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NumCIL and Bohrium: High Productivity and High Performance

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Parallel Processing and Applied Mathematics

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9574))

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Abstract

In this paper, we explore the mapping of the NumCIL C# vector library where operations are offloaded to the Bohrium runtime system and evaluate the performance gains. By using a feature-rich language, such as C#, we argue that productivity can be increased. The use of the Bohrium runtime system allows all vector operations written in C# to be executed efficiently on multi-core systems.

We evaluate the presented design through a setup that targets a 32 core machine. The evaluation includes well-known benchmark applications, such as Black Sholes, 5-point stencil, Shallow Water, and N-body.

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Acknowledgment

This research was supported by grant number 131-2014-5 from Innovation Fund Denmark. This research has been partially supported by the Danish Strategic Research Council, Program Committee for Strategic Growth Technologies, for the research center ‘HIPERFIT: Functional High Performance Computing for Financial Information Technology’ (hiperfit.dk) under contract number 10-092299.

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Authors and Affiliations

  1. Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

    Kenneth Skovhede & Simon Andreas Frimann Lund

Authors
  1. Kenneth Skovhede
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  2. Simon Andreas Frimann Lund
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Corresponding author

Correspondence to Kenneth Skovhede .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technolog, Czestochowa, Poland

    Roman Wyrzykowski

  2. Department of Computer Science, University of Southern California, Marina Del Rey, California, USA

    Ewa Deelman

  3. Electrical Engineering & Comput. Science, University of Tennessee, Knoxville, Tennessee, USA

    Jack Dongarra

  4. Czestochowa University of Technology, Institute of Computer & Information Sci., Czestochowa, Poland

    Konrad Karczewski

  5. Department of Computer Science, AGH University of Science and Technology, Krakow, Poland

    Jacek Kitowski

  6. Systèmes d’informations, Big Data et Rec, AGH University of Science and Technology, Krakow, Poland

    Kazimierz Wiatr

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Skovhede, K., Lund, S.A.F. (2016). NumCIL and Bohrium: High Productivity and High Performance. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K., Kitowski, J., Wiatr, K. (eds) Parallel Processing and Applied Mathematics. Lecture Notes in Computer Science(), vol 9574. Springer, Cham. https://doi.org/10.1007/978-3-319-32152-3_16

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  • DOI: https://doi.org/10.1007/978-3-319-32152-3_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32151-6

  • Online ISBN: 978-3-319-32152-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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