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International Conference on Intelligent Data Engineering and Automated Learning

IDEAL 2013: Intelligent Data Engineering and Automated Learning – IDEAL 2013 pp 342–349Cite as

Graph-Based Substructure Pattern Mining Using CUDA Dynamic Parallelism

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8206))

Abstract

CUDA is an advanced massively parallel computing platform that can provide high performance computing power at much more affordable cost. In this paper, we present a parallel graph-based substructure pattern mining algorithm using CUDA Dynamic Parallelism. The key contribution is a parallel solution to traversing the DFS (Depth First Search) code tree. Furthermore, we implement a parallel frequent subgraph mining algorithm based on the subgraph mining techniques used in gSpan and the entire subgraph mining procedure is executed on GPU to ensure high efficiency. This parallel gSpan is functionally identical to the original gSpan and experiment results show that, with the latest CUDA Dynamic Parallelism techniques, significant speedups can be achieved on benchmark datasets, particularly in traversing a DFS code tree.

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Author information

Authors and Affiliations

  1. Intelligent Computing Lab, Division of Informatics, Graduate School at Shenzhen, Tsinghua University, Shenzhen, 518055, P.R. China

    Fei Wang, Jianqiang Dong & Bo Yuan

Authors
  1. Fei Wang
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  2. Jianqiang Dong
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  3. Bo Yuan
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

  2. University of Science and Technology of China, Hefei, China

    Ke Tang

  3. Nanjing University, Nanjing, China

    Yang Gao

  4. Ostfalia University of Applied Sciences, 38302, Wolfenbüttel, Germany

    Frank Klawonn

  5. Kyungpook National University, 702-701, Buk-Gu, Daegu, Korea

    Minho Lee

  6. Nature Inspired Computational and Applications Laboratory, School of Computer Science and Technology,, University of Science and Technology of China, 230027, Hefei, China

    Thomas Weise

  7. University of Science and Technology of China, 230017, Hefei, China

    Bin Li

  8. CERCIA, School of Computer Science, University of Birmingham, B15 2TT, Edgbaston, Birmingham, UK

    Xin Yao

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Cite this paper

Wang, F., Dong, J., Yuan, B. (2013). Graph-Based Substructure Pattern Mining Using CUDA Dynamic Parallelism. In: Yin, H., et al. Intelligent Data Engineering and Automated Learning – IDEAL 2013. IDEAL 2013. Lecture Notes in Computer Science, vol 8206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41278-3_42

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  • DOI: https://doi.org/10.1007/978-3-642-41278-3_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41277-6

  • Online ISBN: 978-3-642-41278-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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