Slurm Script Examples

Title: run_python.slurm

#!/bin/bash
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1                                    # Run on a single CPU
#SBATCH --time=00:05:00                        # Time limit hrs:min:sec
#SBATCH --account="accountID"

JOBID=$( echo ${PBS_JOBID} | cut -f1 -d. )

module load Miniforge3
eval "$(conda shell.bash hook)"

# Change Directory to the working directory
cd ${PBS_O_WORKDIR} 

# Run your python code
python path/to/your/python_file.py

Usage

$ sbatch run_python.slurm

Title: run_python_legate.slurm

#!/bin/bash
#SBATCH --job-name=serial_job_test     # Job name
#SBATCH --mail-type=END,FAIL               # Mail events (NONE, BEGIN, END, FAIL, ALL)
#SBATCH --mail-user=NetID@kennesaw.edu     # Where to send mail 
#SBATCH --cpus-per-task=4                                     # Request 4 cores
#SBATCH --mem=503gb                                 # Job memory request
#SBATCH --gres=gpu:4
#SBATCH --time=00:05:00                        # Time limit hrs:min:sec
#SBATCH --output=serial_test_%j.log    # Standard output and error log
pwd; hostname; date

JOBID=$( echo ${PBS_JOBID} | cut -f1 -d. )

module load MIniforge3
eval "$(conda shell.bash hook)" 
conda activate legate

# Change Directory to the working directory 
cd ${PBS_O_WORKDIR} 

# Run your code
python path/to/your/python_file.py

date

 Usage

 $ sbatch run_python_legate.slurm

Note: If you only request 1 node, 4 is the maximum gpu you can request.  You will need at least 4 cpu-cores to make use of 4 gpus.

Note: 503 GB is the maximum memory that you can request.

Title: run_matlab.slurm

#!/bin/bash
#SBATCH --nodes=1
#SBATCH --cpus-per-task=12
#SBATCH --partition="defq"
#SBATCH --time=10:00:00
#SBATCH --mail-type="BEGIN,END,FAIL"
#SBATCH --mail-user="netid@kennesaw.edu" 
#SBATCH --account="account_name" 

pwd; hostname; date

JOBID=`echo $SLURM_JOBID | cut -f1 -d.`

module load MATLAB

# Create a temp workdir under work
mkdir -p ${HOME}/work/matlab
export SLURM_MATLAB_WORKDIR=$( mktemp -d -p ${HOME}/work/matlab workdir_XXXXXXXXXX )

matlab -nodisplay -nosplash -logfile ${FILE}.log -r "run ${FILE}"

# Delete temp workdir
rm -rf ${SLURM_MATLAB_WORKDIR}

date

Usage

sbatch --export=ALL,FILE=${PWD}/matlab_script.m run_matlab.slurm

Note: This command includes an argument that passes the filename into the slurm file variable ${FILE} for better reusability.

Note: some MATLAB code can make use any available cpu resources, so I have asked for 12 cores in this example.

Title: run_gaussian.slurm

#!/usr/bin/env bash
#SBATCH --partition="defq"
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=16 #SBATCH --time=01:00:00
#SBATCH --export="ALL"
#SBATCH --mail-type="BEGIN,END,FAIL,TIME_LIMIT_90"
#SBATCH --mail-user="netid@kennesaw.edu"
#SBATCH --account="account_name"

date;hostname;pwd
 
# Load the Gaussian Modules
module load Gaussian

export WORK_DIR=$SLURM_SUBMIT_DIR
cd $WORK_DIR

datestamp=$(date +%Y-%m-%d.%H%M%S)

g16 -p=${SLURM_CPUS_PER_TASK} ${FILE} > ${FILE%.*}.${datestamp}.out

date

Usage

$ sbatch --export=ALL,FILE=${PWD}/my_script.com run_gaussian.slurm

Note: the slurm file includes the argument to send an email if 90% of the walltime has expired.  Exceding the walltime will kill a job.

Title: run_R.slurm

#!/bin/bash
#SBATCH --job-name=R_mpi_job
#SBATCH --mail-type=ALL
#SBATCH --mail-user=NetID@kennesaw.edu
#SBATCH --nodes=2
#SBATCH --ntasks=8
#SBATCH --cpus-per-task=1
#SBATCH --ntasks-per-node=8
#SBATCH --time=00:30:00

pwd; hostname; date

JOBID=$( echo ${SLURM_JOBID} | cut -f1 -d. )

module purge
module load R

cd ${SLURM_SUBMIT_DIR}

mpiexec --quiet R --slave --file=${FILE} > ${FILE}.${JOBID}

date

Usage

$ sbatch --export=ALL,FILE=${PWD}/mycode.R run_R.slurm 

Note: this will send mail for start, end, error and when the time limit reaches 50%, 80% and 90%.

Title: run_vasp_gpu.slurm

#!/bin/bash
#SBATCH --job-name=vasptest
#SBATCH --mail-type=ALL
#SBATCH --mail-user=NetID@kennesaw.edu
#SBATCH --nodes=1
#SBATCH --ntasks=8
#SBATCH --cpus-per-task=8
#SBATCH --mem-per-cpu=10GB
#SBATCH --gres=gpu:4
#SBATCH --time=00:30:00

module purge
module load cuda/10.0.130  intel/2018  openmpi/4.0.0 vasp/5.4.4

srun --mpi=pmix_v3 vasp_gpu

Usage

 sbatch vasp_gpu.slurm

Note:  untested on vhpc