Difference between revisions of "GPU Usage"
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=== How to request a GPU === | === How to request a GPU === | ||
In order to use | In order to use a GPUs for your Job you will have to request a Generic resource (GRES). You can do that by adding the following line to your jobscript: | ||
#SBATCH --gres=gpu:1 | #SBATCH --gres=gpu:1 | ||
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#SBATCH --gres=gpu:3 | #SBATCH --gres=gpu:3 | ||
You will also have to add the following line to your jobscript: | |||
#SBATCH --partition=mpcg.p | |||
This will allow you to use one (or more) of the Tesla P100 cards. You could also add the line | |||
#SBATCH --partition=mpcb.p | |||
which has some nodes with GTX 1080 cards. |
Revision as of 08:49, 14 March 2018
Introduction
Since we got 12 dedicated GPU nodes (mpcg[001-009]) containing one NVIDIA Tesla P100 each and four additional nodes (mpc[001-004]) containing two GTX 1080 each, its possible to run your jobs with one or multiple associated GPUs. The usage might not be self-explanatory, we created this guide to help you get everything set up and working properly.
How to request a GPU
In order to use a GPUs for your Job you will have to request a Generic resource (GRES). You can do that by adding the following line to your jobscript:
#SBATCH --gres=gpu:1
This will request one GPU. A suitable node will be automatically chosen by SLURM.
Of couse its possible to request more than one GPU. With the following line of code you will request 3 GPUs:
#SBATCH --gres=gpu:3
You will also have to add the following line to your jobscript:
#SBATCH --partition=mpcg.p
This will allow you to use one (or more) of the Tesla P100 cards. You could also add the line
#SBATCH --partition=mpcb.p
which has some nodes with GTX 1080 cards.