Tue, Mar 19, 2024

4:30 PM – 6 PM EDT (GMT-4)

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Note: This workshop is scheduled to be held in-person but it may be moved to virtual via Zoom.

This workshop will introduce participants to high-performance Python on GPUs using tools to provide simplified GPU programming, as well as offer a brief look into creating custom kernels by hand. The main software libraries include CuPy and Numba.

Workshop format: Presentation with hands-on exercises.

Target audience: Those with Python experience looking to improve the performance of their code using GPUs.

Knowledge prerequisites: Some experience with Python is required.

Hardware/software prerequisites: For this workshop, users must have an account on our Adroit cluster, and they should confirm that they can SSH into Adroit at least a few hours beforehand. Details on all of the above can be found in this guide: https://bit.ly/3QER9Sv

Learning objectives: Participants will come away with the ability to accelerate their Python code using GPUs.


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Henry Schreiner

Princeton University

Henry Schreiner is a Computational Physicist / Research Software Engineer in High Energy Physics. He received his Ph.D. in experimental high-energy physics from the University of Texas at Austin. Henry is working on a three year project to develop simpler compiled packages for Python using Scikit-build. He is also an admin of Scikit-HEP, and also the lead web developer for IRIS-HEP and Scikit-HEP. Henry is also a maintainer/core developer for pypa/build, scikit-build, cibuildwheel, pybind11, and Plumbum for Python, and primary author of CLI11 for C++. He is also the author of a variety of CMake, GPU, and Python training courses and classes. He is also currently co-teaching APC 524.

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