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A modular lattice boltzmann solver for GPU computing processors

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Abstract

During the past two decades, the lattice Boltzmann method (LBM) has been increasingly acknowledged as a valuable alternative to classical numerical techniques (e.g. finite elements, finite volumes, etc.) in fluid dynamics. A distinguishing feature of LBM is undoubtedly its highly parallelizable data structure. In this work we present a general parallel LBM framework for graphic processing units (GPUs) characterized by a high degree of modularity and memory efficiency, still preserving very good computational performance. After recalling the essential programming principles of the CUDA C language for GPUs, the details of the implementation will be provided. The data structure here presented takes into account the intrinsic properties of the Gauss-Hermite quadrature rules (on which the LBM is based) to guarantee a unique and flexible framework for two- and three-dimensional problems. In addition, a careful implementation of a memory efficient formulation of the LBM algorithm has allowed to limit the high memory consumption that typically affects this computational method. Numerical examples in two and three dimensions illustrate the reliability and the performance of the code.

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Authors and Affiliations

  1. CMCS, Chair of Modelling and Scientific Computing, MATHICSE, Mathematics Institute of Computational Science and Engineering, École Polytechnique Fédérale de Lausanne, Station 8, CH-1015, Lausanne, Switzerland

    M. Astorino & J. Becerra Sagredo

  2. Department of Mathematics, Politecnico di Milano, MOX, Modeling and Scientific Computing, Via Bonardi 9, 20133, Milano, Italy

    A. Quarteroni

Authors
  1. M. Astorino
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  2. J. Becerra Sagredo
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  3. A. Quarteroni
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Correspondence to A. Quarteroni.

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Astorino, M., Sagredo, J.B. & Quarteroni, A. A modular lattice boltzmann solver for GPU computing processors. SeMA 59, 53–78 (2012). https://doi.org/10.1007/BF03322610

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