A Parallel Algorithm for Computing Betweenness Centrality

In this paper we present a multi-grained parallel algorithm for computing betweenness centrality, which is extensively used in large-scale network analysis. Our method is based on a novel algorithmic handling of access conflicts for a CREW PRAM algorithm. We propose a proper data-processor mapping, a novel edge-numbering strategy and a new triple array data structure recording the shortest path for eliminating conflicts to access the shared memory. The algorithm requires O(n + m) space and O(nm p ) ( or O(nm+n2 logn p )) time for unweighted (or weighted) graphs, and it is a work-optimal CREW PRAM algorithm. On current multi-core platforms, our algorithm outperforms the previous algorithm by 2-3 times. Keywords-betweenness centrality; multi-core algorithm; multi-grained parallelism; CREW;

• Type: Journal
• Year: 2009
• Where: ICPP
• Authors: Guangming Tan, Dengbiao Tu, Ninghui Sun
• Keywords: Algorithm, CREW PRAM Algorithm, Distributed And Parallel Computing, ICPP 2009, Multi-grained Parallel Algorithm