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Computational Flood Modeling with UPC Architecture

机译:使用UPC架构进行计算洪水建模

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摘要

Demand for effective flood modeling and forecasting based on the two-dimensional shallow water equations has increased due to uncertainties with climate changes and the need for further accuracy in the urbanized environment. In this study, an alternative parallel computing architecture is presented that uses the Unified Parallel C (UPC) architecture, which combines the respective advantages of message passing interface (MPI) scalability with the direct memory access of OpenMP. A second-order Godunov-type monotone upstream scheme flood model, called ParaFlood2D, is developed using UPC as the first approach. The computational efficiency of ParaFlood2D is investigated with two cases of flood wave propagation on shared-memory and distributed-memory systems. In both cases, the simulation results demonstrate reasonably good accuracy when compared with the respective analytical solutions. At the same time, the obtained speed-up performance of UPC is generally more favorable when compared with that of MPI and OpenMP in their respective basic designs. Overall, the study indicates that UPC parallel architecture can be a viable alternative for large-scale flood modeling simulations.
机译:由于气候变化的不确定性以及对城市化环境的进一步准确性的需求,对基于二维浅水方程的有效洪水建模和预报的需求增加了。在这项研究中,提出了使用统一并行C(UPC)架构的替代并行计算架构,该架构结合了消息传递接口(MPI)可伸缩性和OpenMP的直接内存访问的各自优点。使用UPC作为第一种方法,开发了称为ParaFlood2D的二阶Godunov型单调上游方案洪水模型。通过在共享内存和分布式内存系统上泛洪波传播的两种情况,研究了ParaFlood2D的计算效率。在两种情况下,与相应的分析解决方案相比,仿真结果均显示出相当不错的精度。同时,在各自的基本设计中,与MPI和OpenMP相比,UPC获得的加速性能通常更有利。总体而言,研究表明,UPC并行体系结构可以作为大规模洪水建模仿真的可行替代方案。

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