Genetic Algorithms for Discovery of Matrix Multiplication Methods

Genetic Algorithms for Discovery of Matrix Multiplication Methods

We present a parallel genetic algorithm for finding matrix multiplication algorithms. For 3 3 matrices our genetic algorithm successfully discovered algorithms requiring 23 multiplications, which are equivalent to the currently best known human-developed algorithms. We also studied cases with fewer...

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Veröffentlicht in:IEEE transactions on evolutionary computation 2012-10, Vol.16 (5), p.749-751
Hauptverfasser: Joo, A., Ekart, A., Neirotti, J. P.
Format: Artikel
Sprache:eng
Schlagworte:
Algorithmics. Computability. Computer arithmetics
Algorithms
Applied sciences
Approximation
Approximation methods
Argon
Computer science
control theory
systems
Equivalence
Exact sciences and technology
Genetic algorithms
Mathematical analysis
Mathematical models
Matrices
Multiplication
Theoretical computing
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Beschreibung
Zusammenfassung:We present a parallel genetic algorithm for finding matrix multiplication algorithms. For 3 3 matrices our genetic algorithm successfully discovered algorithms requiring 23 multiplications, which are equivalent to the currently best known human-developed algorithms. We also studied cases with fewer multiplications and found an approximate solution for 22 multiplications.
ISSN:1089-778X
1941-0026
DOI:10.1109/TEVC.2011.2159270