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Introduction to GPU Computing
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Details
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 have participants run code written in Python, R, Julia or MATLAB on the GPU nodes of the Adroit Research Computing cluster. Participants will also gain hands-on experience with getting started with CUDA, a low-level GPU programming model.
Learning objectives: Attendees will learn about GPU hardware and come away with the ability to write and execute simple, compiled programs that use GPUs.
Knowledge prerequisites: Basic Linux and some exposure to a compiled programming language (e.g., C/C++, Fortran, Java).
Hardware/software prerequisites: This workshop will use reserved nodes on the Adroit cluster. If you need an account then please request one at least an hour before the workshop.
Workshop format: Presentation (40%) and hands-on (60%)
Is your research group looking to accelerate a code using GPUs? Consider applying to the 2025 Princeton Open Hackathon by March 12.
See the full PICSciE/RC spring training program or subscribe to the PICSciE/RC mailing list.
Speakers
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
Co-hosted with: GradFUTURES
Contact the organizers