- 1 Overview
- 2 A basic SLURM job
- 3 Accounts and projects
- 4 Examples of job scripts
- 5 Interactive jobs
- 6 Monitoring jobs
- 7 Cancelling jobs
- 8 Troubleshooting
- 9 Further reading
What's a job?
On computers we are most often familiar with graphical user interfaces (GUIs). There are windows, menus, buttons; we click here and there and the system responds. On Compute Canada servers the environment is different. To begin with, you control it by typing, not clicking. This is called a command line interface. Furthermore, a program you would like to run may not begin immediately, but may instead be put in a waiting list. When the necessary CPU cores are available it will begin, otherwise jobs would interfere with each other leading to performance loss.
You prepare a small text file called a job script that basically says what program to run, where to get the input, and where to put the output. You submit this job script to a piece of software called the scheduler which decides when and where it will run. Once the job has finished you can retrieve the results of the calculation. Normally there is no interaction between you and the program while the job is running, although you can check on its progress if you wish.
Here's a very simple job script:
#!/bin/bash #SBATCH --time=00:01:00 echo 'Hello, world!' sleep 30
It runs the programs
sleep, there is no input, and the output will go to a default location. The lines starting with '#' are directives to the scheduler, telling it things about what the job needs to run. This job, for example, only needs one minute of run time (00:01:00).
The job scheduler
The job scheduler is a piece of software with multiple responsibilities. It must
- maintain a database of all jobs that were submitted until they have finished,
- enforce policies regarding limits and priorities,
- ensure resources are not overloaded, for example by only assigning a CPU core to one job at a time,
- decide which jobs to run and on which compute nodes,
- launch them on those nodes,
- clean up after each job finishes, and
- maintain logs for accounting and troubleshooting.
On Compute Canada clusters, these responsibilities are handled by the Slurm Workload Manager.
You use the job script to ask for the resources needed to run your calculation. Among the resources associated with a job are time and number of processors. In the example above, the time requested is one minute and there will be one processor allocated by default since no specific number is given. We describe below other types of requests such as multiple processors, memory capacity and special processors such as GPUs.
It is important to specify those parameters well. If you ask for less than the calculation needs, the job will be killed for exceeding the requested time or memory limit. If you ask for more than it needs, the job may wait longer than necessary before it starts, and once running it will needlessly prevent others from using those resources.
A basic SLURM job
We can submit the job script
simple_job.sh shown above with sbatch:
[someuser@host ~]$ sbatch simple_job.sh Submitted batch job 1234 [someuser@host ~]$ squeue JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON) 1234 mem12_sho simple_j someuser R 0:03 1 zeno001 [someuser@host ~]$ cat slurm-1234.out Hello, world!
Look at the ST column in the output of squeue to determine the status of your jobs. The two most common states are "PD" for "pending" or "R" for "running". When the job has finished it no longer appears in the
Notice that each job is assigned a "job ID", a unique identification number printed when you submit the job --- 1234 in this example. You can have more than one job in the system at a time, and the ID number can be used to distinguish them even if they have the same name. And finally, because we didn't specify anywhere else to put it the output is placed in a file named with the same job ID number,
You can also specify options to
sbatch on the command line. So for example,
[someuser@host ~]$ sbatch --time=00:30:00 simple_job.sh
will change the time limit of the job to 30 minutes. Any option can be overridden in this way.
Choosing where the output goes
If you want the output file to have a more distinctive name than
slurm‑1234.out, you can use
--output to change it.
The following script sets a job name which will appear in
squeue output, and sends the output to a file prefixed with the job name and containing the job ID number.
#!/bin/bash #SBATCH --time=00:01:00 #SBATCH --job-name=test #SBATCH --output=test-%J.out echo 'Hello, world!'
Error output will normally appear in the same file, just as it would if you were typing commands interactively. If you wish you can split the standard error channel (stderr) from the standard output channel (stdout) by specifying a file name with the
Accounts and projects
Information about your job, like how long it waited, how long it ran, and how many cores it used, is recorded so we can monitor our quality of service and so we can report to our funders how their money is spent. Every job must have an associated account name corresponding to a Compute Canada resource allocation project. Most users only work on one project at a time. If this is you, you don't need to supply an account name; we will quietly attach it to your jobs. However, if you are allowed to submit jobs as part of two or more resource allocation projects, you will have to supply an account name for each job using the
If you run
sbatch without supplying an account name, you will be shown a list of valid account names to chose from.
Examples of job scripts
This example script launches four MPI processes, each with 1024 MB of memory. The run time is limited to 5 minutes.
#!/bin/bash #SBATCH --ntasks=4 # number of MPI processes #SBATCH --mem-per-cpu=1024M # memory; default unit is megabytes #SBATCH --time=0-00:05 # time (DD-HH:MM) srun ./mpi_program
One can have detailed control over the location of MPI processes by, for example, requesting a specific number of processes per node. Hybrid MPI/threaded jobs are also possible. For more on these and other options relating to distributed parallel jobs, see Advanced MPI scheduling.
Threaded or OpenMP job
This example script launches a single process with six CPU cores. Bear in mind that for an application to use OpenMP it must be compiled with the appropriate flag, e.g.
gcc -fopenmp ... or
icc -openmp ...
#!/bin/bash #SBATCH --time=0-0:5 #SBATCH --cpus-per-task=6 ./ompHello
For more on writing and running parallel programs with OpenMP, see OpenMP.
This example is a serial job with one GPU allocated, a memory limit of 4000 MB per node, and a run-time limit of 5 hours. The output filename will include the name of the first node used and the job ID number.
#!/bin/bash #SBATCH --gres=gpu:1 # request GPU "generic resource" #SBATCH --mem=4000M # memory per node #SBATCH --time=0-05:00 # time (DD-HH:MM) #SBATCH --output=%N-%j.out # %N for node name, %j for jobID nvidia-smi
Because no node count is specified in the above example, one node will be allocated. If you were to add
--nodes=3, the total memory allocated would be 12000M. The same goes for
--gres: If you request three nodes, you will get one GPU per node, for a total of three.
For more on running GPU jobs, see Using GPUs with SLURM.
Also known as a task array, an array job is a way to submit a whole set of jobs with one command. The individual jobs in the array are distinguished by an environment variable,
$SLURM_ARRAY_TASK_ID, which is set to a different value for each instance of the job.
sbatch --array=0-7 ... # $SLURM_ARRAY_TASK_ID will take values from 0 to 7 inclusive sbatch --array=1,3,5,7 ... # $SLURM_ARRAY_TASK_ID will take the listed values sbatch --array=1-7:2 ... # Another way to do the same thing sbatch --array=1-100%10 ... # Allow no more than 10 of the jobs to run simultaneously
Though batch submission is the most common and most efficient way to take advantage of our clusters, interactive jobs are also supported. These can be useful for things like:
- Data exploration at the command line
- Interactive "console tools" like R and iPython
- Significant software development, debugging, or compiling
You can start an interactive session on a compute node with salloc. In this example we request two tasks, which corresponds to two CPU cores, for an hour:
name@head$ salloc --time=1:0:0 --ntasks=2 name@node01$ ... # do some work name@node01$ exit # log out of the compute node
For more details see Interactive jobs.
By default squeue will show all the jobs the scheduler is managing at the moment. It may run much faster if you ask only about your own jobs with
squeue -u <username>
You can show only running jobs, or only pending jobs:
squeue -u <username> -t RUNNING squeue -u <username> -t PENDING
You can show detailed information for a specific job with scontrol:
scontrol show jobid -dd <jobid>
Find information about a completed job with sacct, and optionally, control what it prints using
sacct -j <jobid> sacct -j <jobid> --format=JobID,JobName,MaxRSS,Elapsed
You can ask to be notified by email of certain job conditions by supplying options to sbatch:
#SBATCH --mail-user=<email_address> #SBATCH --mail-type=BEGIN #SBATCH --mail-type=END #SBATCH --mail-type=FAIL #SBATCH --mail-type=REQUEUE #SBATCH --mail-type=ALL
Use scancel with the job ID to cancel a job:
You can also use it to cancel all your jobs, or all your pending jobs:
scancel -u <username> scancel -t PENDING -u <username>
Preparing a job script with a word processor instead of a text editor is a common cause of trouble. Best practice is to prepare your job script on the cluster using an editor such as nano, vim, or emacs. If you prefer to prepare or alter the script off-line, then:
- Windows users:
- Use a text editor such as Notepad or Notepad++.
- After uploading the script, use
dos2unixto change Windows end-of-line characters to Linux end-of-line characters.
- Mac users:
- Open a terminal window and use an editor such as nano, vim, or emacs.
- Details on Job scheduling policies at Cedar and Graham.
- Comprehensive documentation is maintained by SchedMD, as well as some tutorials.
- sbatch command options
- There is also a "Rosetta stone" mapping commands and directives from PBS/Torque, SGE, LSF, and LoadLeveler, to SLURM.
- Here is a text tutorial from CÉCI, Belgium
- Here is a rather minimal text tutorial from Bright Computing