Using srun to create multiple jobs steps
You can use srun
to start multiple job steps concurrently on a single node, e.g. if your job is not big enough to fill a whole node. There are a few details to follow:
- By default, the
srun
command gets exclusive access to all resources of the job allocation and uses all tasks- you therefore need to limit
srun
to only use part of the allocation - this includes implicitly granted resources, i.e. memory and GPUs
- the
--exact
flag is needed. - if running non-mpi programs, use the
-c
option to denote the number of cores, each process should have access to
- you therefore need to limit
srun
waits for the program to finish, so you need to start concurrent processes in the backgroundGood default memory per cpu values (without hyperthreading) are usually are:
standard96 large96 huge96 medium40 large40/gpu --mem-per-cpu
3770M
7781M 15854M 4525M
19075M
Examples
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#!/bin/bash #SBATCH -p standard96 #SBATCH -t 06:00:00 #SBATCH -N 1 srun --exact -n1 -c 10 --mem-per-cpu 3770M ./program1 & srun --exact -n1 -c 80 --mem-per-cpu 3770M ./program2 & srun --exact -n1 -c 6 --mem-per-cpu 3770M ./program3 & wait |
...
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#!/bin/bash #SBATCH -p gpu #SBATCH -t 12:00:00 #SBATCH -N 1 srun --exact -n1 -c 10 -G1 --mem-per-cpu 19075M ./single-gpu-program & srun --exact -n1 -c 10 -G1 --mem-per-cpu 19075M ./single-gpu-program & srun --exact -n1 -c 10 -G1 --mem-per-cpu 19075M ./single-gpu-program & srun --exact -n1 -c 10 -G1 --mem-per-cpu 19075M ./single-gpu-program & wait |
Using the Linux parallel command to run a large number of tasks
If you have to run many nearly identical but small tasks (single-core, little memory) you can try to use the Linux parallel command. To use this approach you first need to write a bash
-shell script, e.g. task.sh
, which executes a single task. As an example we will use the following script:
...
Codeblock |
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$ sbatch parallel_job.sh |
Looping over two arrays
You can use parallel
to loop over multiple arrays. The --xapply
option controls, if all permuatations are used or not:
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