河网水动力模拟的并行JPWSPC算法

Ronghua Liu, Jiahua Wei, Dejun Zhu
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引用次数: 1

摘要

为了缩短复杂河网的水动力模拟时间,提出了一种基于结合点水位预测与校正的并行计算算法。在PJPWSPC算法求解过程的迭代中,各河段的计算可在从属进程中进行,结合点的水位预测和校正在主进程中执行,主进程与从属进程之间的通信采用MPI API。这种平行的河网水动力模拟框架可以应用于环网和支流网。初步分析了单进程计算的河网加速比与平均河段数之间的关系,并通过分析各河段的计算过程和主从进程之间的通信,构造了用于任务调度的分支分组方法。对天然河网进行了两种水动力方案的模拟。该估计方法可用于河网水动力模拟中的分支分组和基于云计算框架(HydroMP)的大规模河网水动力模拟中的多目标计算资源分配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Parallel JPWSPC Algorithm for Hydrodynamic Simulation of River Network
To diminish the hydrodynamic simulation time of complex river network, a parallel computation algorithm based on JPWSPC (joint point water stage prediction and correction) is proposed. In the iteration of solving procedure of PJPWSPC algorithm, computation of each reach can be performed in slave process, and water level prediction and correction of joint point is executed in the master process with the MPI API employed in the communication between master process and slave process. This parallel framework for river network hydrodynamic simulation can be harnessed in the loop network as well as the tributary network. The relation between speed-up ratio and average segment count of river network calculated in single process is Preliminary analyzed and the grouping method of branches for task scheduling is constructed by analyzing the computing process of each reach and communication between master process and slave process. Two hydrodynamic scheme simulation of natural river network is carried out. The estimation method can be employed in the grouping of branched in the hydrodynamic simulation of river network and the multiobjective computing resources allocation in the massive river network hydrodynamic simulation in the cloud computing based framework (HydroMP).
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