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Running Jobs

Slurm is the utility used for batch processing support, so all jobs must be run through it. This section provides information for getting started with job execution at the cluster.

IMPORTANT

All jobs requesting more cores than what a full node can offer, will automatically use all requested nodes in exclusive mode. For example, if you ask for n+1 cores and nodes have n cores, you will receive two complete nodes (2 x n cores), and the consumed runtime of these 2n cores will be reflected in your budget.

Queues​

Several queues are present in the machines, and users may access different queues. Queues have unlike limits regarding the number of cores and duration for the jobs.

Anytime you can check all queues you have access to and their limits by using:

bsc_queues
info

Besides, special queues are available upon request for longer/bigger executions and will require proof of scalability and application performance. To apply for access to these special queues, please get in touch with us.

Submitting jobs​

A job is the execution unit for Slurm. A job is defined by a text file containing a set of directives describing the job's requirements and the commands to execute.

The method for submitting jobs is to use the Slurm sbatch directives directly.

info

For more information:

man sbatch
man srun
man salloc
IMPORTANT
  • The maximum amount of queued jobs (running or not) is 366.
  • Bear in mind there are execution limitations on the number of nodes and cores that can be used simultaneously by a group to ensure the proper scheduling of jobs.

SBATCH commands​

These are the primary directives to submit jobs with sbatch:

  • Submit a job script to the queue system (see Job directives):

    sbatch <job_script>

  • Show all the submitted jobs:

    squeue

  • Remove a job from the queue system, canceling the execution of the processes (if they were still running):

    scancel <job_id>

  • To set up X11 forwarding on a srun allocation (so that you will be able to execute a graphical command):

    srun --x11
    REMARK

    You will get a graphical window as long as you don't close the current terminal.

  • Also, X11 forwarding can be set through interactive sessions:

    salloc -J interactive --x11

Interactive Sessions​

Allocation of an interactive session has to be done through Slurm:

salloc [ OPTIONS ]
note

Some of the parameters you can use with salloc are the following (see also Job directives):

-p, --partition=<name>
-q, --qos=<name>
-t, --time=<time>
-n, --ntasks=<number>
-c, --cpus-per-task=<number>
-J, --job-name=<name>
--exclusive
Example​

Interactive session for 10 minutes, 1 task, 64 CPUs (cores) per task:

salloc -t 00:10:00 -n 1 -c 64 -J myjob srun --pty /bin/bash

Job directives​

A job must contain a series of directives to inform the batch system about the characteristics of the job. These directives appear as comments in the job script and have to conform to either the sbatch syntaxes.

sbatch syntax is of the form:

#SBATCH --directive=value

Additionally, the job script may contain a set of commands to execute. If not, an external script may be provided with the 'executable' directive.

Here you may find the most common directives:

  • Request the queue for the job:

    #SBATCH --qos=debug
    REMARKS
    • Slurm will use the user's default queue if it is not specified.
    • The queue 'debug' is only intended for small tests.

  • Set the limit of wall clock time:

    #SBATCH --time=HH:MM:SS
    caution

    This is a mandatory field and you must set it to a value greater than real execution time for your application and smaller than the time limits granted to the user. Notice that your job will be killed after the time has passed.

  • Set the working directory of your job (i.e. where the job will run):

    #SBATCH -chdir=pathname

    Or: 

    #SBATCH -D pathname
    caution

    If not specified, it is the current working directory at the time the job was submitted.

  • Set the name of the file to collect the standard output (stdout) of the job:

    #SBATCH --output=file

  • Set the name of the file to collect the standard error output (stderr) of the job:

    #SBATCH --error=file

  • Set the number of processes to start:

    #SBATCH --ntasks=number

  • Optionally, you can specify how many threads each process would open with the directive:

    #SBATCH --cpus-per-task=number
    info

    The number of cpus assigned to the job will be the total_tasks number * cpus_per_task number.

  • Set the number of tasks assigned to a node:

    #SBATCH --ntasks-per-node=number

  • Set the number of GPUs assigned to a node:

    #SBATCH --gres=gpu:number
    info

    The maximum number is "2".

  • Request an exclusive use of a compute node without sharing the resources with other users:

    #SBATCH --exclusive

  • Set the reservation name where you will allocate your jobs (assuming that your account has access to that reservation):

    #SBATCH --reservation=reservation_name
    REMARK

    Sometimes, node reservations can be granted for executions where only a set of accounts can run jobs. Useful for courses.

Some useful Slurm's environment variables​

VariableMeaning
SLURM_JOBIDSpecifies the job ID of the executing job
SLURM_NPROCSSpecifies the total number of processes in the job
SLURM_NNODESIs the actual number of nodes assigned to run your job
SLURM_PROCIDSpecifies the MPI rank (or relative process ID) for the current process. The range is from 0-(SLURM_NPROCS-1)
SLURM_NODEIDSpecifies relative node ID of the current job. The range is from 0-(SLURM_NNODES-1)
SLURM_LOCALIDSpecifies the node-local task ID for the process within a job

Examples​

sbatch examples​

Example for a sequential job:

#!/bin/bash

#SBATCH --job-name="test_serial"
#SBATCH -D .
#SBATCH --output=serial_%j.out
#SBATCH --error=serial_%j.err
#SBATCH --ntasks=1
#SBATCH --time=00:02:00

./serial_binary > serial.out

Example for a parallel job:

#!/bin/bash

#SBATCH --job-name=test_parallel
#SBATCH -D .
#SBATCH --output=mpi_%j.out
#SBATCH --error=mpi_%j.err
#SBATCH --ntasks=16
#SBATCH --cpus-per-task=4
#SBATCH --time=00:02:00
#SBATCH --gres=gpu:2

mpirun ./parallel_binary > parallel.output

Interpreting job status and reason codes​

When using squeue, Slurm will report back the status of your launched jobs. If they are still waiting to enter execution, they will be followed by the reason. Slurm uses codes to display this information, so in this section we will be covering the meaning of the most relevant ones.

Job state codes​

This list contains the usual state codes for jobs that have been submitted:

  • COMPLETED (CD): The job has completed the execution.
  • COMPLETING (CG): The job is finishing, but some processes are still active.
  • FAILED (F): The job terminated with a non-zero exit code.
  • PENDING (PD): The job is waiting for resource allocation. The most common state after running "sbatch", it will run eventually.
  • PREEMPTED (PR): The job was terminated because of preemption by another job.
  • RUNNING (R): The job is allocated and running.
  • SUSPENDED (S): A running job has been stopped with its cores released to other jobs.
  • STOPPED (ST): A running job has been stopped with its cores retained.

Job reason codes​

This list contains the most common reason codes of the jobs that have been submitted and are still not in the running state:

  • Priority: One or more higher priority jobs is in queue for running. Your job will eventually run.
  • Dependency: This job is waiting for a dependent job to complete and will run afterwards.
  • Resources: The job is waiting for resources to become available and will eventually run.
  • InvalidAccount: The job’s account is invalid. Cancel the job and resubmit with correct account.
  • InvaldQoS: The job’s QoS is invalid. Cancel the job and resubmit with correct account.
  • QOSGrpCpuLimit: All CPUs assigned to your job’s specified QoS are in use; job will run eventually.
  • QOSGrpMaxJobsLimit: Maximum number of jobs for your job’s QoS have been met; job will run eventually.
  • QOSGrpNodeLimit: All nodes assigned to your job’s specified QoS are in use; job will run eventually.
  • PartitionCpuLimit: All CPUs assigned to your job’s specified partition are in use; job will run eventually.
  • PartitionMaxJobsLimit: Maximum number of jobs for your job’s partition have been met; job will run eventually.
  • PartitionNodeLimit: All nodes assigned to your job’s specified partition are in use; job will run eventually.
  • AssociationCpuLimit: All CPUs assigned to your job’s specified association are in use; job will run eventually.
  • AssociationMaxJobsLimit: Maximum number of jobs for your job’s association have been met; job will run eventually.
  • AssociationNodeLimit: All nodes assigned to your job’s specified association are in use; job will run eventually.