Running RMG in parallel with a SGE scheduler

Nick previously made a wiki on how to use RMG-Py in parallel with SLURM scheduler. Since some servers are still using SGE scheduler, this wiki is going to give an example of submitting a RMG-Py job when you have SGE scheduler.

In order to help understand, the example job is also named min_par reserving 24 CPUs on a single node (#$ -pe singlenode 24), but uses only 12 workers (= 12 CPUs) in parallel during the RMG-Py simulation.

Make sure that:

• the queue named normal exists on your SGE scheduler
• you modify the path to the parent folder of the RMG-Py installation folder
• you have an anaconda environment named rmg_env that contains RMG-Py's dependencies
• make sure that the working directory from which you launched the job contains the RMG-Py input file input.py

-v adds verbosity to the output log file

#! /bin/bash

#$ -o job.log
#$ -l normal
#$ -N min_par
#$ -pe singlenode 24

WORKERS=12

RMG_WS=/path/to/RMG/parent/folder
export PYTHONPATH=$PYTHONPATH:$RMG_WS/RMG-Py/

source activate rmg_env
python -m scoop --tunnel -n $WORKERS -v $RMG_WS/RMG-Py/rmg.py input.py

source deactivate