IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-642-03913-3_13.html
   My bibliography  Save this book chapter

Large-Scale Flow Computation of Complex Geometries by Building-Cube Method

In: High Performance Computing on Vector Systems 2009

Author

Listed:
  • Daisuke Sasaki

    (Tohoku University, Department of Aerospace Engineering)

  • Shun Takahashi

    (Tohoku University, Department of Aerospace Engineering)

  • Takashi Ishida

    (Tohoku University, Department of Aerospace Engineering)

  • Kazuhiro Nakahashi

    (Tohoku University, Department of Aerospace Engineering)

  • Hiroaki Kobayashi

    (Tohoku University, Cyberscience Center)

  • Koki Okabe

    (Tohoku University, Cyberscience Center)

  • Youichi Shimomura

    (NEC Software Tohoku)

  • Takashi Soga

    (NEC System Technology)

  • Akihiko Musa

    (NEC Corporation)

Abstract

Three-dimensional large scale incompressible flow simulation was conducted by Building-Cube Method (BCM) that is based on equally-spaced Cartesian mesh method. To exploit expected near-future high performance computer with massive number of processors, simple algorithms have been implemented in the BCM for mesh generation and flow solver. In this study, the capability of BCM for large-scale computation was demonstrated by solving formula 1 car model with around 200 million cells. The computation was conducted on Vector-Parallel Supercomputer system of NEC SX-9 at Cyberscience center of Tohoku University. The parallel efficiency of BCM with flat MPI and hybrid MPI on vector-parallel type system was also investigated.

Suggested Citation

  • Daisuke Sasaki & Shun Takahashi & Takashi Ishida & Kazuhiro Nakahashi & Hiroaki Kobayashi & Koki Okabe & Youichi Shimomura & Takashi Soga & Akihiko Musa, 2010. "Large-Scale Flow Computation of Complex Geometries by Building-Cube Method," Springer Books, in: Michael Resch & Sabine Roller & Katharina Benkert & Martin Galle & Wolfgang Bez & Hiroaki Kobayashi (ed.), High Performance Computing on Vector Systems 2009, pages 167-178, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-03913-3_13
    DOI: 10.1007/978-3-642-03913-3_13
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-642-03913-3_13. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.