Algebraic methods in the congested clique

  • Keren Censor-Hillel
  • Petteri Kaski
  • Janne H. Korhonen
  • Christoph Lenzen
  • Ami Paz
  • Jukka Suomela
Article

Abstract

In this work, we use algebraic methods for studying distance computation and subgraph detection tasks in the congested clique model. Specifically, we adapt parallel matrix multiplication implementations to the congested clique, obtaining an \(O(n^{1-2/\omega })\) round matrix multiplication algorithm, where \(\omega < 2.3728639\) is the exponent of matrix multiplication. In conjunction with known techniques from centralised algorithmics, this gives significant improvements over previous best upper bounds in the congested clique model. The highlight results include:
  1. 1.

    triangle and 4-cycle counting in \(O(n^{0.158})\) rounds, improving upon the \(O(n^{1/3})\) algorithm of Dolev et al. [DISC 2012],

     
  2. 2.

    a \((1 + o(1))\)-approximation of all-pairs shortest paths in \(O(n^{0.158})\) rounds, improving upon the \(\tilde{O} (n^{1/2})\)-round \((2 + o(1))\)-approximation algorithm given by Nanongkai [STOC 2014], and

     
  3. 3.

    computing the girth in \(O(n^{0.158})\) rounds, which is the first non-trivial solution in this model.

     
In addition, we present a novel constant-round combinatorial algorithm for detecting 4-cycles.

Keywords

Distributed computing Congested clique model Lower bounds Matrix multiplication Subgraph detection Distance computation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Keren Censor-Hillel
    • 1
  • Petteri Kaski
    • 2
  • Janne H. Korhonen
    • 3
    • 4
  • Christoph Lenzen
    • 5
  • Ami Paz
    • 1
  • Jukka Suomela
    • 2
  1. 1.Department of Computer ScienceTechnionHaifaIsrael
  2. 2.HIIT & Department of Computer ScienceAalto UniversityEspooFinland
  3. 3.HIIT & Department of Computer ScienceUniversity of HelsinkiHelsinkiFinland
  4. 4.School of Computer ScienceReykjavík UniversityReykjavíkIceland
  5. 5.Department for Algorithms and ComplexityMPI SaarbrückenSaarbrückenGermany

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