Copyright Notice:

The documents distributed by this server have been provided by the contributing authors as a means to ensure timely dissemination of scholarly and technical work on a noncommercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Publications of SPCL

N. Edmonds, T. Hoefler, A. Lumsdaine:

 A Space-Efficient Parallel Algorithm for Computing Betweenness Centrality in Distributed Memory

(. Vol , Nr. , In International Conference on High Performance Computing, presented in Goa, India, pages 1 - 10, , ISSN: , ISBN: 978-1-4244-8518-5 , Dec. 2010, )

Publisher Reference

Abstract

Betweenness centrality is a measure based on shortest paths that attempts to quantify the relative importance of nodes in a network. As computation of betweenness centrality becomes increasingly important in areas such as social network analysis, networks of interest are becoming too large to fit in the memory of a single processing unit, making parallel execution a necessity. Parallelization over the vertex set of the standard algorithm, with a final reduction of the centrality for each vertex, is straightforward but requires \Omega(|V|^2) storage. In this paper we present a new parallelizable algorithm with low spatial complexity that is based on the best known sequential algorithm. Our algorithm requires O(|V| + |E|) storage and enables efficient parallel execution. Our algorithm is especially well suited to distributed memory processing because it can be implemented using coarse-grained parallelism. The presented time bounds for parallel execution of our algorithm on CRCW PRAM and on distributed memory systems both show good asymptotic performance. Experimental results with a distributed memory computer show the practical applicability of our algorithm.

Documents

download article:
download slides:
 

BibTeX

@inproceedings{edmonds-hoefler-lumsdaine-bc,
  author={Nicholas Edmonds and Torsten Hoefler and Andrew Lumsdaine},
  title={{A Space-Efficient Parallel Algorithm for Computing Betweenness Centrality in Distributed Memory}},
  journal={},
  institution={},
  year={2010},
  month={12},
  pages={1 - 10},
  volume={},
  number={},
  booktitle={International Conference on High Performance Computing},
  location={Goa, India},
  publisher={},
  issn={},
  isbn={978-1-4244-8518-5 },
  note={},
}