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GPU Libraries

Instructor bio


This session will give participants a tour of GPU-ready numerical libraries and demonstrate how to utilize them from their own codes.

Learning objectives

Participants will leave with a thorough overview of available libraries, how to call them in your own code, which parallel programming models they support, and caveats about compatibility with different GPU hardware.

Knowledge prerequisites

No previous experience with GPU programming in general is required. However, programming experience with C, C++, or Python is expected. Prior exposure to parallel programming methodologies, though not strictly required, is also helpful.

Hardware/software prerequisites

Participants in any PICSciE virtual workshop need a Princeton Zoom account. For this session, users should also have an account on the Adroit cluster, and they should confirm that they can SSH into Adroit at least 48 hours beforehand. Details on all of the above can be found in the advance setup guide for PICSciE virtual workshops.

Session format

Lecture, demonstration, and hands-on exercises

Session Materials

Session Recording

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