Using containers on AI-LAB

Let's run a simple Python script inside a Singularity container with GPU support.

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🚀 Example: Running a container with srun

srun singularity exec --nv /ceph/container/pytorch/pytorch_25.04.sif python3 gpu_stress.py

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📝 Example: Running a container with sbatch

In a batch script, add resource requests using #SBATCH directives:

run.sh

#!/bin/bash

singularity exec --nv /ceph/container/pytorch/pytorch_25.04.sif python3 gpu_stress.py

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📖 Understanding the Singularity command

Let's break down what each part does:

• singularity exec: Tells Singularity to execute something inside the container.
• --nv: Tells Singularity to include NVIDIA libraries. Always use this flag when running GPU-accelerated code so your container can access the GPU.
• /ceph/container/pytorch/pytorch_25.04.sif: The path to your container file. This is a pre-downloaded PyTorch container stored on AI-LAB.
• python3 gpu_stress.py: The command to run inside the container. This executes your Python script using Python 3 from within the container environment.

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Next: Exercise 3 →