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

Conference ·
OSTI ID:203476
; ;  [1];  [2]
  1. Sandia National Labs., Albuquerque, NM (United States)
  2. California Univ., San Diego, La Jolla, CA (United States). Dept. of Computer Science and Engineering

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.

Research Organization:
Sandia National Labs., Albuquerque, NM (United States)
Sponsoring Organization:
USDOE, Washington, DC (United States); Department of Defense, Washington, DC (United States)
DOE Contract Number:
AC04-94AL85000
OSTI ID:
203476
Report Number(s):
SAND--96-0339C; CONF-960450--2; ON: DE96006045
Country of Publication:
United States
Language:
English

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