Moment Representation in the Lattice Boltzmann Method on Massively Parallel Hardware

Authors: Madhurima Vardhan (Duke University), John Gounley (Oak Ridge National Laboratory), Luiz Hegele (Santa Catarina State University), Erik Draeger (Lawrence Livermore National Laboratory), Amanda Randles (Duke University)

Abstract: The widely-used lattice Boltzmann method (LBM) for computational fluid dynamics is highly scalable, but also significantly memory bandwidth-bound on current architectures. This paper presents a new regularized LBM implementation that reduces the memory footprint by only storing macroscopic, moment-based data. We show that the amount of data that must be stored in memory during a simulation is reduced by up to 47%. We also present a technique for cache-aware data re-utilization and show that optimizing cache utilization to limit data motion results in a similar improvement in time to solution. These new algorithms are implemented in the hemodynamics solver HARVEY and demonstrated using both idealized and realistic biological geometries. We develop a performance model for the moment representation algorithm and evaluate the performance on Summit.


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