GPU Hackathons provide exciting opportunities for scientists to accelerate their AI research or HPC codes under the guidance of expert mentors from National Labs, Universities and Industry leaders in a collaborative environment.
The Princeton GPU Hackathon is a multi-day event designed to help teams of three to six developers accelerate their own codes on GPUs using a programming model, or machine learning framework of their choice. Each team is assigned mentors for the duration of the event.
- Teams are expected to be fluent with the code or project they bring to the event and motivated to make progress during the hackathon.
- No advanced GPU skills required, but teams are expected to know the basics of GPU programming and profiling at the event. A collection of GPU lectures, tutorials, and labs are available for all participants at no fee. Please contact organizers for more information to help you prepare for the hackathon.
GPU Compute Resource
Teams attending the event will be given access to a GPU cluster for the duration of the hackathon. If participants prefer they can use their own GPU resource at the event.
The Princeton GPU Hackathon will be hosted online with all times Eastern Daylight Time (EDT). Each team will be assigned to a virtual breakout room to work with mentors on their codes and will present reports (SCRUMS) on their progress to all participants in the main virtual meeting space daily.
Attending the Hackathon
If your team is accepted for the hackathon, registration information will be provided along with mentor introductions and computational resource access. Accepted teams should:
- Register all team members for the event.
- Review the attendee guide.
To get a better idea of what the virtual GPU Hackathon will be like, check out this blog post on the first virtual hackathon in the series hosted by San Diego Supercomputer Center.
Important Event Dates
Princeton GPU Hackathon Application Deadline
Princeton GPU Hackathon Day 1
Princeton GPU Hackathon Day 2
Princeton GPU Hackathon Day 3
Princeton GPU Hackathon Day 4