Parallelizing Maximal Clique Enumeration on GPUs

Mohammad Almasri, Yen Hsiang Chang, Izzat El Hajj, Rakesh Nagi, Jinjun Xiong, Wen Mei Hwu

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

Abstract

We present a GPU solution for exact maximal clique enumeration (MCE) that performs a search tree traversal following the Bron-Kerbosch algorithm. Prior works on parallelizing MCE on GPUs perform a breadth-first traversal of the tree, which has limited scalability because of the explosion in the number of tree nodes at deep levels. We propose to parallelize MCE on GPUs by performing depth-first traversal of independent subtrees in parallel. Since MCE suffers from high load imbalance and memory capacity requirements, we propose a worker list for dynamic load balancing, as well as partial induced subgraphs and a compact representation of excluded vertex sets to regulate memory consumption. Our evaluation shows that our GPU implementation on a single GPU outperforms the state-of-the-art parallel CPU implementation by a geometric mean of 4.9× (up to 16.7×), and scales efficiently to multiple GPUs. Our code has been open-sourced to enable further research on accelerating MCE.

Original languageEnglish (US)
Title of host publicationProceedings - 2023 32nd International Conference on Parallel Architecture and Compilation Techniques, PACT 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages162-175
Number of pages14
ISBN (Electronic)9798350342543
DOIs
StatePublished - 2023
Event32nd International Conference on Parallel Architecture and Compilation Techniques, PACT 2023 - Vienna, Austria
Duration: Oct 21 2023Oct 25 2023

Publication series

NameParallel Architectures and Compilation Techniques - Conference Proceedings, PACT
ISSN (Print)1089-795X

Conference

Conference32nd International Conference on Parallel Architecture and Compilation Techniques, PACT 2023
Country/TerritoryAustria
CityVienna
Period10/21/2310/25/23

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture

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