A GPU-Accelerated Two-Dimensional Hydrodynamic Model for Unstructured Grids

The precision of numerical overland flow models is limited by their computational cost. A GPU-accelerated 2D shallow flow model is developed to overcome this challenge in this study. The model employs a Godunov-type finite volume method (FVM) to solve shallow water equations (SWEs) with unstructured grids, while also considering rainfall, infiltration, bottom slope, and friction source terms. The numerical simulation demonstrates that this model has well-balanced and robust properties. In an experiment of urban rain-runoff and flood, the accuracy and stability of the model are further demonstrated. The model is programmed with CUDA, and each numerical computation term is processed in parallel to adopt multi-thread GPU acceleration technology. With the GPU computation framework, this model can achieve a speeding up ration around 75 to single-thread CPU in the dam-break flow for a large-scale application.

Automated summary

A GPU-accelerated 2D shallow flow model is developed in this study to overcome the computational cost limitation of numerical overland flow models. The model uses a Godunov-type finite volume method to solve shallow water equations with unstructured grids, considering rainfall, infiltration, bottom slope, and friction source terms. The simulation demonstrates the well-balanced and robust properties of the model, and its accuracy and stability are further demonstrated in an urban rain-runoff and flood experiment. Programmed with CUDA, the model achieves significant acceleration with multi-thread GPU computation technology, achieving a speeding up ratio of approximately 75 compared to single-thread CPU in dam-break flow for large-scale applications.