slurm | 易学教程

Is it possible to force SLURM to have access to only job's running folder and not alter any other file?

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I observe that when I run a SLURM job, it could create files on other folder paths and also could remove them. It seems dangerous that via SLURM job they can access others folders/files and make changes on them. $ sbatch run.sh run.sh: #!/bin/bash #SBATCH -o slurm.out # STDOUT #SBATCH -e slurm.err # STDERR echo hello > /home/avatar/completed.txt rm /home/avatar/completed.txt [Q] Is it possible to force SLURM to only have access to its own running folder and not others? Files access is controlled through UNIX permissions, so a job can only write where the submitting user has permission to write

Could SLURM trigger a script(implemented by the frontend-SLURM user) when any job is completed?

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问题 As we know SLURM can sent a e-mail when a job is completed. In addition to that, similar to mailing mechanism when job is completed: [Q] Could SLURM trigger a script(implemented by the frontend-SLURM user) when any job is completed? Example solution: This would force me to have while() to check and wait is the submitted job is completed. This might eat additional CPU usage. jobID=$(sbatch -U user -N1 run.sh | cut -d " " -f4-); job_state=$(sacct -j $jobID --format=state | tail -n1 | head -n1)

SLURM: How to view completed jobs full name?

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sacct -n returns all job's name trimmed for example" QmefdYEri+ . [Q] How could I view the complete name of the job, instead of its trimmed version? -- $ sacct -n 1194 run.sh debug root 1 COMPLETED 0:0 1194.batch batch root 1 COMPLETED 0:0 1195 run_alper+ debug root 1 COMPLETED 0:0 1195.batch batch root 1 COMPLETED 0:0 1196 QmefdYEri+ debug root 1 COMPLETED 0:0 1196.batch batch root 1 COMPLETED 0:0 I use the scontrol command when I am interested in one particular jobid as shown below (output of the command taken from here ). $ scontrol show job 106 JobId=106 Name=slurm-job.sh UserId=rstober

How to use multiple nodes/cores on a cluster with parellelized Python code

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问题 I have a piece of Python code where I use joblib and multiprocessing to make parts of the code run in parallel. I have no trouble running this on my desktop where I can use Task Manager to see that it uses all four cores and runs the code in parallel. I recently learnt that I have access to a HPC cluster with 100+ 20 core nodes. The cluster uses SLURM as the workload manager. The first question is: Is it possible to run parallelized Python code on a cluster? If it is possible, Does the Python

difference between slurm sbatch -n and -c

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The cluster that I work with recently switched from SGE to SLURM. I was wondering what the difference between sbatch options --ntasks and --cpus-per-task ? --ntasks seemed appropriate for some MPI jobs that I ran but did not seem appropriate for some OpenMP jobs that I ran. For the OpenMP jobs in my SLURM script, I specified: #SBATCH --ntasks=20 All the nodes in the partition are 20core machines, so only 1 job should run per machine. However, multiple jobs were running simultaneously on each node. Tasks in SLURM are basically processes / mpi ranks - it seems you just want a single task. A task

slurm: DependencyNeverSatisfied error even after crashed job re-queued

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问题 My goal is to build a pipeline using slurm dependencies and handle a case where a slurm job crashes. Based on following answer and guide 29th section, it is recommended to use scontrol requeue $jobID , that will re-queue the already cancelled job. if job crashes can be detected from within the submission script, and crashes are random, you can simply requeue the job with scontrol requeue $SLURM_JOB_ID so that it runs again. After I have re-queued a cancelled job, its dependent job remain as

SLURM sbatch multiple parallel calls to executable

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问题 I have an executable that takes multiple options and multiple file inputs in order to run. The executable can be called with a variable number of cores to run. E.g. executable -a -b -c -file fileA --file fileB ... --file fileZ --cores X I'm trying to create an sbatch file that will enable me to have multiple calls of this executable with different inputs. Each call should be allocated in a different node (in parallel with the rest), using X cores. The parallelization at core level is taken

slurm: How to connect front-end with compute nodes?

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I have a front end and two compute nodes All have same slurm.conf file which ends with (for detail please see: https://gist.github.com/avatar-lavventura/46b56cd3a29120594773ae1c8bc4b72c ): NodeName=ebloc2 NodeHostName=ebloc NodeAddr=54.227.62.43 CPUs=1 PartitionName=debug Nodes=ebloc2 Default=YES MaxTime=INFINITE State=UP NodeName=ebloc4 NodeHostName=ebloc NodeAddr=54.236.173.82 CPUs=1 PartitionName=debug Nodes=ebloc4 Default=YES MaxTime=INFINITE State=UP slurmctld : only checks first written nodes information and does not check the second written node's. When I try to send a job I recieve

SLURM display the stdout and stderr of an unfinished job

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问题 I used to use a server with LSF but now I just transitioned to one with SLURM. What is the equivalent command of bpeek (for LSF) in SLURM? bpeek bpeek Displays the stdout and stderr output of an unfinished job I couldn't find the documentation anywhere. If you have some good references for SLURM, please let me know as well. Thanks! 回答1: You might also want to have a look at the sattach command. 回答2: I just learned that in SLURM there is no need to do bpeek to check the current standard output

SLURM Submit multiple tasks per node?

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I found some very similar questions which helped me arrive at a script which seems to work however I'm still unsure if I fully understand why, hence this question.. My problem (example): On 3 nodes, I want to run 12 tasks on each node (so 36 tasks in total). Also each task uses OpenMP and should use 2 CPUs. In my case a node has 24 CPUs and 64GB memory. My script would be: #SBATCH --nodes=3 #SBATCH --ntasks=36 #SBATCH --cpus-per-task=2 #SBATCH --mem-per-cpu=2000 export OMP_NUM_THREADS=2 for i in {1..36}; do srun -N 1 -n 1 ./program input${i} >& out${i} & done wait This seems to work as I