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Accelerating Processing of Scale-Free Graphs on Massively-Parallel Architectures

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Algorithms and Architectures for Parallel Processing (ICA3PP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10393))

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Abstract

Processing of big scale-free graphs on parallel architectures with high parallelization opportunities connected with a lot of overheads. Due to skewed degree distribution each thread receives different amount of computational workload. In this paper we present a method devoted to address this challenge by modificating CSR data structure and redistributing work across threads. The method was implemented in breadth-first search and single source shortest path algorithms for GPU architecture.

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Acknowledgments

The research was supported by the Ministry of Education and Science of the Russian Federation Agreement no. 02.A03.21.0006.

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Authors and Affiliations

  1. Krasovskii Institute of Mathematics and Mechanics, Ural Federal University, Yekaterinburg, Russia

    Mikhail Chernoskutov

Authors
  1. Mikhail Chernoskutov
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Correspondence to Mikhail Chernoskutov .

Editor information

Editors and Affiliations

  1. Inria, Rennes, France

    Shadi Ibrahim

  2. University of Texas at San Antonio, San Antonio, Texas, USA

    Kim-Kwang Raymond Choo

  3. Aalto University, Espoo, Finland

    Zheng Yan

  4. University of Alberta, Edmonton, Alberta, Canada

    Witold Pedrycz

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Chernoskutov, M. (2017). Accelerating Processing of Scale-Free Graphs on Massively-Parallel Architectures. In: Ibrahim, S., Choo, KK., Yan, Z., Pedrycz, W. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2017. Lecture Notes in Computer Science(), vol 10393. Springer, Cham. https://doi.org/10.1007/978-3-319-65482-9_61

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  • DOI: https://doi.org/10.1007/978-3-319-65482-9_61

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65481-2

  • Online ISBN: 978-3-319-65482-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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