Multilevel algorithms for partitioning power-law graphs

Amine Abou-Rjeili, George Karypis

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

174 Scopus citations

Abstract

Graph partitioning is an enabling technology for parallel processing as it allows for the effective decomposition of unstructured computations whose data dependencies correspond to a large sparse and irregular graph. Even though the problem of computing high-quality partitionings of graphs arising in scientific computations is to a large extent well-understood, this is far from being true for emerging HPC applications whose underlying computation involves graphs whose degree distribution follows a power-law curve. This paper presents new multilevel graph partitioning algorithms that are specifically designed for partitioning such graphs. It presents new clustering-based coarsening schemes that identify and collapse together groups of vertices that are highly connected. An experimental evaluation of these schemes on 10 different graphs show that the proposed algorithms consistently and significantly outperform existing state-of-the-art approaches.

Original languageEnglish (US)
Title of host publication20th International Parallel and Distributed Processing Symposium, IPDPS 2006
PublisherIEEE Computer Society
ISBN (Print)1424400546, 9781424400546
DOIs
StatePublished - 2006
Event20th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2006 - Rhodes Island, Greece
Duration: Apr 25 2006Apr 29 2006

Publication series

Name20th International Parallel and Distributed Processing Symposium, IPDPS 2006
Volume2006

Other

Other20th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2006
CountryGreece
CityRhodes Island
Period4/25/064/29/06

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