On the strong scalability of maritime CFD

Since 2004, supercomputer growth has been constrained by energy efficiency rather than raw hardware speeds. To maintain exponential growth of overall computing power, a massive growth in parallelization is under way. To keep up with these changes, computational fluid dynamics (CFD) must improve its strong scalability—its ability to handle lower cells-per-core ratios and achieve finer-grain parallelization.

A maritime-focused, unstructured, finite-volume code (ReFRESCO) is used to investigate the scalability problems for incompressible, viscous CFD using two classical test-cases. Existing research suggests that the linear equation-system solver is the main bottleneck to incompressible codes, due to the stiff Poisson pressure equation. Here, these results are expanded by analysing the reasons for this poor scalability. I

n particular, a number of alternative linear solvers and preconditioners are tested to determine if the scalability problem can be circumvented, including GMRES, Pipelined-GMRES, Flexible-GMRES and BCGS. Conventional block-wise preconditioners are tested, along with multi-grid preconditioners and smoothers in various configurations. Memory-bandwidth constraints and global communication patterns are found to be the main bottleneck, and no state-of-the-art solution techniques which solve the strong-scalability problem satisfactorily could be found. There is significant incentive for more research and development in this area.

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For more information contact Guilherme Vaz.

July 14, 2017
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