Analysis of the numerical effects of parallelism on a parallel genetic algorithm

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This paper examines the effects of relaxed synchronization on both the numerical and parallel efficiency of parallel genetic algorithms (GAs). We describe a coarse-grain geographically structured parallel genetic algorithm. Our experiments show that asynchronous versions of these algorithms have a lower run time than-synchronous GAs. Furthermore, we demonstrate that this improvement in performance is partly due to the fact that the numerical efficiency of the asynchronous genetic algorithm is better than the synchronous genetic algorithm. Our analysis includes a critique of the utility of traditional parallel performance measures for parallel GAs, and we evaluate the claims made by several researchers ... continued below

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25 p.

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Hart, W. E.; Belew, R. K.; Kohn, S. & Baden, S. September 18, 1995.

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This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 38 times . More information about this article can be viewed below.

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  • Hart, W. E.
  • Belew, R. K.
  • Kohn, S. Sandia National Labs., Albuquerque, NM (United States)
  • Baden, S. California Univ., San Diego, La Jolla, CA (United States). Dept. of Computer Science and Engineering

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  • Sandia National Laboratories
    Publisher Info: Sandia National Labs., Albuquerque, NM (United States)
    Place of Publication: Albuquerque, New Mexico

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Description

This paper examines the effects of relaxed synchronization on both the numerical and parallel efficiency of parallel genetic algorithms (GAs). We describe a coarse-grain geographically structured parallel genetic algorithm. Our experiments show that asynchronous versions of these algorithms have a lower run time than-synchronous GAs. Furthermore, we demonstrate that this improvement in performance is partly due to the fact that the numerical efficiency of the asynchronous genetic algorithm is better than the synchronous genetic algorithm. Our analysis includes a critique of the utility of traditional parallel performance measures for parallel GAs, and we evaluate the claims made by several researchers that parallel GAs can have superlinear speedup.

Physical Description

25 p.

Notes

INIS; OSTI as DE96006045

Source

  • 10. international parallel processing symposium, Honolulu, HI (United States), 15-19 Apr 1996

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  • Other: DE96006045
  • Report No.: SAND--96-0339C
  • Report No.: CONF-960450--2
  • Grant Number: AC04-94AL85000
  • Office of Scientific & Technical Information Report Number: 203476
  • Archival Resource Key: ark:/67531/metadc669662

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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Creation Date

  • September 18, 1995

Added to The UNT Digital Library

  • June 29, 2015, 9:42 p.m.

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  • June 22, 2016, 6:47 p.m.

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Hart, W. E.; Belew, R. K.; Kohn, S. & Baden, S. Analysis of the numerical effects of parallelism on a parallel genetic algorithm, article, September 18, 1995; Albuquerque, New Mexico. (digital.library.unt.edu/ark:/67531/metadc669662/: accessed November 17, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.