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TuningGenie: Auto-Tuning Framework Based on Rewriting Rules

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Information and Communication Technologies in Education, Research, and Industrial Applications (ICTERI 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 469))

Abstract

This paper presents results on development of the auto-tuning framework named TuningGenie aimed at automating adjustment of parallel tasks to target platform. The framework works with source code of parallel software and performs source-to-source transformations by using facilities of a rule-based rewriting system. This approach significantly raises flexibility of proposed solution and enables changing computation structure of a tuned program in a declarative way. The framework’s architecture, lifecycle, offered toolset for optimization, demo examples and results of tuning of a computationally complex task of short-term meteorological forecasting are presented.

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Author information

Authors and Affiliations

  1. Institute of Software Systems of National Academy of Sciences of Ukraine, Glushkov prosp. 40, Kyiv, 03187, Ukraine

    Pavlo A. Ivanenko, Anatoliy Y. Doroshenko & Kostiantyn A. Zhereb

Authors
  1. Pavlo A. Ivanenko
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  2. Anatoliy Y. Doroshenko
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  3. Kostiantyn A. Zhereb
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Corresponding author

Correspondence to Pavlo A. Ivanenko .

Editor information

Editors and Affiliations

  1. Zaporizhzhya National University, Zaporizhzhya, Ukraine

    Vadim Ermolayev

  2. Institute of Applied Informatics, Alpen-Adria-Universität Klagenfurt, Klagenfurt, Austria

    Heinrich C. Mayr

  3. Taras Shevchenko National University of Kyiv, Kyiv, Ukraine

    Mykola Nikitchenko

  4. Kherson State University, Kherson, Ukraine

    Aleksander Spivakovsky

  5. V.N. Karazin Kharkiv National University, Kharkov, Ukraine

    Grygoriy Zholtkevych

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© 2014 Springer International Publishing Switzerland

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Ivanenko, P.A., Doroshenko, A.Y., Zhereb, K.A. (2014). TuningGenie: Auto-Tuning Framework Based on Rewriting Rules. In: Ermolayev, V., Mayr, H., Nikitchenko, M., Spivakovsky, A., Zholtkevych, G. (eds) Information and Communication Technologies in Education, Research, and Industrial Applications. ICTERI 2014. Communications in Computer and Information Science, vol 469. Springer, Cham. https://doi.org/10.1007/978-3-319-13206-8_7

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  • DOI: https://doi.org/10.1007/978-3-319-13206-8_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13205-1

  • Online ISBN: 978-3-319-13206-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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