JuliaCon 2025

Katharine Hyatt

I am a Julia contributor since 2015. I work mostly on GPUs, quantum packages, and linear algebra.


Sessions

07-24
14:30
30min
Quasar.jl: a pure Julia parser for OpenQASM 3
Katharine Hyatt

A significant pain point for the wider Julia Quantum ecosystem has been the lack of a Julia parser for OpenQASM 3 (OQ3). OQ3 is a widely used domain-specific language for specifying quantum programs. Quasar.jl is a new Julia package built on top of Automa.jl which allows generation of an AST from OQ3 and output of easily translatable instructions which can be run on real quantum devices or simulators. In this talk I will introduce the package and provide several usage examples.

Quantum Minisymposium
Main Room 6
07-25
10:50
10min
Things that annoyed me about multithreading in 2024
Katharine Hyatt

In this lightning talk I will step through some of the annoyances and papercuts I encountered while writing multithreaded Julia code for my scientific applications. I will present a feature wishlist for Julia multithreading capabilities going forward and identify some tools I used to address performance problems I ran into.

Multithreading in Julia
Main Room 3
07-25
14:30
30min
What's new and improved in CUDA.jl?
Katharine Hyatt

In this talk we'll summarize and demonstrate some of the improvements made to the CUDA.jl package over the past year; including new features in the compiler, memory management, and device programming stack; as well as updates about the support for various CUDA libraries. Practical examples will be provided to show the benefits of this work for both end users and developers of packages which rely on CUDA.jl.

JuliaGPU minisymposium
Main Room 5
07-25
15:30
30min
Lead, follow, or get out of the way: Julia and threaded Python
Katharine Hyatt

PythonCall.jl and juliacall have recently added support for using multithreaded Julia code from Python, or calling Python code from Julia threads. However, there are still quite a few gotchas. In this talk I will discuss some pitfalls encountered when developing a Python wrapper for a multithreaded Julia package and demonstrate workarounds and some suggestions for other package developers encountering similar issues.

General
Main Room 6