SLURM job submission scripts

slurmjob.sh

#!/bin/bash
#SBATCH --job-name=newjob
#SBATCH -n 1                # Number of cores
#SBATCH -N 1                # Ensure that all cores are on one machine
#SBATCH -t 0-01:00          # Runtime in D-HH:MM, minimum of 10 minutes
#SBATCH -p shared,general   # Partition to submit to, whichever is faster
#SBATCH --mem-per-cpu=4G    # Memory (see also --mem)
#SBATCH -o joboutput_%j.out # File to which STDOUT will be written, %j inserts jobid
#SBATCH -e joberrors_%j.err # File to which STDERR will be written, %j inserts jobid
#SBATCH --mail-type=ALL     # Type of email notification- BEGIN,END,FAIL,ALL
#SBATCH --mail-user=user@email.domain  #Email to which notifications will be sent

echo "Now running job ${SLURM_JOB_ID}"
# Reference: https://slurm.schedmd.com/
# Usage: "sbatch slurmjob.sh"

slurmjob_array.sh

#!/bin/bash
#SBATCH --job-name=newjob
#SBATCH -n 1                # Number of cores
#SBATCH -N 1                # Ensure that all cores are on one machine
#SBATCH -t 0-01:00          # Runtime in D-HH:MM, minimum of 10 minutes
#SBATCH -p shared,general   # Partition to submit to, whichever is faster
#SBATCH --mem-per-cpu=4G    # Memory (see also --mem)
#SBATCH -o joboutput_%A_%a.out  # File to which STDOUT will be written, %A inserts jobid, %a inserts arrayid
#SBATCH -e joberrors_%A_%a.err  # File to which STDERR will be written, %j inserts jobid, %a inserts arrayid
#SBATCH --mail-type=ALL      # Type of email notification- BEGIN,END,FAIL,ALL
#SBATCH --mail-user=user@email.domain  #Email to which notifications will be sent

echo "Now running array job ${SLURM_ARRAY_JOB_ID}, task ${SLURM_ARRAY_TASK_ID}"
# Reference: https://slurm.schedmd.com/job_array.html
# Usage: "sbatch --array=0-31 slurmjob_array.sh"

slurmjob_testGPU.sh

#!/bin/bash
#SBATCH --job-name=testgpu
#SBATCH -n 1                # Number of cores
#SBATCH -N 1                # Ensure that all cores are on one machine
#SBATCH -t 0-00:10          # Runtime in D-HH:MM, minimum of 10 minutes
#SBATCH -p gpu              # Partition to submit to
#SBATCH --gres=gpu:teslaK80:1   # request for 1 GPU logical processing unit of type TeslaK80
#SBATCH --mem-per-cpu=4G    # Memory (see also --mem)
#SBATCH -o joboutput_%j.out # File to which STDOUT will be written, %j inserts jobid
#SBATCH -e joberrors_%j.err # File to which STDERR will be written, %j inserts jobid
#SBATCH --mail-type=ALL     # Type of email notification- BEGIN,END,FAIL,ALL
#SBATCH --mail-user=user@email.domain  #Email to which notifications will be sent

module load gcc/6.2.0 python/3.6.0 cuda/10.0
source /path/to/virtualenv/bin/activate
gpuAvail=$(echo "import tensorflow as tf; print(tf.test.is_gpu_available())" | python)
echo "GPU available? $gpuAvail"
nvidia-smi
# Reference: https://wiki.rc.hms.harvard.edu/display/O2/Using+O2+GPU+resources
# Usage: "sbatch slurmjob.sh"