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wiki:gpu_jobs

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Running jobs on GPUs

Keck II workstation w01-w10 and w13-w15.keck2.ucsd.edu have NVidia GTX680 GPU installed each. These can be used to run computationally intensive jobs on.

All jobs must be submitted through the SGE queue manager. All rogue jobs will be terminated and user accounts not adhering to this policy will be suspended.

Example SGE scripts

These are example SGE script for running most common applications on the GPUs.

Amber

The optimal AMBER job configuration for KeckII is to use 1 CPU and 1 GPU per run.

#!/bin/bash
#$ -cwd
#$ -q all.q
#$ -V
#$ -N AMBER_job
#$ -S /bin/bash
#$ -e sge.err
#$ -o sge.out

myrun=my_simulation_name

module load nvidia
module load amber
export CUDA_VISIBLE_DEVICES=1

# create a scratch directory on the SDD and copy all runtime data there
export scratch_dir=`mktemp -d /scratch/${USER}.XXXXXX`
current_dir=`pwd`
cp * $scratch_dir
cd $scratch_dir

$AMBERHOME/bin/pmemd.cuda -O -i $myrun.in -o $myrun.out -r $myrun.rst \
 -x $myrun.nc -p  $myrun.prmtop -c $myrun.rst

# copy all data back from the scratch directory
cp * $current_dir
rm -rf $scratch_dir

NAMD

Running NAMD on 2 CPUs and one GPU is the optimal number of CPUs/GPUs for a typical NAMD job on KeckII workstations.

Running namd on 2 CPUs/1 GPU

#!/bin/bash
#$ -cwd
#$ -q all.q
#$ -V
#$ -N NAMD_job
#$ -pe orte-host 2
#$ -S /bin/bash
#$ -e sge.err
#$ -o sge.out

module load nvidia
module load namd-cuda

# create a scratch directory and copy all runtime data there
export scratch_dir=`mktemp -d /scratch/${USER}.XXXXXX`
current_dir=`pwd`
cp * $scratch_dir
cd $scratch_dir

# 2 CPUs/1 GPU
namd2 +idlepoll +p2 +devices 1 apoa1.namd >& apoa1-2.1.out

# copy all data back from the scratch directory
cp * $current_dir
rm -rf $scratch_dir
wiki/gpu_jobs.1350589416.txt.gz ยท Last modified: 2012/10/18 12:43 by admin