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arXiv · 2210.10173

Faster Matrix Multiplication via Asymmetric Hashing

Ran Duan·Hongxun Wu·Renfei Zhou
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Abstract

Fast matrix multiplication is one of the most fundamental problems in algorithm research. The exponent of the optimal time complexity of matrix multiplication is usually denoted by $\omega$. This paper discusses new ideas for improving the laser method for fast matrix multiplication. We observe that the analysis of higher powers of the Coppersmith-Winograd tensor [Coppersmith & Winograd 1990] incurs a "combination loss", and we partially compensate for it using an asymmetric version of CW's hashing method. By analyzing the eighth power of the CW tensor, we give a new bound of $\omega<2.371866$, which improves the previous best bound of $\omega<2.372860$ [Alman & Vassilevska Williams 2020]. Our result breaks the lower bound of $2.3725$ in [Ambainis, Filmus & Le Gall 2015] because of the new method for analyzing component (constituent) tensors.

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Ran Duan, Hongxun Wu, Renfei Zhou. 2022-10-18. Faster Matrix Multiplication via Asymmetric Hashing. https://arxiv.org/abs/2210.10173

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