Assignment: HiPerGator New User Training

Due: Friday, January 23, 2026 at 8:30 AM (before class) Points: 5 (part of Infrastructure Assignments - 5% of course grade) Submission: Canvas

Overview

The University of Florida’s HiPerGator supercomputer is a key resource for this course. You will use HiPerGator to run computationally intensive tasks, train models, and work with large datasets. Matt Gitzendanner from UF Research Computing will give a talk to our class on Friday, January 23 at 8:30 AM about using HiPerGator effectively.

You must complete the HiPerGator New User Training before Matt’s talk.

Task

Complete the HiPerGator User Training online course provided by UF’s Office of Professional and Workforce Development.

Course Link: HiPerGator User Training (Course #777876)

What You’ll Learn

Introduction to Research Computing and HiPerGator
Accessing HiPerGator via command line and web interfaces (Jupyter)
Running jobs with the SLURM scheduler
Understanding storage locations and quotas
Using the environment module system
Common mistakes to avoid

Course Details

Format: Self-paced online course
Cost: Free (non-credit)
Time: Plan for 1-2 hours to complete

Submission

After completing the training, submit proof of completion to Canvas:

Screenshot of completion page showing your name and the completion status
Brief reflection (2-3 sentences): What is one thing you learned that you expect to use this semester?

Upload both items as a single PDF or two separate files to the Canvas assignment.

Grading

Criterion	Points
Proof of completion (screenshot with name visible)	4
Reflection on learning	1
Total	5

Late Policy

Due date: Friday, January 23, 2026 at 8:30 AM (before class)

You may submit after the due date until grading begins (typically 1-3 days after due date). The exact grading start time will not be announced. No submissions accepted after grading begins.

Note: The training must be completed before attending the guest lecture on January 23 to get the most value from Matt’s talk.

Why This Matters

HiPerGator provides computing resources far beyond what your laptop can offer:

32 CPU cores (shared allocation for our class)
GPU access for training models (by request)
2 TB storage for datasets and results

Many of your course projects will require these resources, especially for RAG systems, model fine-tuning, and large-scale data processing.

Questions?

HiPerGator issues: Contact UF Research Computing at help@rc.ufl.edu
Assignment questions: Post in Canvas discussion or email the instructor