GPyTorch on Aurora

1. Login and queue a job

Login to Aurora

ssh <username>@aurora.alcf.anl.gov

Refer to Getting Started on Aurora for additional information. In particular, you need to set the environment variables that provide access to the proxy host.

Note

The instructions below should be ran directly from a compute node.

Explicitly, to request an interactive job (from aurora-uan):

qsub -I -q [your_Queue] -l select=1,walltime=60:00 -A [your_ProjectName]

Refer to job scheduling and execution for additional information.

2. Once on a Compute Node, Load Modules

module use /soft/modulefiles
module load frameworks
python3 -m venv --system-site-packages env_gpytorch
source env_gpytorch/bin/activate
python3 -m pip install gpytorch

Optional

Create a activation_env.sh file that contains the following lines:

module use /soft/modulefiles
module load frameworks
source env_gpytorch/bin/activate

and do source activation_env.sh to activate your environment for subsequent runs.

3. Running on GPUs

To run on GPUs, one needs to add to code

import intel_extension_for_pytorch as ipex
 ```
and set the device as follows in the code:

```python
if torch.cuda.is_available():
    device = torch.device('cuda')
elif torch.xpu.is_available():
    device = torch.device('xpu')
else: 
    device = torch.device('cpu')

(One might need to install an earlier version of GPyTorch for multiple GPUs running.)