Difference between revisions of "Slurm"
(→Optional Arguments: Finished table)
m (→Running Jobs)
|Line 13:||Line 13:|
== Running Jobs ==
== Running Jobs ==
Many of the following commands have
Many of the following commands have options. For full details, see the [https://slurm.schedmd.com/ Slurm Docs].
=== Display Info ===
=== Display Info ===
Revision as of 17:45, 3 June 2019
Some of the CAC's Private Clusters are managed with OpenHPC, which includes the Slurm Workload Manager (Slurm for short). Slurm (Simple Linux Utility for Resource Management) is a group of utilities used for managing workloads on compute clusters.
This page is intended to give users an overview of Slurm. Some of the information on this page has been adapted from the Cornell Virtual Workshop topics on the Stampede2 Environment and Advanced Slurm. For a more in-depth tutorial, please review these topics directly.
Some clusters use Slurm as the batch queuing system and the scheduling mechanism. This means that jobs are submitted to Slurm from a login node and Slurm handles scheduling these jobs on nodes as resources becomes available. Users submit jobs to the batch component which is responsible for maintaining one or more queues (also known as "partitions"). These jobs include information about themselves as well as a set of resource requests. Resource requests include anything from the number of CPUs or nodes to specific node requirements (e.g. only use nodes with > 2GB RAM). A separate component, called the scheduler, is responsible for figuring out when and where these jobs can be run on the cluster. The scheduler needs to take into account the priority of the job, any reservations that may exist, when currently running jobs are likely to end, etc. Once informed of scheduling information, the batch system will handle starting your job at the appropriate time and place. Slurm handles both of these components, so you don't have to think of them as separate processes, you just need to know how to submit jobs to the batch queue(s).
Note: Refer to the documentation for your cluster to determine what queues/partitions are available.
Many of the following commands have several options. For full details, see the man page for the command, or the Slurm Docs.
Common commands used to display information:
sinfodisplays information about nodes and partitions/queues. Use
-lfor more detailed information.
scontrol show nodesviews the state of the nodes.
scontrol show partitionviews the state of the partition/queue.
Here are some common Job Control commands:
sbatch testjob.shsubmits a job where testjob.sh is the script you want to run. Also see the Job Scripts section and the sbatch documentation.
srun -p <partition> --pty /bin/bashstarts an interactive job. Also see the srun documentation.
squeue -u my_useridshows state of jobs for user my_userid. Also see the squeue documentation.
scontrol show job <job id>views the state of a job. Also see the scontrol documentation.
scancel <job id>cancels a job. Also see the scancel documentation.
squeuewith no arguments retrieves summary information on all jobs scheduled.
Once the job has completed, the stdout and stderr streams will be put in your $HOME directory named with the job id. To verify the job ran successfully, examine these output files.
The following table shows required directives that must be provided with each job. Note that the max number of tasks/processes is dependent on the system you are running on, and some systems may have more required arguments.
Meaning Flag Value Example Job Walltime -t hh:mm:ss -t 00:05:00 Number of tasks/processes -n 1 ... (nodes * max tasks/processes per node) -n 16 Submission Queue -p Queue Name -p normal
Note: In the absence of any other information, Slurm allocates the minimum number of nodes necessary to accommodate
-n number of tasks with each task occupying one CPU core. It is possible to assign fewer process to each node via the -N argument (see the Optional Arguments section), which specifies the desired number of nodes.
Example Command-line Job Submission
All of the required options can be specified on the command-line with
sbatch. For example, say you had the following script "simple_cmd.sh" to run:
#!/bin/bash #Ensures that the node can sleep #print date date #verify that sleep 5 works time sleep 5
In order to run this on the command-line, you could issue (where development is an available queue on the system):
$ sbatch -p development -t 00:01:00 -n 1 simple_cmd.sh
There is also an easier way, as demonstrated in Job Scripts.
Meaning Flag Value Example Number of nodes -N 1 ... max queue length -N 12 Name of Job -J any string -J SimpleJob Stdout -o absolute path -o $HOME/project1/%j.out Sterr -e absolute path -e $HOME/project1/%j.err Job Dependency -d type:job_id -d=after:1234 Email address --mail-user email@domain --firstname.lastname@example.org Email notification type --mail-type BEGIN, END, FAIL, REQUEUE, or ALL --mail-type=ALL Specify Environment Variable --export varname=varvalue, ALL (default), NONE --export LOC=$SCRATCH/x/foo.cdf
Simple Job Script
For the same example from above, the same commands can be put into the batch script itself. This makes it easy to copy and paste to new scripts as well as be confident that a job is submitted the same way over and over again. We'll modify the previous script so that it includes all of the required directives.
All that is required is to place the command line options in the batch script and prepend them with #SBATCH. They appear as comments to the shell, but Slurm parses them for you and applies them. Here is the end result:
#!/bin/bash #Ensures that the node can sleep #SBATCH -t 00:05:00 #SBATCH -n 1 #SBATCH -p development #print date date #verify that sleep 5 works time sleep 5
- Slurm Docs
- Quick Start User Guide - this page lists all of the available Slurm commands
- Command/Option Summary (two page PDF)
- Frequently Asked Questions includes FAQs for Management, Users and Administrators
- Convenient SLURM Commands has examples for getting information on jobs and controlling jobs
- sbatch - used to submit a job script for later execution. The script will typically contain one or more srun commands to launch parallel tasks.