Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11861/7649
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Prof. LEUNG Kwong Sak | en_US |
dc.contributor.author | Lee, Kin Hong | en_US |
dc.contributor.author | Cheang, Sin Man | en_US |
dc.date.accessioned | 2023-03-29T04:59:36Z | - |
dc.date.available | 2023-03-29T04:59:36Z | - |
dc.date.issued | 2002 | - |
dc.identifier.citation | Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002, 2002, vol. 2, pp. 1703 - 1708, Article number 1004499 | en_US |
dc.identifier.isbn | 0780372824 | - |
dc.identifier.isbn | 978-078037282-5 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11861/7649 | - |
dc.description.abstract | This paper proposes a novel genetic parallel programming (GPP) paradigm for evolving optimal parallel programs running on a multi-ALU processor by linear genetic programming. GPP uses a two-phase evolution approach. It evolves completely correct solution programs in the first phase. Then it optimizes execution speeds of solution programs in the second phase. Besides, GPP also employs a new genetic operation that swaps sub-instructions of a solution program. Three experiments (Sextic, Fibonacci and Factorial) are given as examples to show that GPP could discover novel parallel programs that fully utilize the processor's parallelism. © 2002 IEEE. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE Computer Society | en_US |
dc.relation.ispartof | Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002 | en_US |
dc.title | Evolving parallel machine programs for a multi-ALU processor | en_US |
dc.type | Conference Proceedings | en_US |
dc.identifier.doi | 10.1109/CEC.2002.1004499 | - |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Department of Applied Data Science | - |
Appears in Collections: | Applied Data Science - Publication |
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