Accelerating GPU betweenness centrality

Abstract

Graphs that model social networks, numerical simulations, and the structure of the Internet are enormous and cannot be manually inspected. A popular metric used to analyze these networks is Betweenness Centrality (BC), which has applications in community detection, power grid contingency analysis, and the study of the human brain. However, these analyses come with a high computational cost that prevents the examination of large graphs of interest.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 23, 2018
Source ID
10.1145/3230485

Entities

People

  • Adam Mclaughlin
  • David A. Bader

Organizations

  • Defense Advanced Research Projects Agency
  • Georgia Tech
  • National Science Foundation

Tags

Readers

  • Computational Fluid Dynamics (CFD)
  • Neural Network Machine Learning.
  • Systems Analysis and Design