| 要約: | This work presents a state-of-the-art computational approach for performing large-scale simulations of turbulence on heterogeneous compute nodes. The approach proposed combines message passing interface (MPI) parallelization for distributing the computation across nodes with open accelerators (OpenACC) to target a graphical processing unit (GPU) acceleration. Two different OpenACC approaches, corresponding to managed and non-managed data management, have been tested and compared. The results obtained indicate that the non-managed strategy outperforms the non-managed scheme in all cases. Additionally, the non-managed GPU-accelerated approach presents an overall speedup of 6× with respect to the CPU version. Finally, the capability of the resulting parallel and accelerated flow solver to perform high-fidelity simulations of turbulent flow is validated against a canonical wall-bounded fluid problem.
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