Parallel Programs are More Evolvable than Sequential Programs

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{leung03,
  author =       "Kwong Sak Leung and Kin Hong Lee and Sin Man Cheang",
  title =        "Parallel Programs are More Evolvable than Sequential
                 Programs",
  booktitle =    "Genetic Programming, Proceedings of EuroGP'2003",
  year =         "2003",
  editor =       "Conor Ryan and Terence Soule and Maarten Keijzer and 
                 Edward Tsang and Riccardo Poli and Ernesto Costa",
  volume =       "2610",
  series =       "LNCS",
  pages =        "107--118",
  address =      "Essex",
  publisher_address = "Berlin",
  month =        "14-16 " # apr,
  organisation = "EvoNet",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-00971-X",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2610&spage=107",
  DOI =          "doi:10.1007/3-540-36599-0_10",
  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.",
  notes =        "EuroGP'2003 held in conjunction with EvoWorkshops
                 2003",
}

Genetic Programming entries for Kwong-Sak Leung Kin-Hong Lee Ivan Sin Man Cheang

Citations