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GPU Acceleration of the caffa3d.MB Model

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Computational Science and Its Applications – ICCSA 2012 (ICCSA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7336))

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Abstract

This work presents a study of porting Strongly Implicit Procedure (SIP) solver to GPU in order to improve its computational efficiency. The SIP heptadiagonal linear system solver was evaluated to be the most time consuming stage in finite volume flow solver caffa3d.MB. The experimental evaluation of the proposed implementation of the solver demonstrates that a significant runtime reduction can be attained (acceleration values up to 10×) when compared with a CPU version, and this improvement significantly reduces the total runtime of the model. This results evidence a promising prospect for a full GPU-based implementation of finite volume flow solvers like caffa3d.MB.

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Author information

Authors and Affiliations

  1. Instituto de Computación, Universidad de la República, 11.300, Montevideo, Uruguay

    Pablo Igounet, Pablo Alfaro & Pablo Ezzatti

  2. Instituto de Mecánica de los Fluidos e Ingeniería Ambiental, Universidad de la República, 11.300, Montevideo, Uruguay

    Gabriel Usera

Authors
  1. Pablo Igounet
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  2. Pablo Alfaro
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  3. Gabriel Usera
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  4. Pablo Ezzatti
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Editor information

Editors and Affiliations

  1. Laboratory of Urban and Territorial Systems, University of Basilicata, 10, Viale dell’Ateneo Lucano, 85100, Potenza, Italy

    Beniamino Murgante

  2. Department of Mathematics and Computer Science, University of Perugia, Via Vanvitelli 1, 06123, Perugia, Italy

    Osvaldo Gervasi

  3. Department of Cyber Security Science, Federal University of Technology, Gidan Kwano Campus, Minna, Nigeria

    Sanjay Misra

  4. Faculty of Engineering, Department of Electronics Engineering and Telecommunications, State University of Rio de Janeiro, Rua Sao Francisco Xavier, 524, 50. andar, sala 5145-F, Maracana, 20, 550-013, Rio de Janeiro, RJ, Brazil

    Nadia Nedjah

  5. Department of Production and Systems, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal

    Ana Maria A. C. Rocha

  6. School of Business Systems, Monash University, 3800, Clayton, VIC, Australia

    David Taniar

  7. Department of Intelligent Informatics, Kyushu Sangyo University, 2-3-1 Matsukadai, Higashi-ku, 813-8503, Fukuoka, Japan

    Bernady O. Apduhan

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© 2012 Springer-Verlag Berlin Heidelberg

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Igounet, P., Alfaro, P., Usera, G., Ezzatti, P. (2012). GPU Acceleration of the caffa3d.MB Model. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2012. ICCSA 2012. Lecture Notes in Computer Science, vol 7336. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31128-4_39

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  • DOI: https://doi.org/10.1007/978-3-642-31128-4_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31127-7

  • Online ISBN: 978-3-642-31128-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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