Numerical simulation of surface runoff process based on multi-GPU numerical framework
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Abstract:
Compared to the traditional conceptual hydrological models, two-dimensional hydrodynamic models can provide more comprehensive hydraulic information of watershed surfaces, but the issue of long computational time restricts its widespread application. Exploring ways to improve the computational efficiency of two-dimensional hydraulic models has become one of the hot points and key technological challenges in current digital twin watershed development. The rapid advancement of GPU hardware technology has enabled the utilization of two-dimensional hydraulic models for the purpose of simulating watershed flood processes in real time. The potential applications of this technology in the construction of digital twin watersheds appear bright.The model is established based on a structured grid and adopts the Godunov scheme based on the finite volume method to discretize the complete two-dimensional shallow water equations. A high-performance accelerated calculation based on multiple GPUs is realized by combining MPI and CUDA computing architecture to meet the requirements of large-scale parallel computing tasks and realize the simultaneous work of multiple GPUs. MPI implements message passing between parallel processes based on the distributed storage model. Each process has a unique process rank at runtime and controls a GPU device. When using multiple GPUs for computation, the computational domain needs to be divided into multiple subdomains, and each GPU is assigned to compute a specific subdomain. Each subdomain is surrounded by an additional layer of grid cells that is used to communicate with adjacent subdomains. This outer layer of grid cells receives data from the adjacent subdomains to perform updates. Once the communication is completed, the computation continues within each subdomain.The model's numerical accuracy has been verified using ideal and real watershed cases, with a relative error of 0.011% for the peak discharge in the ideal case and 2.98% for the peak discharge in the real watershed case. The acceleration effect of the model under different cell resolutions was analyzed in the Baogaisi watershed. The results showed that when the total number of grids reaches a certain scale, the multi-GPU acceleration technology can obtain a satisfactory acceleration effect. When the grid resolutions of the watershed are 5 m, 2 m, and 1 m, the corresponding grid units are 861,605, 5384,807, and 21,539,061. The speedup ratios obtained by 8 Tesla V100 GPUs are 1.58, 3.92, and 5.77, respectively. Higher cell resolutions lead to more significant acceleration effects with multiple GPUs. The hydrodynamic model based on multi-GPU has great potential for acceleration and can provide strong technical support for the construction of digital twin river basins.
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