Do I need a single bash file for each task in SLURM? - bash

I am trying to launch several task in a SLURM-managed cluster, and would like to avoid dealing with dozens of files.
Right now, I have 50 tasks (subscripted i, and for simplicity, i is also the input parameter of my program), and for each one a single bash file slurm_run_i.sh which indicates the computations configuration, and the srun command:
#!/bin/bash
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH -J pltCV
#SBATCH --mem=30G
srun python plotConvergence.py i
I am then using another bash file to submit all these tasks, slurm_run_all.sh
#!/bin/bash
for i in {1..50}:
sbatch slurm_run_$i.sh
done
This works (50 jobs are running on the cluster), but I find it troublesome to have more than 50 input files. Searching a solution, I came up with the & command, obtaining something as:
#!/bin/bash
#SBATCH --ntasks=50
#SBATCH --cpus-per-task=1
#SBATCH -J pltall
#SBATCH --mem=30G
# Running jobs
srun python plotConvergence.py 1 &
srun python plotConvergence.py 2 &
...
srun python plotConvergence.py 49 &
srun python plotConvergence.py 50 &
wait
echo "All done"
Which seems to run as well. However, I cannot manage each of these jobs independently: the output of squeue shows I have a single job (pltall) running on a single node. As there are only 12 cores on each node in the partition I am working in, I am assuming most of my jobs are waiting on the single node I've been allocated to. Setting the -N option doesn't change anything too.. Moreover, I cannot cancel some jobs individually anymore if I realize there's a mistake or something, which sounds problematic to me.
Is my interpretation right, and is there a better way (I guess) than my attempt to process several jobs in slurm without being lost among many files ?

What you are looking for is the jobs array feature of Slurm.
In your case, you would have a single submission file (slurm_run.sh) like this:
#!/bin/bash
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH -J pltCV
#SBATCH --mem=30G
#SBATCH --array=1-50
srun python plotConvergence.py ${SLURM_ARRAY_TASK_ID}
and then submit the array of jobs with
sbatch slurm_run.sh
You will see that you will have 50 jobs submitted. You can cancel all of them at once or one by one. See the man page of sbatch for details.

Related

Using OpenMP and OpenMPI together under Slurm

I have written a C++ code that uses both OpenMP and OpenMPI. I want to use (let's say) 3 nodes (so size_Of_Cluster should be 3) and use OpenMP in each node to parallelize the for loop (There are 24 cores in a node). In essence I want MPI ranks be assigned to nodes. The Slurm script I have written is as follows. (I have tried many variations but could not come up with the "correct" one. I would be grateful if you could help me.)
#!/bin/bash
#SBATCH -N 3
#SBATCH -n 72
#SBATCH -p defq
#SBATCH -A akademik
#SBATCH -o %J.out
#SBATCH -e %J.err
#SBATCH --job-name=MIXED
module load slurm
module load shared
module load gcc
module load openmpi
export OMP_NUM_THREADS=24
mpirun -n 3 --bynode ./program
Using srun did not help.
The relevant lines are:
#SBATCH -N 3
#SBATCH -n 72
export OMP_NUM_THREADS=24
This means you have 72 MPI processes, and each creates 24 thread. For that to be efficient you probably need 24x72 cores. Which you don't have. You should specify:
#SBATCH -n 3
Then you will have 3 processes, with 24 threads per process.
You don't have to worry about the placement of the ranks on the nodes: that is done by the run time. You could for instance let each process print MPI_Get_processor_name to confirm.

How to correctly submit an array of jobs using slurm

I'm trying to submit an array of jobs using slurm, but it's not working as I expected. My bash script is test.sh:
#!/bin/bash
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem=10G
#SBATCH --account=myaccount
#SBATCH --partition=partition
#SBATCH --time=10:00:00
###Array setup here
#SBATCH --array=1-6
#SBATCH --output=test_%a.out
echo TEST MESSAGE 1
echo $SLURM_ARRAY_TASK_ID
python test.py
The test.py code:
print('TEST MESSAGE 2')
I then submitted this job by doing:
sbatch --wrap="bash test.sh"
I'm not even sure if this is how I should run it. Because there are already SBATCH commands in the bash script, should I just be running bash test.sh?
I was expecting that 5 jobs would be submitted and that $SLURM_ARRAY_TASK_ID would increase incrementally, but that's not happening. Just one job is submitting and the output is:
TEST MESSAGE 1
TEST MESSAGE 2
So the $SLURM_ARRAY_TASK_ID never get's printed and seems to be the problem. Can anyone tell me what I'm doing wrong?
You just need to submit the script with sbatch test.sh. Using --wrap in the way you've done it just runs test.sh as a simple Bash script, so none of the Slurm-specific parts are used.

SLURM How to start a script once per node

I have a Big Cluster available through SLURM.
I want to start my script e.g. ./calc on every requested node with a specified amount of cores. So for example on 2 nodes, 16 cores each.
I start with sbatch script
#SBATCH -N 2
#SBATCH --ntasks-per-node=16
srun -N 1 ./calc 2 &
srun -N 1 ./clac 2 &
wait
It doesn't work as intended though.
I tried many configurations of --ntask --nodes --cpus-per-task but nothing worked and I'm very lost.
I also don't understand the difference between task and CPUs in SLURM
In your example, you ask slurm to launch 16 tasks per node, on 2 nodes. At the end of the job, slurm will probably runs 8x(srun)x2 nodes tasks.
For your needs, you don't need to specify that you want 2 nodes specifically instead of the jobs have to run on 2 two different nodes.
For your example, run the following sbatch :
#!/bin/bash
#SBATCH --ntasks=2
#SBATCH --cpus-per-task=16
#SBATCH --hint=nomultithread
srun <my program>
In this example, slurm will run 2 times the program with 16 cores. The nomultithread is optional and depends the cluster configuration. If the hyper-threading is activated, this will be 16 virtual cpus.
I found this to be a working solution. It turned out the most important thing was to define all parameters nodes tasks cpus
#!/bin/bash
#SBATCH -N 2
#SBATCH --ntasks-per-node=1
#SBATCH --cpus-per-task=16
srun -N 1 -n 1 -c 16 ./calc 2 &
srun -N 1 -n 1 -c 16 ./calc 2 &
wait

What does the keyword --exclusive mean in slurm?

This is a follow up question from [How to run jobs in paralell using one slurm batch script?]. The goal was to create a single SBatch-Script, which can start multiple processes and run them in parallel. The Answer given by
damienfrancois was very detailed and looked something like this.
#!/bin/bash
#
#SBATCH --job-name=test
#SBATCH --output=/dev/null
#SBATCH --error=/dev/null
#SBATCH --partition=All
srun -n 1 -c 1 --exclusive sleep 60 &
srun -n 1 -c 1 --exclusive sleep 60 &
....
wait
However, I am not able to understand the exclusive keyword. If I use the keyword, one node of the cluster is chosen and all processes are launched there. However, I would like Slurm to distribute the ["sleeps"/steps] over the entire cluster.
So how does the keyword exclusive work ? According to the Slurm documentaion, the restriction to one node should not happen, since the keyword is used within a step-allocation.
[I am new to Slurm]

comment in bash script processed by slurm

I am using slurm on a cluster to run jobs and submit a script that looks like below with sbatch:
#!/usr/bin/env bash
#SBATCH -o slurm.sh.out
#SBATCH -p defq
#SBATCH --mail-type=ALL
#SBATCH --mail-user=my.email#something.com
echo "hello"
Can I somehow comment out a #SBATCH line, e.g. the #SBATCH --mail-user=my.email#something.com in this script? Since the slurm instructions are bash comments themselves I would not know how to achieve this.
just add another # at the beginning.
##SBATCH --mail-user...
This will not be processed by Slurm

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