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GP-ENGINE NRP and K8s Tutorial Logistics University of Missouri Data Science and Analytics
Overview
This workshop will give researchers a hands-on introduction to leveraging the large distributed computing resources available through the National Research Platform (NRP). Researchers will learn how to migrate an AI/ML workflow from their local computer or Hellbender to the NRP. By accessing Nautilus, you can gain access to a vast array of cutting-edge GPUs, ideal for facilitating AI research and accelerating your research.
When: May 1st, 2026, 9:00 am to 12:00 pm
Where: Room-22M Heinkel Building, 201 S. 7th St., Columbia, MO 65201
Learning Objectives:
- Kubernetes Architecture and Concepts
- Hands-on with Nautilus HyperCluster
- Deploying Pods and Jobs in Kubernetes using Nautilus
- Deploying Scikit Learn ML Jobs to Kubernetes
- Deploying GPU Jobs to Kubernetes for Training Computer Vision Models
- Scaling Computer Vision Models on Kubernetes with Job Automation
Pre-Workshop: Registration & Setting up your Identity
In order for you to be added to the training group's namespace, your NRP identity MUST match what the NRP sees. You must also sign into NRP to have your email as a valid account with NRP. You do not need to create an additional account as authentication is handled with your university pawprint. If you do not sign-in, your university email will not be registered with the NRP and may prevent participation in the training.
Please complete the registration form: Required Registration Here!
On the above form, you'll be guided in the registration form to follow these steps.
- Navigate to: https://nrp.ai/
- Sign into NRP using your campus credentials: https://nrp.ai/
- You will be redirected to the CILogon page where you have to select an Identity Provider
- Select University of Missouri System in the dropdown.
- If University of Missouri System is not available, you can use Google or Microsoft.
- When you are signed in, you should see your email at the top right of your screen.
Day of the Workshop
Check-in and complete form
Check-in to the workshop here: Required Workshop Check-in Here!
Go to https://nrp.ai/namespaces/ . Is gp-engine-tutorial-jobs visible? If you do not see the gp-engine-tutorial-jobs, put up your red sticky note. You will need to be able to see this namespace to follow along in the hands-on activities.
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 unclear on a topic at any point in the workshop, please let us know and we would be happy to help. Participation can be accomplished by using sticky notes or raising hands.
How to Request Help
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 visible 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
Links and Steps
Open these at the start:
When we move to the hands-on activities:
- Sign into the GP-ENGINE JupyterHub Portal: https://gp-engine.nrp-nautilus.io/
- Select
Stack Datascience + K8sand clickStart. This process will take a few minutes. - Put up your green checkmark when you see it is complete.
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
