A scalable computational approach to political redistricting optimization

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present the experience of developing a scalable computational approach to political redistricting optimization by enhancing a parallel genetic algorithm library on XSEDE and Blue Waters.

Original languageEnglish (US)
Title of host publicationProceedings of the XSEDE 2015 Conference
Subtitle of host publicationScientific Advancements Enabled by Enhanced Cyberinfrastructure
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450337205
DOIs
StatePublished - Jul 26 2015
Event4th Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2015 - St. Louis, United States
Duration: Jul 26 2015Jul 30 2015

Publication series

NameACM International Conference Proceeding Series
Volume2015-July

Other

Other4th Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2015
CountryUnited States
CitySt. Louis
Period7/26/157/30/15

Keywords

  • Genetic algorithm
  • Message passing
  • Parallel computing

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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  • Cite this

    Liu, Y. Y., Cho, W. K. T., & Wang, S. (2015). A scalable computational approach to political redistricting optimization. In Proceedings of the XSEDE 2015 Conference: Scientific Advancements Enabled by Enhanced Cyberinfrastructure [a6] (ACM International Conference Proceeding Series; Vol. 2015-July). Association for Computing Machinery. https://doi.org/10.1145/2792745.2792751