Fast parallel graph triad census and triangle counting on shared-memory platforms

Sindhuja Parimalarangan, George M. Slota, Kamesh Madduri

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

7 Scopus citations

Abstract

Triad census is a graph analytic used for comparative network analysis and to characterize local structure in directed networks. For large sparse graphs, an algorithm by Batagelj and Mrvar is considered the state-of-the-art for computing triad census. In this paper, we present a new parallel algorithm for triad census. Our algorithm takes advantage of a specific graph vertex identifier ordering to reduce the operation count. We also develop several new variants for exact triangle counting in large sparse, undirected graphs. We show that our parallel triangle counting variants outperform other recently-developed triangle counting methods on current Intel multicore and manycore processors. We also achieve good strong scaling for both triad census and triangle counting on these platforms.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1500-1509
Number of pages10
ISBN (Electronic)9781538634080
DOIs
StatePublished - Jun 30 2017
Event31st IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017 - Orlando, United States
Duration: May 29 2017Jun 2 2017

Publication series

NameProceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017

Other

Other31st IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017
CountryUnited States
CityOrlando
Period5/29/176/2/17

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Computer Networks and Communications
  • Information Systems

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  • Cite this

    Parimalarangan, S., Slota, G. M., & Madduri, K. (2017). Fast parallel graph triad census and triangle counting on shared-memory platforms. In Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017 (pp. 1500-1509). [7965213] (Proceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IPDPSW.2017.144