Run Anaconda/Jupyter Environment on SLURM 

In this tutorial, you will run an interactive Anaconda Jupyter notebook environment within on SLURM. Make sure you have opened a FastX terminal and are logged in to the fx1 node.

To run interactive jobs, we have use the srun command to log in to an interactive job node. You can see what nodes are available using sinfo:

To request a GPU, add the Slurm directive --partition=gpu parameter in srun.

srun --pty --mem=8gb --time=1:00:00 --cpus-per-task=1 --nodes=1 /bin/bash

• srun: Command to submit a job to the Slurm scheduler.

• --pty: Allocate a pseudo-terminal for interactive job execution.

• --mem=8gb: Request 8 gigabytes of memory for the job.

• --time=1:00:00: Set a time limit of 1 hour for the job’s execution.

• --cpus-per-task=1: Request 1 CPU core per task.

• --nodes=1: Request 1 compute node for the job.

• /bin/bash: Execute the Bash shell as the job’s command.

You will see that you are logged in to one of the interactive nodes.

Check what modules are installed:

module av 

# OR

# module avail

To load the Anaconda environment, type in the following command:

module load anaconda3/py3.9

Now run the following command to load the Jupyter Notebook:

jupyter-notebook

You will see a Jupyter notebook open up in Chromium Browser.

Navigate to your Jupyter notebook or create a new one using the “New” button and then clicking on “Python 3 (ipykernel). 

Once inside the Jupyter notebook, type Python code in the cells and click the “Run” button to execute the code.