基于多GPU数值框架的流域地表径流过程数值模拟  

Numerical simulation of surface runoff process based on multi-GPU numerical framework

作　　者：冯新政 张大伟[1] 徐海卿[1] 鞠琴[2,3] FENG Xinzheng;ZHANG Dawei;XU Haiqing;JU Qin(China Institute of Water Resources and Hydropower Research,Beijing 100038,China;The National Key Laboratory of Water Disaster Prevention,Hohai University,Nanjing 210098,China;National Cooperative Innovation Center for Water Safety&Hydro Science,Nanjing 210098,China)

机构地区：[1]中国水利水电科学研究院,北京100038 [2]河海大学水灾害防御全国重点实验室,南京210098 [3]水安全与水科学协同创新中心,南京210098

出　　处：《南水北调与水利科技（中英文）》2024年第1期48-55,共8页South-to-North Water Transfers and Water Science & Technology

基　　金：国家重点研发计划项目(2022YFC3005501);水利部重大科技项目(SKS-2022007);中国水科院科研专项(WH0145B022021;WH0145B042021;JZ110145B0022023)。

摘　　要：与传统概念性水文模型相比,二维水动力模型可提供更丰富的流域地表水力要素信息,但是计算耗时太长的问题限制其推广应用,提升二维水动力模型的计算效率成为当前数字孪生流域建设工作中的关键技术难题之一。采用基于Godunov格式的有限体积法离散完整二维浅水方程组建立模型,通过消息传递接口(message passing interface,MPI)与统一计算设备架构(compute unified device architecture,CUDA)相结合的技术实现了基于多图形处理器(graphics processing unit,GPU)的高性能加速计算,采用理想算例和真实流域算例验证模型具有较好的数值计算精度,其中,理想算例中洪峰的相对误差为0.011%,真实流域算例中洪峰的相对误差为2.98%。选取宝盖寺流域为研究对象,分析不同单元分辨率下模型的加速效果,结果表明:在5、2、1 m分辨率下,使用8张GPU卡计算获得的加速比分别为1.58、3.92、5.77,单元分辨率越高,即单元数越多,多GPU卡的加速效果越明显。基于多GPU的水动力模型加速潜力巨大,可为数字孪生流域建设提供有力技术支撑。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 t

关 键 词：水动力模型 地表径流 多GPU Godunov格式 加速比 

分 类 号：TV131.2[水利工程—水力学及河流动力学]