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Parallelization of an XML Data Compressor on Multi-cores

  • Conference paper
Parallel Processing and Applied Mathematics (PPAM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7204))

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Abstract

Because of a growing interest in using XML for massive complex data there has been considerable research on designing XML compressors. This paper presents our research aimed at building parallel XML compressors, using Java and OpenMP (with C++). Our findings show that OpenMP is a preferred choice achieving better results than Java using a multi-core platform.

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Author information

Authors and Affiliations

  1. Jodrey School of Computer Science, Acadia University, Wolfville, B4P 2A9, NS, Canada

    Tomasz Müldner, Christopher Fry & Tyler Corbin

  2. IBI AL, University of Warsaw, Warsaw, Poland

    Jan Krzysztof Miziołek

Authors
  1. Tomasz Müldner
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  2. Christopher Fry
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  3. Tyler Corbin
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  4. Jan Krzysztof Miziołek
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Editor information

Editors and Affiliations

  1. Institute of Computer and Information Science, Czestochowa University of Technology, Dabrowskiego 69, 42-201, Czestochowa, Poland

    Roman Wyrzykowski  & Konrad Karczewski  & 

  2. Electrical Engineering and Computer Science Department, University of Tennessee, 1122 Volunteer Blvd, 37996-3450, Knoxville, TN, USA

    Jack Dongarra

  3. Department of Informatics and Mathematical Modeling, Technical University of Denmark, Richard Petersens Plads, Building 321, 2800, Kongens Lyngby, Denmark

    Jerzy Waśniewski

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© 2012 Springer-Verlag Berlin Heidelberg

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Müldner, T., Fry, C., Corbin, T., Miziołek, J.K. (2012). Parallelization of an XML Data Compressor on Multi-cores. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2011. Lecture Notes in Computer Science, vol 7204. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31500-8_11

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  • DOI: https://doi.org/10.1007/978-3-642-31500-8_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31499-5

  • Online ISBN: 978-3-642-31500-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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