Turbulence simulations on the verge of Exascale: GPU algorithms and an alternative to long simulations at high resolutions

With Exascale Computing having officially arrived in mid 2022, we report on the development of a new Exascale-ready GPU algorithm for 3D homogeneous turbulence. Our goal is to push the envelope in simulation size while optimizing code performance aggressively by fully exploiting the particular strengths of leadership-class hardware and software. In particular on ``Frontier'' at Oak Ridge National Laboratory, OpenMP offloading to GPUs, fast GPU-aware message passing and reduced needs for host-device data copying are helping make turbulence simulations at $32768^3$ resolution a reality, and also raising hopes for other computational challenges previously out of reach. However, resource requirements in turbulence actually grow with problem size so fast that long, well-sampled simulations at state-of-the-art resolution are becoming increasingly less feasible. We briefly discuss a new simulation paradigm (Yeung \& Ravikumar, PRF 2020) which is well-suited for problems requiring good statistics of the small scales which evolve rapidly in time.