Tue, Jul 9, 2024

2:30 PM – 4 PM EDT (GMT-4)

Add to Calendar

Private Location (sign in to display)

View Map


Options Sales Start Sales End Availability Price
Option RSVP

Sales Start - Sales End - Availability 18
Spots Left
Price FREE
Note: There is a limit at 1 ticket per person for this event.

This event is open to specific members only. You need to Sign In


What is a GPU? How can it be used for scientific computing? What GPU resources does Princeton provide? This workshop will answer these questions and give participants the opportunity to run sample code written in Python, R, Julia and MATLAB on the GPU nodes of one of the Research Computing clusters. Participants will also gain hands-on experience with getting started with CUDA, a low-level GPU programming model and platform. This workshop presumes no previous knowledge of GPU computing.

Learning objectives: Attendees will learn about GPU hardware and come away with the ability to run GPU codes.

Knowledge prerequisites: Basic Linux is required; knowledge of a compiled programming language (e.g., C/C++, Fortran, Java) would be beneficial.

Hardware/software prerequisites: You will need a laptop and an account on the Adroit cluster (https://researchcomputing.princeton.edu/adroit).

Workshop format: Lecture and hands-on


Jonathan Halverson's profile photo

Jonathan Halverson

Research Software and Computing Training Lead

Princeton University

Jonathan Halverson is the Research Software and Computing Training Lead with PICSciE and Research Computing. He has an expertise in data science and he is a founding organizer of the TensorFlow & PyTorch User Group at Princeton. Prior to his current position, Jonathan performed polymer physics research at the Max Planck Institute for Polymer Research and nanoscience research at Brookhaven National Laboratory. He holds a Ph.D. in Chemical Engineering from CUNY.

Hosted By

PICSciE/Research Computing | View More Events
Co-hosted with: GradFUTURES

Contact the organizers