

where MEMORY is given in MB. The maximum memory/core at NIIFI SC is 2600 MB.

Email notification

Sending mail when the status of the job change (start, stop, error):

#SBATCH --mail-type=ALL
#SBATCH --mail-user=EMAIL

where EMAIL is the e-mail to notify.

Array jobs

Array jobs are needed, when multiple one threaded (serial) jobs are to be sent (with different data). Slurm stores unique id of the instances in the SLURM_ARRAY_TASK_ID enviromnemt variable. It is possible to seperate threads of the array job by retrieving these ids. Output of the threads are written into slurm-SLURM_ARRAY_JOB_ID-SLURM_ARRAY_TASK_ID.out files. The scheduler uploads outputs tightly. It is useful to use multiply threads for a CPU core. More on this topic


Alice user submits 96 serial job for a maximum of 24 hour run. on the expenses of 'foobar' account. The #SBATCH --array=1-96 directive indicates, that it is an array job. The application can be run with the srun command. This is a shell script in this example.

#SBATCH -A foobar
#SBATCH --time=24:00:00
#SBATCH --job-name=array
#SBATCH --array=1-96

MPI jobs

Using MPI jobs, the number of MPI processes running on a node is to be given (#SBATCH --ntasks-per-node=). The most frequent case is to provide the number of CPU cores. Parallel programs should be started by using mpirun command.


Bob user allocates 2 nodes, 12 hour for an MPI job, billing 'barfoo' account. 24 MPI thread will be started on each node. The stdout output is piped to slurm.out file (#SBATCH -o).

#SBATCH -A barfoo
#SBATCH --job-name=mpi
#SBATCH --ntasks-per-node=24
#SBATCH --time=12:00:00
#SBATCH -o slurm.out
mpirun ./a.out

CPU binding

Generally, the performance of MPI application can be optimized with CPU core binding. In this case, the threads of the paralel program won't be scheduled by the OS between the CPU cores, and the memory localization can be made better (less cache miss). It is advised to use memory binding. Tests can be run to define, what binding strategy gives the best performance for our application. The following settings are valid for OpenMPI environment. Further information on binding can be retrieved with --report-bindings MPI option. Along with the running commands, few lines of the detailed binding information are shown. It is important, that one should not use task_binding of the scheduler!

Binding per CPU core

In this case, MPI fills CPU cores by the order of threads (rank).

Command to run: mpirun --bind-to-core --bycore

[cn05:05493] MCW rank 0 bound to socket 0[core 0]: [B . . . . . . . . . . .][. . . . . . . . . . . .]
[cn05:05493] MCW rank 1 bound to socket 0[core 1]: [. B . . . . . . . . . .][. . . . . . . . . . . .]
[cn05:05493] MCW rank 2 bound to socket 0[core 2]: [. . B . . . . . . . . .][. . . . . . . . . . . .]
[cn05:05493] MCW rank 3 bound to socket 0[core 3]: [. . . B . . . . . . . .][. . . . . . . . . . . .]
Binding based on CPU socket

In this case, MPI threads are filling CPUs alternately.

Command to run: mpirun --bind-to-core --bysocket

[cn05:05659] MCW rank 0 bound to socket 0[core 0]: [B . . . . . . . . . . .][. . . . . . . . . . . .]
[cn05:05659] MCW rank 1 bound to socket 1[core 0]: [. . . . . . . . . . . .][B . . . . . . . . . . .]
[cn05:05659] MCW rank 2 bound to socket 0[core 1]: [. B . . . . . . . . . .][. . . . . . . . . . . .]
[cn05:05659] MCW rank 3 bound to socket 1[core 1]: [. . . . . . . . . . . .][. B . . . . . . . . . .]
Binding by nodes

In this case, MPI threads are filling nodes alternately. At least 2 nodes needs to be allocated.

Command to run: mpirun --bind-to-core --bynode

[cn05:05904] MCW rank 0 bound to socket 0[core 0]: [B . . . . . . . . . . .][. . . . . . . . . . . .]
[cn05:05904] MCW rank 2 bound to socket 0[core 1]: [. B . . . . . . . . . .][. . . . . . . . . . . .]
[cn06:05969] MCW rank 1 bound to socket 0[core 0]: [B . . . . . . . . . . .][. . . . . . . . . . . .]
[cn06:05969] MCW rank 3 bound to socket 0[core 1]: [. B . . . . . . . . . .][. . . . . . . . . . . .]

OpenMP (OMP) jobs

For OpenMP paralell applications, 1 node needs to be allocated, and the number of OMP threads needs to be provided with the OMP_NUM_THREADS environment variable. The variable needs to be written before the application (see example), or needs to be exported before executing the command:

 export OMP_NUM_THREADS=24


Alice user starts a 24 threaded OMP application for maximum 6 hours on the expenses of foobar account.

#SBATCH -A foobar
#SBATCH --job-name=omp
#SBATCH --time=06:00:00
OMP_NUM_THREADS=24 ./a.out

Hybrid MPI-OMP jobs

When an application uses MPI and OMP it is running in hybrid MPI-OMP mode. Good to know that Intel MKL linked applications MKL calls are OpenMP capable. Generally, the following distribution suggested: MPI process number is from 1 to the CPU socket number, OMP thread number is the number of CPU cores in a node, or the half or quarter of that (it depends on code). For the job script, the parameters of these two needs to be combined.


Alice user sent a hybrid job on the expenses of the 'foobar' account for 8 hours, and 2 nodes. 1 MPI process is running on one node using 24 OMP thread per node. For the 2 nodes, 2 MPI process is running, with 2x24 OMP threads

#SBATCH -A foobar
#SBATCH --job-name=mpiomp
#SBATCH --time=08:00:00
#SBATCH --ntasks-per-node=1
#SBATCH -o slurm.out
mpirun ./a.out

Maple Grid jobs

Maple can be run - similarly to OMP jobs - on one node. Maple module need to be loaded for using it. A grid server needs to be started, because Maple is working in client-server mode (${MAPLE}/toolbox/Grid/bin/startserver). This application needs to use license, which have to be given in the jobscript (#SBATCH --licenses=maplegrid:1). Starting of a Maple job is done by using ${MAPLE}/toolbox/Grid/bin/joblauncher code.


Alice user is running a Maple Grid application for 6 hours on the expenses of 'foobar' account:

#SBATCH -A foobar
#SBATCH --job-name=maple
#SBATCH --ntasks-per-node=24
#SBATCH --time=06:00:00
#SBATCH -o slurm.out
#SBATCH --licenses=maplegrid:1

module load maple

${MAPLE}/toolbox/Grid/bin/joblauncher ${MAPLE}/toolbox/Grid/samples/Simple.mpl

GPU compute nodes

The Szeged site accomodates 2 GPU enabled compute nodes. Each GPU node has 6 Nvidia Tesla M2070 cards. The GPU nodes reside in a separate job queue (--partition gpu). To specify the number of GPUs set --gres gpu:# directive.


Alice user submits to the foobar account a 4 GPU, 6 hour job.

#SBATCH -A foobar
#SBATCH --job-name=GPU
#SBATCH --partition gpu
#SBATCH --gres gpu:4
#SBATCH --time=06:00:00

$PWD/gpu_burnout 3600


Extensions should be asked for at the Execution site (NIIF) at All requests will be carefully reviewed and decided if eligable.

Reporting after finishing project

A report must be created after using PRACE resources. Please contact for further details.

Acknowledgement in publications

We acknowledge [NIIF] for awarding us access to resource based in Hungary at [Budapest/Debrecen/Pécs/Szeged]. Where technical support has been received the following additional text should also be used: The support of [name of person/people] from NIIF Institute, Hungary to the technical work is gratefully acknowledged.