Accelerating Sparse Algebra with Program Synthesis

ACM SIGPLAN International Conference on Compiler Construction (CC) 2026

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Authors: José Wesley de Souza Magalhães, Shideh Hashemian, Alexander Brauckmann, Jackson Woodruff, Elizabeth Polgreen, Michael F. P. O’boyle
DOI: 10.1145/3771775.3786281
Cited by: 0
References: 23

Abstract

Linear algebra libraries and tensor domain-specific languages are able to deliver high performance for modern scientific and machine learning workloads. While there has been recent work in automatically translating legacy software to use these libraries/DSLs using pattern matching and program lifting, this has been largely limited to dense linear algebra.

Fields of Study & Subjects

Parallel Computing and Optimization Techniques Embedded Systems Design Techniques Logic programming and type systems

Publication details

Journal / source
ACM SIGPLAN International Conference on Compiler Construction (CC)
Pages
106–118
Publication date
28 January 2026