The Lengau cluster at the CHPC includes 9 GPU compute nodes with a total of 24 Nvidia V100 GPU devices.

Access to these GPU node is by PI application only though the CHPC Helpdesk.

Research programme allocations will be depleted by a factor of the wallclock time and the number of GPUs (1, 2, or 4) requested by the job.

gpu_allocation_used = 40 * runtime * ngpus

Some pre-built applications have automated scripts that you can use to launch them:

• GROMACS
• AMBER18
• NAMD

There are three queues available in PBSPro which access the GPU nodes:

The maximum wall clock time on all GPU queues is 12 hours.

#PBS -l walltime=12:00:00

It is better to specify a shorter walltime if your code executes in less time: this allows the scheduler a better chance of running your job sooner.

A single interactive session may be request on a GPU node by

qsub -I -q gpu_1 -P PRJT1234

NB: Replace PRJT1234 with your project number.

The default time for an interactive session is 1 hour.

#!/bin/bash
#PBS -N nameyourjob
#PBS -q gpu_1
#PBS -l ncpus=10:ngpus=1
#PBS -P PRJT1234
#PBS -l walltime=4:00:00
#PBS -o /mnt/lustre/users/USERNAME/cuda_test/test1.out
#PBS -e /mnt/lustre/users/USERNAME/cuda_test/test1.err
#PBS -m abe
#PBS -M your.email@address
 
cd /mnt/lustre/users/USERNAME/cuda_test
 
echo
echo `date`: executing CUDA job on host ${HOSTNAME}
echo
 
# Run program
./hello_cuda

The Nvidia V100 GPUs are programmed using the CUDA development tools.

To build a CUDA code (library or application) for the GPU nodes requires loading the appropriate CUDA module before compiling. The CUDA runtime tools are already installed on all GPU nodes and won't need to be loaded specifically unless you require (for some reason) a different version. The V100 GPUs have Volta architecture cores, support CUDA compute capability 7.0, and require CUDA 9 or newer.

• Detailed overview of the V100.
• Nvidia whitepaper on the Volta architecture.
• CUDA Toolkit Release Notes