Job script for Saga.

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Martin Lilleeng Sætra 2020-10-16 22:30:14 +02:00
parent 51b54b7711
commit a321dcdb43

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#!/bin/bash
# Job name:
#SBATCH --job-name=saga-test
#
# Project:
#SBATCH --account=nn9550k
#
# Wall clock limit:
#SBATCH --time=00:10:00
#
# Ask for 1 GPU (max is 2)
# Note: The environment variable CUDA_VISIBLE_DEVICES will show which GPU
# device(s) to use. It will have values '0', '1' or '0,1' corresponding to
# /dev/nvidia0, /dev/nvidia1 or both, respectively.
#SBATCH --partition=accel --gres=gpu:1
#
# Max memory usage per task (core) - increasing this will cost more core hours:
#SBATCH --mem-per-cpu=4G
#
# Number of tasks:
#SBATCH --nodes=2 --ntasks-per-node=1
## Set up job environment: (this is done automatically behind the scenes)
## (make sure to comment '#' or remove the following line 'source ...')
# source /cluster/bin/jobsetup
module restore system # instead of 'module purge' rather set module environment to the system default
module load CUDA/10.2.89
# It is also recommended to to list loaded modules, for easier debugging:
module list
set -o errexit # exit on errors
set -o nounset # Treat unset variables as errors (added for more easily discovering issues in your batch script)
## Copy input files to the work directory:
mkdir $SCRATCH/ShallowWaterGPU
cp -r . $SCRATCH/ShallowWaterGPU
## Make sure the results are copied back to the submit directory (see Work Directory below):
# chkfile MyResultFile
# chkfile is replaced by 'savefile' on Saga
savefile "$SCRATCH/ShallowWaterGPU/*.log"
savefile "$SCRATCH/ShallowWaterGPU/*.nc"
## Do some work:
cd $SCRATCH/ShallowWaterGPU
srun /cluster/home/$HOME/.conda/envs/ShallowWaterGPU_HPC/bin/python3 --version
srun /cluster/home/$HOME/.conda/envs/ShallowWaterGPU_HPC/bin/python3 mpiTesting.py