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A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm

Publication ,  Journal Article
Bazterra, VE; Cuma, M; Ferraro, MB; Facelli, JC
Published in: Journal of Parallel and Distributed Computing
January 1, 2005

This paper presents a general model to define, measure and predict the efficiency of applications running on heterogeneous parallel computer systems. Using this framework, it is possible to understand the influence that the heterogeneity of the hardware has on the efficiency of an algorithm. This methodology is used to compare an existing parallel genetic algorithm with a new adaptive parallel model. All the performance measurements were taken in a loosely coupled cluster of processors. © 2004 Elsevier Inc. All rights reserved.

Duke Scholars

Published In

Journal of Parallel and Distributed Computing

DOI

ISSN

0743-7315

Publication Date

January 1, 2005

Volume

65

Issue

1

Start / End Page

48 / 57

Related Subject Headings

  • Distributed Computing
  • 4606 Distributed computing and systems software
  • 0805 Distributed Computing
  • 0803 Computer Software
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Bazterra, V. E., Cuma, M., Ferraro, M. B., & Facelli, J. C. (2005). A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm. Journal of Parallel and Distributed Computing, 65(1), 48–57. https://doi.org/10.1016/j.jpdc.2004.09.011
Bazterra, V. E., M. Cuma, M. B. Ferraro, and J. C. Facelli. “A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm.” Journal of Parallel and Distributed Computing 65, no. 1 (January 1, 2005): 48–57. https://doi.org/10.1016/j.jpdc.2004.09.011.
Bazterra VE, Cuma M, Ferraro MB, Facelli JC. A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm. Journal of Parallel and Distributed Computing. 2005 Jan 1;65(1):48–57.
Bazterra, V. E., et al. “A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm.” Journal of Parallel and Distributed Computing, vol. 65, no. 1, Jan. 2005, pp. 48–57. Scopus, doi:10.1016/j.jpdc.2004.09.011.
Bazterra VE, Cuma M, Ferraro MB, Facelli JC. A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm. Journal of Parallel and Distributed Computing. 2005 Jan 1;65(1):48–57.
Journal cover image

Published In

Journal of Parallel and Distributed Computing

DOI

ISSN

0743-7315

Publication Date

January 1, 2005

Volume

65

Issue

1

Start / End Page

48 / 57

Related Subject Headings

  • Distributed Computing
  • 4606 Distributed computing and systems software
  • 0805 Distributed Computing
  • 0803 Computer Software