NDLI: A modular lattice boltzmann solver for GPU computing processors

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A modular lattice boltzmann solver for GPU computing processors

Content Provider	Semantic Scholar
Author	Astorino, Matteo Sagredo, J. Quarteroni, Alfio
Copyright Year	2012
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.
Starting Page	53
Ending Page	78
Page Count	26
File Format	PDF HTM / HTML
DOI	10.1007/BF03322610
Volume Number	59
Alternate Webpage(s)	https://mathicse.epfl.ch/files/content/sites/mathicse/files/Mathicse%20reports%202011/06.2011%20MA-AQ.pdf
Alternate Webpage(s)	https://doi.org/10.1007/BF03322610
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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