waLBerla: Optimization for Itanium-based Systems with Thousands of Processors

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Abstract

Performance optimization is an issue at different levels, in particular for computing and communication intensive codes like free surface lattice Boltzmann. This method is used to simulate liquid-gas flow phenomena such as bubbly flows and foams. Due to a special treatment of the gas phase, an aggregation of bubble volume data is necessary in every time step. In order to accomplish efficient parallel scaling, the all-to-all communication schemes used up to now had to be replaced with more sophisticated patterns that work in a local vicinity. With this approach, scaling could be improved such that simulation runs on up to 9 152 processor cores are possible with more than 90% efficiency. Due to the computation of surface tension effects, this method is also computational intensive. Therefore, also optimization of single core performance plays a tremendous role. The characteristics of the Itanium processor require programming techniques that assist the compiler in efficient code vectorization, especially for complex C++ codes like the waLBerla framework. An approach using variable length arrays shows promising results.