8 citations · 11 across the 8 of their papers we have counts for
5 papers · 1 filter
Galley: Modern Query Optimization for Sparse Tensor Programs
Kyle Deeds, Willow Ahrens, Magda Balazinska +1
The tensor programming abstraction is a foundational paradigm which allows users to write high performance programs via a high-level imperative interface. Recent work on sparse ten…
The Continuous Tensor Abstraction: Where Indices are Real
Jaeyeon Won, Willow Ahrens, Teodoro Fields Collin +3
This paper introduces the continuous tensor abstraction, allowing indices to take real-number values (for example, A[3.14]). It also presents continuous tensor algebra expressions,…
SySTeC: A Symmetric Sparse Tensor Compiler
Radha Patel, Willow Ahrens, Saman Amarasinghe
Symmetric and sparse tensors arise naturally in many domains including linear algebra, statistics, physics, chemistry, and graph theory. Symmetric tensors are equal to their transp…
Mechanised Hypersafety Proofs about Structured Data: Extended Version
Vladimir Gladshtein, Qiyuan Zhao, Willow Ahrens +2
Arrays are a fundamental abstraction to represent collections of data. It is often possible to exploit structural properties of the data stored in an array (e.g., repetition or spa…
Finch: Sparse and Structured Tensor Programming with Control Flow
Willow Ahrens, Teodoro Fields Collin, Theadora Fields Collin +4
From FORTRAN to NumPy, tensors have revolutionized how we express computation. However, tensors in these, and almost all prominent systems, can only handle dense rectilinear intege…