基于 GPU 的城市暴雨淹没模拟流体力学数值模型

Hao Han, Jingming Hou, Zhao Jin, Pingping Luo, Guodong Li, Ye Zhang, Jiahui Gong, Da Luo, Siqi Yang
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摘要

通过加强城市洪水数值模型的计算能力,可以提高城市洪水预报和风险控制的响应能力。本研究开发了基于 GPU 的水动力模型,用于模拟城市暴雨洪水。通过模拟西咸新区某区域的暴雨洪水,所建立的模型可以实现高分辨率的城市暴雨洪水模拟,计算性能明显加快。定量分析了 5 米和 2 米分辨率下不同暴雨事件模拟的加速计算效率,结果表明,在所有场景下,应用两个 GPU 的绝对加速比和相对加速比分别是 CPU 和单个 GPU 的 10.8 至 12.6 倍和 1.32 至 1.68 倍。大规模暴雨淹没模拟的应用表明,与之前的研究相比,该模型具有出色的加速性能。此外,模拟中包含的计算网格数量越多,对加速计算性能的影响越明显。所提出的模型能有效预测淹没水深的空间变化。模拟结果为城市暴雨淹没管理提供了指导,提高了城市洪水应急决策的时间和效率。
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A GPU-based hydrodynamic numerical model for urban rainstorm inundation simulations
The response capacities of urban flood forecasting and risk control can be improved by strengthening the computational abilities of urban flood numerical models. In this work, a GPU-based hydrodynamic model is developed to simulate urban rainstorm inundations. By simulating rainstorm floods in a certain area of Xixian New City, the established model can implement high-resolution urban rainstorm inundation simulations with significantly accelerated computing performances. The accelerated computation efficiencies of the different rainstorm event simulations under resolutions of 5 and 2 m are quantitatively analysed, showing that the absolute and relative speedup ratios for all scenarios of applying two GPUs range from 10.8 to 12.6 and 1.32 to 1.68 times as much as those of a CPU and a single GPU, respectively. The application of a large-scale rainstorm inundation simulation shows the excellent acceleration performance of the model compared to previous research. In addition, the greater the number of computational grids included in the simulation, the more significant the effect on the acceleration computing performance. The proposed model efficiently predicts the spatial variation in the inundation water depth. The simulation results provide guidance for urban rainstorm inundation management, and it improves the time and efficiency of urban flood emergency decision-making.
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