Course Resources

Lecture Notes
1. Changelog
GitHub Classroom
Assignments
Computing Resources
Videos
Lecture Slides & Recordings Archive (2023)

2025 Video Series (New)

I have refreshed this course to run, starting from January 2025. All materials will be kept online for reference at any later point.

The lecture content has been updated and split across several smaller videos. These are available on YouTube, with the playlist below:

YouTube Playlist

Unfortunately, these videos have an unreasonable amount of ads, so I would encourage viewers to use an AdBlocker, like UBlock Origin (Firefox) to improve your experience.

Lecture Notes

The original lecture notes from 2023 are available here. The new course notes will be posted online on my personal website: jamiemair.co.uk/courses/hpc. Entries posted weekly to accompany the video material. Links to the book are kept here for reference.

Changelog

Current Version: v1.2 (23/01/2023)

Updated to v1.1: Improved Chapters 5 and 6: Measuring Performance and Optimisation.
Updated to v1.2

GitHub Classroom

The assessment and submission will be done via GitHub Classroom, which allows for automated marking and feedback. The assignment for each week will be emailed to everyone enrolled in the class. You will need a GitHub account (it's free!) to sign up.

Git/GitHub Refresher

For this course, you do not need to be an expert with Git, but its use is encouraged. The video below gives an overview of Git for researchers, but any Git video/tutorial should be enough. Basic usage needed for the course will be covered during the first workshop.

Assignments

Week 1 - Getting Started with Julia: Workflow and Setup - Announced
Week 2 - Profiling and Optimisation - TBA
Week 3 - Multithreading - TBA
Week 4 - Multiprocessing - TBA
Week 5 - GPU Programming - TBA

The deadline for all assessments for the 2025 course is the 1st April 2025. This deadline only applies to those enrolled on the MPAGS course.

More information about the assignments is in this video.

If you need help getting set up with the assignments, watch this video.

Computing Resources

During this course, you should be able to do everything on your own personal machine. I would advise trying to run some code on your local cluster as well if you have access. You will benefit from being able to access a GPU, but it is not a requirement for this course. Being able to test and run your GPU code locally will make it easier to complete the final assessment, but it can be done without one. If you have access to your local institution's HPC already, but do not have GPU access, you can ask your local admin to give you a small number of GPU hours (around 20 should be more than enough).

Another option is to use Google Colab which has free access to GPU resources for testing. There is also a cheap paid option for better access. The notebook linked here has instructions for how to setup Julia and CUDA, however this notebook may not work for everyone.

If you are from UoN and are struggling to access GPUs, contact myself to see if we can arrange temporary access to our in-house Physics cluster. Access to this cluster cannot be guaranteed, and we advise students to use this as a last resort.

Videos

No videos for 2025 have been posted yet. Sign up to the mailing list to recieve updates, or check back later to find new videos.

Lecture Slides & Recordings Archive (2023)

Below is an archive of the original lecture videos and accompanying slides. The new videos in 2025 will largely follow the same content, with a few sections expanded upon and others removed. In particular, these recordings do not include the in-person workshops that were ran in 2025.