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Improving Data Locality of RNA Secondary Structure Prediction Code

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Artificial Intelligence and Soft Computing (ICAISC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10245))

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Abstract

An approach allowing us to improve the locality of RNA Secondary Structure Prediction code is proposed. We discuss the application of this technique to automatic loop nest tiling for the Nussinov algorithm. The approach requires an exact representation of dependences in the form of tuple relations and calculating the transitive closure of dependence graphs. First, to improve code locality, 3-d rectangular tiles are formed within the 3-d iteration space of the Nussinov loop nest. Then tiles are corrected to establish code validity by means of applying the exact transitive closure of a dependence graph. The approach has been implemented as a part of the polyhedral TRACO compiler. The experimental results presents the speed-up factor of optimized code. Related work and future tasks are outlined.

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Notes

  1. 1.

    traco.sourceforge.net.

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Acknowledgments

Thanks to the Miclab Team (miclab.pl) from the Technical University of Czestochowa (Poland) that provided access to high performance multi-core machines for the experimental study presented in this paper.

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Authors and Affiliations

  1. Faculty of Computer Science and Information Systems, West Pomeranian University of Technology in Szczecin, Zolnierska 49, 71210, Szczecin, Poland

    Marek Palkowski, Wlodzimierz Bielecki & Piotr Skotnicki

Authors
  1. Marek Palkowski
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  2. Wlodzimierz Bielecki
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  3. Piotr Skotnicki
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Corresponding author

Correspondence to Marek Palkowski .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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Palkowski, M., Bielecki, W., Skotnicki, P. (2017). Improving Data Locality of RNA Secondary Structure Prediction Code. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10245. Springer, Cham. https://doi.org/10.1007/978-3-319-59063-9_62

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  • DOI: https://doi.org/10.1007/978-3-319-59063-9_62

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59062-2

  • Online ISBN: 978-3-319-59063-9

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