Performance Analysis Of Massively-Parallel Computational Fluid Dynamics

As modern supercomputers edge towards exascale, their architectures are becoming more parallel. In order for computational fluid dynamics (CFD) simulations to operate efficiently on newer machines, a complete harmony between hardware, software and numerical algorithms is required. In the work presented here, a typical CFD code is instrumented, and a strong-scalability study performed to identify areas of the execution which require improvement, using the well-known KVLCC2 test case. The effects of changing discretization schemes, mesh structure, turbulence models and linear solvers are all tested. The results show that data-exchange among cores and the inner-loop pre-conditioners both have a large impact on performance in a massively-parallel environment, and should be the focus of future developments.