GPU-CA模型下的溃坝洪水演进实时模拟与分析

Real-time Simulation and Analysis of Dam-break Flood Routing Based on GPU-CA Model

基于元胞自动机(CA)的局部并行计算特性和统一计算设备架构(CUDA)并行计算架构,提出了GPU-CA的溃坝洪水演进计算模型,重点探讨了溃坝洪水演进元胞自动机模型、GPU模型映射、计算优化、CPU/GPU协同的溃坝洪水演进模拟与分析等关键问题,研发了原型系统,并选择了案例进行初步试验。试验结果表明,在保证溃坝洪水演进模拟结果有效性的情况下,与基于CPU-CA串行计算模式相比,基于GPUCA的溃坝洪水演进模型计算可提高计算效率,加速比随着元胞格网分辨率的提升而增加,当元胞格网的大小为10m时,模型计算效率的加速比可以达到15.9倍,可支持实时溃坝洪水演进模拟分析与风险评估。

Based on the natural similarity between the parallel computing features of cellular automata and the parallel computing architecture of the CUDA, a dam-break flood routing computing model based on GPU-CA is proposed. Key technologies including cellular automata （CA） model of dam- break flood routing, GPU model mapping method, calculation optimization method, and GPU/CPU collaborative implementation for dam-break flood routing simulation and analysis are discussed in de- tail. Finally, a prototype system was developed and a case study region selected for carrying out a pre- liminary experiment. As compared to the CPU-CA model computing, the experimental results showed that the dam-break flood routing computing based on GPU-CA model can greatly improve the comou-ting efficiency, and also ensured the validity of the simulation results. Speedup can be improved by in- creasing the cellular grid resolution. When the cellular grid size was lOm, the speedup of model calcu- lation reached 15.9 times, which can support real-time simulation analysis and risk assessment for dam-break flood routing.