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#!/bin/bash #SBATCH --account=shared #SBATCH --partition=shared #SBATCH --qos=scavenger # #SBATCH --job-name=test #SBATCH --output=output-%j.txt #SBATCH --error=output-%j.txt # #SBATCH --ntasks=1 #SBATCH --cpus-per-task=12 #SBATCH --mem-per-cpu=1g # #SBATCH --time=10:00 # #SBATCH --gpu geforce_gtx_1080_ti:gpus 1 <commands here> |
In the above example, we submit a job named 'test' and output both stdout and stderr to the same file (%j will be replaced with the Job ID). We request a single Task (think of it as an MPI rank) and that single task will request 12 CPUs; each of which will be allocated 1GB of RAM - so a total of 12GB. By default, the --ntasks will be equivalent to the number of nodes (servers) asked for. In order to aid scheduling (and potentially prioritising the Job), we limit the length of the Job to 10 minutes.
We also request a single 1080 GPU with the Job. This will be exposed via CUDA_VISIBLE_DEVICES. To specify specific GPU's, see below.
You will need an account (see below). All SLAC users have access to the "shared" partition with a quality of service of "scavenger". This is so that stakeholders of machines in the SDF will get priority access to their resources, whilst any user can use all resources as long as the 'owners' of the hardware isn't wanting to use it. As such, owners (or stakeholders) will have qos "normal" access to their partitions (of which such hosts are also within the shared partition).
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