Stability Improvements for Fast Matrix Multiplication
Numerical Analysis
2023-10-05 v1 Numerical Analysis
Abstract
We implement an Augmented Lagrangian method to minimize a constrained least-squares cost function designed to find polyadic decompositions of the matrix multiplication tensor. We use this method to obtain new discrete decompositions and parameter families of decompositions. Using these parametrizations, faster and more stable matrix multiplication algorithms can be discovered.
Cite
@article{arxiv.2310.02794,
title = {Stability Improvements for Fast Matrix Multiplication},
author = {Charlotte Vermeylen and Marc Van Barel},
journal= {arXiv preprint arXiv:2310.02794},
year = {2023}
}