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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- parallel genetic algorithm
- matrix multiplication algo-rithms
- theoretical lower bound
Joó, A. M., Ekárt, A., & Neirotti, J. P. (2012). Genetic algorithms for discovery of matrix multiplication methods. IEEE Transactions on Evolutionary Computation, 16(5), 749-751. . https://doi.org/10.1109/TEVC.2011.2159270