GPU Access¶
Running Jobs¶
Use srun for interactive and sbatch for batch mode. The srun example below is requesting 1 node and 1 GPU with 4GB of memory in the gpu partition. You must use the --gres= option to request a gpu:
srun --partition=gpu --nodes=1 --pty --gres=gpu:v100-pcie:1 --ntasks=1 --mem=4GB --time=01:00:00 /bin/bash
Note
On the gpu partition, requesting more than 1 GPU (--gres=gpu:1) will cause your request to fail. Additionally, one cannot request all the CPUs on that gpu node as they are reserved for other GPUs.
The sbatch example below is similar to the srun example above, but it submits the job in the background, gives it a name, and directs the output to a file:
#!/bin/bash
#SBATCH --partition=gpu
#SBATCH --nodes=1
#SBATCH --gres=gpu:v100-pcie:1
#SBATCH --time=01:00:00
#SBATCH --job-name=gpu_run
#SBATCH --mem=4GB
#SBATCH --ntasks=1
#SBATCH --output=myjob.%j.out
#SBATCH --error=myjob.%j.err
## <your code>
Specifying a GPU type¶
You can add a specific type of GPU to the --gres= option (with either srun or sbatch). For a list of available GPU types, refer to the GPU Types column in gpu-table, that are listed as Public.
--gres=gpu:v100-pcie:1
Note
Requesting a specific type of GPU could result in longer wait times, based on GPU availability at that time.