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Computational fluid dynamics (CFD) requires a vast amount of compute cycleson contemporary large-scale parallel computers. Hence, performance optimizationis a pivotal activity in this field of computational science. Not only does itreduce the time to solution, but it also allows to minimize the energyconsumption. In this work we study performance optimizations for anMPI-parallel lattice Boltzmann-based flow solver that uses a sparse latticerepresentation with indirect addressing. First we describe how this indirectaddressing can be minimized in order to increase the single-core and chip-levelperformance. Second, the communication overhead is reduced via appropriatepartitioning, but maintaining the single core performance improvements. Bothoptimizations allow to run the solver at an operating point with minimal energyconsumption.

Modeling and analyzing performance for highly optimized propagation steps of the lattice Boltzmann method on sparse lattices