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Effortless Hardware Acceleration and More with JAX

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Training/Workshop Programming Languages Research & Data Analysis Undergraduate Research

Fri, Mar 6, 2026

3 PM – 4:30 PM EST (GMT-5)

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Details

JAX is a Python library for high-performance array computing. Combining support a NumPy-like API with minimal-friction hardware acceleration and automatic differentiation, it is an increasingly important tool in the scientific and AI computing ecosystem. In this workshop, I will introduce the core concepts underpinning JAX, highlighting key similarities and differences from working with NumPy, and introduce some common tools in the wider JAX ecosystem.

Knowledge prerequisites: Some knowledge of NumPy would be beneficial

Hardware/software prerequisites: Google Colab will be used so only a laptop and web browser are needed

Workshop format: Demonstration and hands-on

Target audience: Students, researchers, faculty, staff

Speakers

Colm Talbot's profile photo

Colm Talbot

Colm is a Senior Research Software and Programming Analyst with Research Computing and Physics.

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