JuliaCon 2025

Willow Marie Ahrens

I am a postdoc at MIT advised by Saman Amarasinghe, and an incoming professor at Georgia Tech! I am inspired to make programming high-performance computers more productive, efficient, and accessible. My research primarily focuses on using compilers to adapt programs to the structure of data, bridging the gap between program flexibility and data structure flexibility. I’m the author of the Finch array programming language, which supports a wide variety of programming constructs on sparse, run-length-encoded, banded, or otherwise structured arrays.

willowahrens.io


Sessions

07-24
13:45
30min
Finch.jl: Flexible and Efficient Sparse Tensor Programming!
Willow Marie Ahrens

Finch is a Julia-to-Julia compiler which adapts array programs to the sparsity and structure of data automatically. Finch understands array structure through a language of basic loop building blocks called Looplets. This enables new loop optimizations across multiple domains, unifying techniques such as sparse tensors, geometric programming, databases, and lossless compression.

Sparse & Graph Computing in Julia
Main Room 3
07-24
14:55
15min
Binsparse: A Specification for Cross-Platform Storage of Sparse
Willow Marie Ahrens

Sparse matrices and tensors are ubiquitous throughout multiple subfields of computing. The widespread usage of sparse data has inspired a multitude of in-memory and on-disk storage formats, but the only widely adopted storage specifications are the Matrix Market and FROSTT file formats, which are both ASCII text-based.

Sparse & Graph Computing in Julia
Main Room 3
07-24
15:35
25min
Panel: What's next for SparseArrays.jl
Willow Marie Ahrens

Panel: What's next for SparseArrays.jl

Sparse & Graph Computing in Julia
Main Room 3