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Accelerating Keyword Search for Big RDF Web Data on Many-Core Systems

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Intelligent Software Methodologies, Tools and Techniques (SoMeT 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 532))

Abstract

Resource Description Framework (RDF) is the commonly used format for Semantic Web data. Nowadays, huge amounts of data on the Internet in the RDF format are used by search engines for providing answers to the queries of users. Querying through big data needs suitable searching methods supported by a very high processing power, because the traditional, sequential keyword matching on a semantic web server may take a prohibitively long time. In this paper, we aim at accelerating the search in big RDF data by exploiting modern many-core architectures based on Graphics Processing Units (GPUs). We develop several implementations of the RDF search for many-core architectures using two programming approaches: OpenMP for systems with CPUs and CUDA for systems comprising CPUs and GPUs. Experiments show that our approach is 20.5 times faster than the sequential search.

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Acknowledgments

This work was supported by the following institutes and research programs: The Thailand Research Fund (TRF) through the Royal Golden Jubilee Ph.D. Program under Grant PHD/0005/2554, DAAD (German Academic Exchange Service) Scholarship project id: 57084841, the Faculty of Engineering at Kasetsart University Research funding contract no. 57/12/MATE, the DFG Cells-in-Motion Cluster of Excellence (EXC 1003 – CiM), University of Muenster, Germany, as well by the FP7 EU project MONICA (PIRSES-GA-2011-295222) and a hardware grant from NVIDIA Corporation.

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Authors and Affiliations

  1. Department of Computing, Silpakorn University, Bangkok, Thailand

    Chidchanok Choksuchat

  2. Department of Computer Engineering, Kasetsart University, Bangkok, Thailand

    Chantana Chantrapornchai

  3. University of Muenster, Münster, Germany

    Michael Haidl & Sergei Gorlatch

Authors
  1. Chidchanok Choksuchat
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  2. Chantana Chantrapornchai
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  3. Michael Haidl
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  4. Sergei Gorlatch
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Corresponding author

Correspondence to Chantana Chantrapornchai .

Editor information

Editors and Affiliations

  1. Iwate Prefectural University, Takizawa, Japan

    Hamido Fujita

  2. University of Naples "Federico II", Napoli, Italy

    Guido Guizzi

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Choksuchat, C., Chantrapornchai, C., Haidl, M., Gorlatch, S. (2015). Accelerating Keyword Search for Big RDF Web Data on Many-Core Systems. In: Fujita, H., Guizzi, G. (eds) Intelligent Software Methodologies, Tools and Techniques. SoMeT 2015. Communications in Computer and Information Science, vol 532. Springer, Cham. https://doi.org/10.1007/978-3-319-22689-7_14

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  • DOI: https://doi.org/10.1007/978-3-319-22689-7_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22688-0

  • Online ISBN: 978-3-319-22689-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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