Using Containers to Run Jobs

Now that you know how to get containers, let's learn how to use them to run your computational tasks on TAAURUS.

Basic Container Usage

To run commands inside a container, you use singularity exec with either srun or sbatch.

Running a Simple Command

Let's start with a basic example using a Python container:

srun --mem=24G --cpus-per-task=6 --gres=gpu:1 --time=01:00:00 singularity exec --nv /media/project/work/pytorch_25.05.sif python3 -c "print('Hello from TAAURUS!')"

Command breakdown:

• srun: Run on a compute node with specified resources
• singularity exec: Execute a command inside a container
• --nv: Enable NVIDIA GPU drivers (required for GPU jobs)
• /media/project/work/pytorch_25.05.sif: Path to the container (replace project with your projects name)
• python3 -c "print('Hello from TAAURUS!')": Command to run

Using Containers with sbatch

For longer jobs, create a batch script:

my_job.sh

#!/bin/bash

#SBATCH --job-name=my_python_job
#SBATCH --output=my_job.out
#SBATCH --error=my_job.err
#SBATCH --mem=24G
#SBATCH --cpus-per-task=15
#SBATCH --gres=gpu:1
#SBATCH --time=01:00:00

# Run Python script in container
singularity exec --nv /media/project/work/pytorch_25.05.sif python3 my_script.py

Submit the job:

sbatch my_job.sh

Check the results:

cat my_job.out  # View output
cat my_job.err  # View errors (if any)

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Cancelling Jobs

Sometimes you need to cancel jobs that are running too long, stuck, or have incorrect parameters.

Check Your Jobs First

Before cancelling, see what jobs you have running:

squeue --me

This shows all your jobs with their IDs and status.

Cancel a Specific Job

To cancel a single job, use its job ID:

scancel 12345  # Replace 12345 with your actual job ID

Cancel All Your Jobs

To cancel all your jobs at once:

scancel --user=$USER

Now that you know how to run jobs using containers, let's delve into the last part about monitoring on TAAURUS