Computational fluid dynamics (CFD) solvers are essential for understanding and predicting turbulent hypersonic flows, providing a critical resource for the timely development of atmospheric and space flight technologies as well as improving climate science. However, the sensitivity of hypersonic turbulence demands a high degree of numerical fidelity in simulations.

Existing approaches have been shown to achieve good performance on CPU-based systems using only MPI, but the emergence of GPU-based supercomputing platforms has created a new opportunity to further improve performance. In addition, adaptive mesh refinement (AMR) can massively decrease the amount of work required to achieve a given level of fidelity. In this project, we have adapted an existing hypersonics CFD code that was MPI-only to include support GPU acceleration and AMR using the AMReX library, adapting our use of AMReX to handle previously-unsupported curvilinear grids in interpolation and data management. This cumulatively results in substantial orders-of-magnitude reductions in time-to-solution on representative benchmarks.

Related Publications

[1] Josh Davis et al, "Extreme-scale Computational Fluid Dynamics with AMR on GPUs", Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC ’22, November 2022

[2] Josh Davis et al, "Porting a Computational Fluid Dynamics Code with AMR to Large-scale GPU Platforms", Proceedings of the IEEE International Parallel & Distributed Processing Symposium. IEEE Computer Society, May 2023