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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.
Published in:
Evolutionary Computation, IEEE Transactions on
(Volume:16
,
Issue:
5
)
Date of Publication: Oct. 2012
- Page(s):
- 749 - 751
- ISSN :
- 1089-778X
- INSPEC Accession Number:
- 13014920
- Digital Object Identifier :
- 10.1109/TEVC.2011.2159270
- Product Type:
- Journals & Magazines
- Date of Publication :
- 10 February 2012
- Date of Current Version :
- 27 September 2012
- Issue Date :
- Oct. 2012
- Sponsored by :
- IEEE Computational Intelligence Society
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