Massively Parallel Algorithms for the Lattice Boltzmann Method on Non-uniform Grids
Florian Schornbaum, Ulrich R\"ude

TL;DR
This paper introduces parallel algorithms and data structures for the lattice Boltzmann method on non-uniform grids, enabling highly scalable large-scale flow simulations on supercomputers with near-trillion cell updates per second.
Contribution
It presents novel parallel algorithms and data structures supporting large-scale, non-uniform grid lattice Boltzmann simulations, implemented in the waLBerla framework.
Findings
Near-perfect scalability on Blue Gene/Q with almost two million threads.
Achieved close to a trillion lattice Boltzmann cell updates per second.
Simulation of over 8.5 million cells with less than one millisecond per time step.
Abstract
The lattice Boltzmann method exhibits excellent scalability on current supercomputing systems and has thus increasingly become an alternative method for large-scale non-stationary flow simulations, reaching up to a trillion grid nodes. Additionally, grid refinement can lead to substantial savings in memory and compute time. These saving, however, come at the cost of much more complex data structures and algorithms. In particular, the interface between subdomains with different grid sizes must receive special treatment. In this article, we present parallel algorithms, distributed data structures, and communication routines that are implemented in the software framework waLBerla in order to support large-scale, massively parallel lattice Boltzmann-based simulations on non-uniform grids. Additionally, we evaluate the performance of our approach on two current petascale supercomputers. On…
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