slurm

I am trying to understand what the difference is between SLURM's srun and sbatch commands. I will be happy with a general explanation, rather than specific answers to the following questions, but here are some specific points of confusion that can be a starting point and give an idea of what I'm looking for. According to the documentation , srun is for submitting jobs, and sbatch is for submitting jobs for later execution, but the practical difference is unclear to me, and their behavior seems to be the same. For example, I have a cluster with 2 nodes, each with 2 CPUs. If I execute srun

I am wondering how I might be able to run 500 parallel jobs in R using the Rscript function. I currently have an R file that has the header on top: args <- commandArgs(TRUE) B <- as.numeric(args[1]) Num.Cores <- as.numeric(args[2]) Outside of the R file, I wish to pass which of the 500 jobs are to be run, which is specified by B . Also, I would like to control the number of cores/CPUs available to each job, Num.Cores . I am wondering if there is software or guides that can allow this. I currently have a CentOS 7/Linux server and I know one way is to install Slurm. However, it is quite a hassle

I was using SLURM to use some computing cluster and it had the -ntasks or -n . I have obviously read the documentation for it ( http://slurm.schedmd.com/sbatch.html ): sbatch does not launch tasks, it requests an allocation of resources and submits a batch script. This option advises the Slurm controller that job steps run within the allocation will launch a maximum of number tasks and to provide for sufficient resources. The default is one task per node, but note that the --cpus-per-task option will change this default. the specific part I do not understand what it means is: run within the

I could get access to a computing cluster, specifically one node with two 12-Core CPUs, which is running with Slurm Workload Manager . I would like to run TensorFlow on that system but unfortunately I were not able to find any information about how to do this or if this is even possible. I am new to this but as far as I understand it, I would have to run TensorFlow by creating a Slurm job and can not directly execute python/tensorflow via ssh. Has anyone an idea, tutorial or any kind of source on this topic? It's relatively simple. Under the simplifying assumptions that you request one process

I wanted to run a python script main.py multiple times with different arguments through a sbatch_run.sh script as in: #!/bin/bash #SBATCH --job-name=sbatch_run #SBATCH --array=1-1000 #SBATCH --exclude=node047 arg1=10 #arg to be change during runs arg2=12 #arg to be change during runs python main.py $arg1 $arg2 The arguments are encoded in the bash file ran by sbatch. I was worried that if I ran sbatch_run.sh multiple times one after the other but changing the value of arg1 and arg2 during each run, that it might cause errors in my runs. For example if I do: sbatch sbatch_run.sh # with arg1=10

I suppose it's a pretty trivial question but nevertheless, I'm looking for the (sacct I guess) command that will display the CPU time and memory used by a slurm job ID. You're right that the sacct command is what you're looking for. The --format switch is the other key element. If you run this command: sacct -e you'll get a printout of the different fields that can be used for the --format switch. The details of each field are described in the Job Account Fields section of the man page. For CPU time and memory, CPUTime and MaxRSS are probably what you're looking for. cputimeraw can also be