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    A Parallel Performance Study of the High-order Compact Direct Flux Reconstruction Method for Conservation Laws on Maya Cluster

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    LaiWangHPCF2017.pdf (568.8Kb)
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    https://userpages.umbc.edu/~gobbert/papers/LaiWangHPCF2017.pdf
    Permanent Link
    http://hdl.handle.net/11603/11299
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    • UMBC Mechanical Engineering Department
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    Author/Creator
    Wang, Lai
    Yu, Meilin
    Gobbert, Matthias K.
    Date
    2017
    Type of Work
    11 pages
    Text
    Technical Report
    Rights
    This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please contact the author.
    Subjects
    compact direct flux reconstruction method (CDFR)
    UMBC High Performance Computing Facility (HPCF)
    conservation laws
    compact finite difference methods
    approximating spatial derivatives of fluxes
    parallel performance study of the 3rd-order CDFR
    3rd-order explicit Runge-Kutta scheme
    inviscid isentropic vortex propagation problem
    comparison between different partition approaches
    optimizing communication to improve the parallel performance.
    Abstract
    The compact direct flux reconstruction method (CDFR) for conservation laws utilizes techniques from compact finite difference methods to directly approximate spatial derivatives of fluxes within standard elements. The CDFR scheme is a compact high-order method family which can be efficiently parallelized for high performance computing. In the present study, a parallel performance study of the 3rd-order CDFR scheme with a 3rd-order explicit Runge-Kutta scheme is conducted. The inviscid isentropic vortex propagation problem is adopted as a test case. The numerical performance studies have demonstrated that the CDFR method can efficiently solve conservation laws. The parallel performance study shows excellent observed speedup and efficiency. A comparison between different partition approaches of the mesh also demonstrates that optimized communication between processes can improve the parallel performance.


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    Albin O. Kuhn Library & Gallery
    University of Maryland, Baltimore County
    1000 Hilltop Circle
    Baltimore, MD 21250
    www.umbc.edu/scholarworks

    Contact information:
    Email: scholarworks-group@umbc.edu
    Phone: 410-455-3544


    If you wish to submit a copyright complaint or withdrawal request, please email mdsoar-help@umd.edu.