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Computer Science > Data Structures and Algorithms

Title: More Asymmetry Yields Faster Matrix Multiplication

Abstract: We present a new improvement on the laser method for designing fast matrix multiplication algorithms. The new method further develops the recent advances by [Duan, Wu, Zhou FOCS 2023] and [Vassilevska Williams, Xu, Xu, Zhou SODA 2024]. Surprisingly the new improvement is achieved by incorporating more asymmetry in the analysis, circumventing a fundamental tool of prior work that requires two of the three dimensions to be treated identically. The method yields a new bound on the square matrix multiplication exponent $$\omega<2.371339,$$ improved from the previous bound of $\omega<2.371552$. We also improve the bounds of the exponents for multiplying rectangular matrices of various shapes.
Comments: 44 pages. arXiv admin note: text overlap with arXiv:2307.07970
Subjects: Data Structures and Algorithms (cs.DS); Computational Complexity (cs.CC)
Cite as: arXiv:2404.16349 [cs.DS]
  (or arXiv:2404.16349v1 [cs.DS] for this version)

Submission history

From: Renfei Zhou [view email]
[v1] Thu, 25 Apr 2024 05:59:44 GMT (46kb)

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