Genetic algorithms for discovery of matrix multiplication methods


We present a parallel genetic algorithm for nding matrix multiplication algo-rithms. For 3 x 3 matrices our genetic algorithm successfully discovered algo-rithms requiring 23 multiplications, which are equivalent to the currently best known human-developed algorithms. We also studied the cases with less mul-tiplications and evaluated the suitability of the methods discovered. Although our evolutionary method did not reach the theoretical lower bound it led to an approximate solution for 22 multiplications.

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Divisions: ?? 50811700Jl ??
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
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Uncontrolled Keywords: parallel genetic algorithm,matrix multiplication algo-rithms,theoretical lower bound,Software,Computational Theory and Mathematics,Theoretical Computer Science
Publication ISSN: 1089-778X
Last Modified: 06 Jun 2024 07:08
Date Deposited: 25 Jun 2013 14:12
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
http://ieeexplo ... rnumber=6151102 (Publisher URL)
PURE Output Type: Article
Published Date: 2012-10
Published Online Date: 2012-02-10
Authors: Joó, A.M.
Ekárt, Aniko (ORCID Profile 0000-0001-6967-5397)
Neirotti, Juan P. (ORCID Profile 0000-0002-2409-8917)



Version: Accepted Version

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