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Intro to CuPy and Numba

Instructor bio


This session will introduce CuPy and Numba as mechanisms to leverage GPUs using Python. Participants will see pragmatic hands-on examples of how the CuPy library and Numba package can be used to accelerate Python code with a low barrier to entry.

Learning objectives

Participants will leave with exposure to different use-cases for CuPy and Numba.

Knowledge prerequisites

No previous experience with GPU programming in general is required. However, programming experience with 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 may also need 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

See the GitHub repo