HPC UNITe

Consider the following simple python test script( “pytorch_test.py”):

import torch
 
def test_pytorch():
    print("PyTorch version:", torch.__version__)
    print("CUDA available:", torch.cuda.is_available())
 
    if torch.cuda.is_available():
        print("CUDA device:", torch.cuda.get_device_name(0))
        device = torch.device("cuda")
    else:
        device = torch.device("cpu")
 
    # Simple tensor operation
    x = torch.tensor([1.0, 2.0, 3.0], device=device)
    y = torch.tensor([4.0, 5.0, 6.0], device=device)
    z = x + y
    print("Tensor operation result:", z)
 
test_pytorch()

To test it on the unite cluster you can use the folling sbatch scrpit to run it:

#!/bin/bash
#SBATCH --job-name=pytorch_test
#SBATCH --output=pytorch_test.out
#SBATCH --error=pytorch_test.err
#SBATCH --time=00:10:00
#SBATCH --partition=a40
#SBATCH --gres=gpu:1
#SBATCH --mem=4G
#SBATCH --cpus-per-task=2
 
# Load necessary modules (modify based on your system)
module load python/pytorch-2.5.1-llvm-cuda-12.3-python-3.13.1-llvm
 
# Activate your virtual environment if needed
# source ~/your_env/bin/activate
 
# Run the PyTorch script
python3.13 pytorch_test.py