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Husker AI Days - Intro to Machine Learning and AI on HCC - April 2026 Logistics

Setup

Please make sure to complete the setup steps below.

  1. Ensure your HCC Account is active.

  2. Sign into Swan's Open OnDemand Portal: https://swan-ood.unl.edu

  3. When you have signed into the Swan Open OnDemand Portal, please put up your Yellow Sticky Note or Green Checkmark.

If you have any issues logging in or accesing Swan, please visit our event troubleshooting guide here

Check In

Check into the workshop for today

Check in is required to make sure the setup is complete!

If you do not see the namespace in the steps listed below or are unable to sign into Swan Open OnDemand, please raise your hand and put up your red sticky note. You will need to be able to sign into Swan and see the namespace below to follow along in the hands-on activities!

Go to https://swan-ood.unl.edu and sign in with your HCC account.

  • If you were able to sign in and see the Message of the Day at the bottom, proceed to the step below.
  • If you are not able to sign in, please put up your red sticky note.

Sign into nrp.ai. Go to the NRP Namespaces page. Is gp-engine-tutorial-jobs visible?

  • If you are able to see the gp-engine-tutorial-jobs, then the setup is complete for the workshop today. Please put up your yellow sticky note.
  • If you are not able to see the gp-engine-tutorial-jobs, please put up your red sticky note. You may need to complete this form to be added to the namespace.

Sticky Notes and Reactions

Throughout the workshop, we will use sticky notes to indicate status. These help instructors and helpers in the workshop assist with various issues and provide formative feedback during the workshops.

Please make sure the sticky note is visibly on both the front and back of your laptop

  • Yellow Sticky Note: All good to go
  • Red Sticky Note: I need help or I am not ready to continue

Workshop Recommendations

To make the most of this workshop, we strongly encourage active participation throughout the entire session, including participating in the hands-on exercises and asking questions throughout the workshop.

If you are stuck or not sure on something at any point of the workshop, please let us know and we would be happy to help.

Participation can be accomplished by using the sticky notes or raising hands.

Workshop Website: https://hcc.unl.edu/husker-ai-days-introduction-artificial-intelligence-and-machine-learning-using-hcc

Feedback Form: https://forms.office.com/r/3iQZKPYdXc

Introduction to Bash

Command History Link: https://hcc.unl.edu/swc-history/20260420.html

Slides Link:

Download Materials

  1. Open a terminal in Open OnDemand (OOD). This is done by opening the "Clusters" menu at the top of the screen and selecting "Swan Shell Access"
  2. Change to your $WORK directory and run git clone https://github.com/unlhcc/hcc-ai-ml-workshop.git. Verify that the data was downloaded using the ls command.

Setup Jupyter

Return the the OOD main page and start a "Jupyter Lab" session from the "Interactive Apps" menu using the settings in the section below.

Open OnDemand Settings

Open OnDemand WebForm Settings

Parameter Value
Jupyter Lab version 4.0
Working Directory /work/groupname/username
Number of cores 8
Running time in hours 3
Requested RAM in GBs 32
Partition selection gpu
Reservation Located on the back of your name tag
GRES gpu
Job Constraints ---Leave BLANK---

Resource Reservation for GPUs: Located on back of nametags

JupyterLab Settings:

Parameter Value
INSIDE JUPYTER LAB: Kernel Name hcc-ai-ml-workshop
  1. Navigate to the "hcc-ai-ml-workshop" directory on the left hand side of the screen.
  2. Open the "prepare_datasets.ipynb" notebook and run all cells
  3. When all cells have finished execution without error, put up your YELLOW sticky note.

Git Lesson Link: https://swcarpentry.github.io/git-novice/

Open these at the start:

When we move to the hands-on activities

  1. Sign into the GP-ENGINE JupyterHub Portal: https://gp-engine.nrp-nautilus.io/
  2. Select Stack Datascience + K8s and click Start. This process will take a few minutes.
  3. Put up your yellow sticky note when you see it is complete.

??? tip "Want to learn how to setup your own instance for a class or lab?" Check out the "Deploying JupyterHub" documentation: NRP Jupyter Hub Docs

Cloning the repository:

git clone https://github.com/MUAMLL/gp-engine-tutorials.git

Troubleshooting

PyTorch is not loading correctly in Tensorboard

This can be caused by running an old version of Tensorboard. Cancel the existing tensorboard job and resubmit with the latest version.

sbatch: error: Batch job submission failed: Requested node configuration is not available

For this workshop, make sure you are using the gpu partition with the reservation and the normal QoS.