The FastEddy® Resident-GPU Accelerated Large-Eddy Simulation Framework: Model Formulation, Dynamical-Core Validation and Performance Benchmarks

This paper introduces a new large-eddy simulation model, FastEddy®, purpose built for leveraging the accelerated and more power-efficient computing capacity of graphics processing units (GPUs) toward adopting microscale turbulence-resolving atmospheric boundary layer simulations into future numerical weather prediction activities. Here a basis for future endeavors with the FastEddy® model is provided by describing the model dry dynamics formulation and investigating several validation scenarios that establish a baseline of model predictive skill for canonical neutral, convective, and stable boundary layer regimes, along with boundary layer flow over heterogeneous terrain. The current FastEddy® GPU performance and efficiency gains versus similarly formulated, state-of-the-art CPU-based models is determined through scaling tests as 1 GPU to 256 CPU cores. At this ratio of GPUs to CPU cores, FastEddy® achieves 6 times faster prediction rate than commensurate CPU models under equivalent power consumption. Alternatively, FastEddy® uses 8 times less power at this ratio under equivalent CPU/GPU prediction rate. The accelerated performance and efficiency gains of the FastEddy® model permit more broad application of large-eddy simulation to emerging atmospheric boundary layer research topics through substantial reduction of computational resource requirements and increase in model prediction rate.