A Scalable Distributed Louvain Algorithm for Large-Scale Graph Community Detection

Jianping Zeng, Hongfeng Yu

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

1 Scopus citations

Abstract

We present a new distributed community detection algorithm for large graphs based on the Louvain method. We exploit a distributed delegate partitioning to ensure the workload and communication balancing among processors. In addition, we design a new heuristic strategy to carefully coordinate the community constitution in a distributed environment, and ensure the convergence of the distributed clustering algorithm. Our intensive experimental study has demonstrated the scalability and the correctness of our algorithm with various large-scale real-world and synthetic graph datasets using up to 32,768 processors.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE International Conference on Cluster Computing, CLUSTER 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages268-278
Number of pages11
ISBN (Electronic)9781538683194
DOIs
StatePublished - Oct 29 2018
Event2018 IEEE International Conference on Cluster Computing, CLUSTER 2018 - Belfast, United Kingdom
Duration: Sep 10 2018Sep 13 2018

Publication series

NameProceedings - IEEE International Conference on Cluster Computing, ICCC
Volume2018-September
ISSN (Print)1552-5244

Other

Other2018 IEEE International Conference on Cluster Computing, CLUSTER 2018
CountryUnited Kingdom
CityBelfast
Period9/10/189/13/18

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Keywords

  • Accuracy
  • Community detection
  • Graph clustering
  • Large graph
  • Parallel and distributed processing
  • Scalability

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Signal Processing

Cite this

Zeng, J., & Yu, H. (2018). A Scalable Distributed Louvain Algorithm for Large-Scale Graph Community Detection. In Proceedings - 2018 IEEE International Conference on Cluster Computing, CLUSTER 2018 (pp. 268-278). [8514887] (Proceedings - IEEE International Conference on Cluster Computing, ICCC; Vol. 2018-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CLUSTER.2018.00044