Designing a graphics processing unit accelerated petaflop capable lattice Boltzmann solver: Read aligned data layouts and asynchronous communication

Fredrik Robertsén, Jan Westerholm, Keijo Mattila

    Research output: Contribution to journalArticleScientificpeer-review

    4 Citations (Scopus)

    Abstract

    The lattice Boltzmann method is a well-established numerical approach for complex fluid flow simulations. Recently, general-purpose graphics processing units (GPUs) have become available as high-performance computing resources at large scale. We report on designing and implementing a lattice Boltzmann solver for multi-GPU systems that achieves 1.79 PFLOPS performance on 16,384 GPUs. To achieve this performance, we introduce a GPU compatible version of the so-called bundle data layout and eliminate the halo sites in order to improve data access alignment. Furthermore, we make use of the possibility to overlap data transfer between the host central processing unit and the device GPU with computing on the GPU. As a benchmark case, we simulate flow in porous media and measure both strong and weak scaling performance with the emphasis being on large-scale simulations using realistic input data.
    Original languageEnglish
    Pages (from-to)246-255
    Journal International Journal of High Performance Computing Applications
    Volume31
    Issue number3
    DOIs
    Publication statusPublished - 24 Aug 2016
    Publication typeA1 Journal article-refereed

    Publication forum classification

    • Publication forum level 2

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