Accessing the GPGPU TESLA (CUDA resources on lonsdale) enabled nodes
There are currently two methods for accessing the TESLA (CUDA capable) nodes on the lonsdale compute partition.
- For work-hours interactive and batch jobs, add this flag to your script/salloc: "
--reservation=cuda". More details below. - For out-of-hours batch jobs, add this flag to your script/salloc: "
--gres=gpu:1". More details below.
Please note that we currently only have two machines with TESLA cards and each node only has 2 cards.
Work-hours Interactive and Batch Jobs
There is a reservation in place from 8am til 8pm to allow for interactive and batch use of the CUDA/GPU-enable TESLA nodes on the lonsdale compute partition.
To access it, add "--reservation=cuda" to your sbatch, srun or salloc commands.
Out-of-hours Batch Jobs
Please add "--gres=gpu:1" to your sbatch, srun or salloc commands. Examples are given below.
$ salloc --gres=gpu:1 -p compute -N 1 -t 01:00:00 -U my_project_name
or
$ srun --gres=gpu:1 -p compute -N 1 -t 01:00:00 -U my_project_name hostname lonsdale-n129.cluster
or
#!/bin/sh #SBATCH -N 1 # 1 node #SBATCH -t 1-03:00:00 # 1 day and 3 hours #SBATCH -p compute # partition name #SBATCH -U my_project # your project name - contact Ops if unsure what this is #SBATCH -J my_job_name # sensible name for the job #SBATCH --gres=gpu:1 mpirun ./mycuda.x