Parallel Algorithms for Evaluating Centrality Indices in Real-World Networks

dc.contributor.author Bader, David A.
dc.contributor.author Madduri, Kamesh
dc.date.accessioned 2007-05-22T19:19:20Z
dc.date.available 2007-05-22T19:19:20Z
dc.date.issued 2006-04-14
dc.description.abstract This paper discusses fast parallel algorithms for evaluating several centrality indices frequently used in complex network analysis. These algorithms have been optimized to exploit properties typically observed in real-world large scale networks, such as the low average distance, high local density, and heavy-tailed power law degree distributions. We test our implementations on real datasets such as the web graph, protein-interaction networks, movie-actor and citation networks, and report impressive parallel performance for evaluation of the computationally intensive centrality metrics (betweenness and closeness centrality) on high-end shared memory symmetric multiprocessor and multithreaded architectures. To our knowledge, these are the first parallel implementations of these widely-used social network analysis metrics. We demonstrate that it is possible to rigorously analyze networks three orders of magnitude larger than instances that can be handled by existing network analysis (SNA) software packages. For instance, we compute the exact betweenness centrality value for each vertex in a large US patent citation network (3 million patents, 16 million citations) in 42 minutes on 16 processors, utilizing 20GB RAM of the IBM p5 570. Current SNA packages on the other hand cannot handle graphs with more than hundred thousand edges. en
dc.identifier.uri http://hdl.handle.net/1853/14428
dc.language.iso en_US en
dc.publisher Georgia Institute of Technology en
dc.relation.ispartofseries CSE Technical Reports; GT-CSE-06-13 en
dc.subject Centrality metrics en
dc.subject Multithreaded architecture en
dc.subject Parallel algorithms en
dc.subject Real-world networks en
dc.subject Shared memory system en
dc.subject Symmetric multiprocessors (SMPs) en
dc.title Parallel Algorithms for Evaluating Centrality Indices in Real-World Networks en
dc.type Text
dc.type.genre Technical Report
dspace.entity.type Publication
local.contributor.corporatename College of Computing
local.contributor.corporatename School of Computational Science and Engineering
local.relation.ispartofseries College of Computing Technical Report Series
local.relation.ispartofseries School of Computational Science and Engineering Technical Report Series
relation.isOrgUnitOfPublication c8892b3c-8db6-4b7b-a33a-1b67f7db2021
relation.isOrgUnitOfPublication 01ab2ef1-c6da-49c9-be98-fbd1d840d2b1
relation.isSeriesOfPublication 35c9e8fc-dd67-4201-b1d5-016381ef65b8
relation.isSeriesOfPublication 5a01f926-96af-453d-a75b-abc3e0f0abb3
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
637.07 KB
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
1.86 KB
Item-specific license agreed upon to submission