DAIC Experimental
— Documentation for the experimental environment.
(Go to stable docs)
First GPU Job
Submit your first GPU job on DAIC.
less than a minute
Before you begin
Complete First Job to understand batch job basics.
Submit a GPU job
1. Create a test script
gpu_test.py
import torch
print(f"CUDA available: {torch.cuda.is_available()}")
print(f"GPU count: {torch.cuda.device_count()}")
if torch.cuda.is_available():
print(f"GPU name: {torch.cuda.get_device_name(0)}")
2. Create the batch script
gpu_job.sh
#!/bin/bash
#SBATCH --account=<your-account>
#SBATCH --partition=all
#SBATCH --time=0:10:00
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=4
#SBATCH --mem=8G
#SBATCH --gres=gpu:1
#SBATCH --output=gpu_%j.out
module purge
module load 2025/gpu
module load py-torch/2.5.1
srun python gpu_test.py
3. Submit and check output
sbatch gpu_job.sh
> Submitted batch job 301
cat gpu_301.out
> CUDA available: True
> GPU count: 1
> GPU name: NVIDIA L40
Request specific GPU types
To request a specific GPU type:
#SBATCH --gres=gpu:l40:1 # NVIDIA L40
#SBATCH --gres=gpu:a40:1 # NVIDIA A40
Next steps
- Use Containers for custom GPU environments
- Learn about Modules for software management