Location of Repository

Fax: (217) 244-5705Scaling eCGA Model Building via Data-Intensive Computing

By Abhishek Verma, Xavier Llorà, Shivaram Venkataraman, David E. Goldberg and Roy H. CampbellAbhishek Verma, Xavier Llorà, Shivaram Venkataraman, David E. Goldberg and Roy H. Campbell

Abstract

This paper shows how the extended compact genetic algorithm can be scaled using dataintensive computing techniques such as MapReduce. Two different frameworks (Hadoop and MongoDB) are used to deploy MapReduce implementations of the compact and extended compact genetic algorithms. Results show that both are good choices to deal with large-scale problems as they can scale with the number of commodity machines, as opposed to previous efforts with other techniques that either required specialized high-performance hardware or shared memory environments.

Year: 2010
OAI identifier: oai:CiteSeerX.psu:10.1.1.192.6882
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://www.illigal.uiuc.edu/pu... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.