Parallel Programs are More Evolvable than Sequential Programs
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{leung03,
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author = "Kwong Sak Leung and Kin Hong Lee and Sin Man Cheang",
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title = "Parallel Programs are More Evolvable than Sequential
Programs",
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booktitle = "Genetic Programming, Proceedings of EuroGP'2003",
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year = "2003",
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editor = "Conor Ryan and Terence Soule and Maarten Keijzer and
Edward Tsang and Riccardo Poli and Ernesto Costa",
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volume = "2610",
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series = "LNCS",
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pages = "107--118",
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address = "Essex",
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publisher_address = "Berlin",
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month = "14-16 " # apr,
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organisation = "EvoNet",
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publisher = "Springer-Verlag",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "3-540-00971-X",
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DOI = "doi:10.1007/3-540-36599-0_10",
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abstract = "This paper presents a novel phenomenon of the Genetic
Parallel Programming (GPP) paradigm - the GPP
accelerating phenomenon. GPP is a novel Linear Genetic
Programming representation for evolving parallel
programs running on a Multi-ALU Processor (MAP). We
carried out a series of experiments on GPP with
different number of ALUs. We observed that parallel
programs are more evolvable than sequential programs.
For example, in the Fibonacci sequence regression
experiment, evolving a 1-ALU sequential program
requires 51 times on average of the computational
effort of an 8-ALU parallel program. This paper
presents three benchmark problems to show that the GPP
can accelerate evolution of parallel programs. Due to
the accelerating evolution phenomenon of GPP over
sequential program evolution, we could increase the
normal GP's evolution efficiency by evolving a parallel
program by GPP and if there is a need, the evolved
parallel program can be translated into a sequential
program so that it can run on conventional hardware.",
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notes = "EuroGP'2003 held in conjunction with EvoWorkshops
2003",
- }
Genetic Programming entries for
Kwong-Sak Leung
Kin-Hong Lee
Ivan Sin Man Cheang
Citations