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A simulation suite for lattice Boltzmann based real time CFD applications exploiting multi-level parallelism on modern multi-and many-core architectures

Markus Geveler, Dirk Ribbrock, Sven Mallach, Dominik Goddeke
Institut fur Angewandte Mathematik (LS3), TU Dortmund, Vogelpothsweg 87, D-44227 Dortmund, Germany
Journal of Computational Science, Volume 2, Issue 2, Pages 113-123, 2011

@article{Geveler2011113,

   title={"AsimulationsuiteforLattice-Boltzmannbasedreal-timeCFDapplicationsexploitingmulti-levelparallelismonmodernmulti-andmany-corearchitectures"},

   journal={"JournalofComputationalScience"},

   volume={"2"},

   number={"2"},

   pages={"113-123"},

   year={2011},

   note={"<ce:title>SimulationSoftwareforSupercomputers</ce:title>"},

   issn={"1877-7503"},

   doi={"10.1016/j.jocs.2011.01.008"},

   url={"http://www.sciencedirect.com/science/article/pii/S1877750311000159"},

   author={"MarkusGevelerandDirkRibbrockandSvenMallachandDominikGoddeke"},

   keywords={"Lattice-Boltzmannmethodsfluid-structureinteraction"}

}

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We present a software approach to hardware-oriented numerics which builds upon an augmented, previously published set of open-source libraries facilitating portable code development and optimisation on a wide range of modern computer architectures. In order to maximise efficiency, we exploit all levels of parallelism, including vectorisation within CPU cores, the Cell BE and GPUs, shared memory thread-level parallelism between cores, and parallelism between heterogeneous distributed memory resources in clusters. To evaluate and validate our approach, we implement a collection of modular building blocks for the easy and fast assembly and development of CFD applications based on the shallow water equations: We combine the Lattice-Boltzmann method with fluid-structure interaction techniques in order to achieve real-time simulations targeting interactive virtual environments. Our results demonstrate that recent multi-core CPUs outperform the Cell BE, while GPUs are significantly faster than conventional multi-threaded SSE code. In addition, we verify good scalability properties of our application on small clusters.
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