research-article

On fast parallel detection of strongly connected components (SCC) in small-world graphs

Authors:

Nicole C. Rodia,

Kunle OlukotunAuthors Info & Claims

SC '13: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis

Article No.: 92, Pages 1 - 11

https://doi.org/10.1145/2503210.2503246

Published: 17 November 2013 Publication History

Abstract

Detecting strongly connected components (SCCs) in a directed graph is a fundamental graph analysis algorithm that is used in many science and engineering domains. Traditional approaches in parallel SCC detection, however, show limited performance and poor scaling behavior when applied to large real-world graph instances. In this paper, we investigate the shortcomings of the conventional approach and propose a series of extensions that consider the fundamental properties of real-world graphs, e.g. the small-world property. Our scalable implementation offers excellent performance on diverse, small-world graphs resulting in a 5.01x to 29.41x parallel speedup over the optimal sequential algorithm with 16 cores and 32 hardware threads.

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On fast parallel detection of strongly connected components (SCC) in small-world graphs

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cover image ACM Conferences

SC '13: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis

November 2013

1123 pages

ISBN:9781450323789

DOI:10.1145/2503210

General Chair:
William Gropp
University of Illinois at Urbana-Champaign, Urbana, Illinois
,
Program Chair:
Satoshi Matsuoka
Tokyo Institute of Technology, Tokyo, Japan

Copyright © 2013 ACM.

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Published: 17 November 2013

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SC13: International Conference for High Performance Computing, Networking, Storage and Analysis

November 17 - 21, 2013

Colorado, Denver

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SC '13 Paper Acceptance Rate 91 of 449 submissions, 20%;

Overall Acceptance Rate 1,516 of 6,373 submissions, 24%

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Xie HFang YXia YLuo WMa C(2023)On Querying Connected Components in Large Temporal GraphsProceedings of the ACM on Management of Data10.1145/35893151:2(1-27)Online publication date: 20-Jun-2023
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Wang LDong XGu YSun Y(2023)Parallel Strong Connectivity Based on Faster ReachabilityProceedings of the ACM on Management of Data10.1145/35892591:2(1-29)Online publication date: 20-Jun-2023
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Alabandi GSands WBiros GBurtscher MMohror KArnold DBadia R(2023)A GPU Algorithm for Detecting Strongly Connected ComponentsProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1145/3581784.3607071(1-13)Online publication date: 12-Nov-2023
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