Dynamic parallelization of hydrological model simulations
Dynamic parallelization of hydrological model simulations
复制标题
水文模型模拟的动态并行化
DOI：
10.1016/j.envsoft.2011.07.015
复制
发表时间：
2011-12
期刊：
影响因子：
--
通讯作者：
Wang, Hao
中科院分区：
文献类型：
--
作者：
Li, Tiejian;Wang, Guangqian;Chen, Ji;Wang, Hao
本文介绍了一种用于水文模型模拟的动态并行算法的开发。该算法由河网分解方法和改进的主从模式两部分组成。采用分解法将流域河网划分为大量的子流域，并采用增强的主从范式，通过消息传递接口（MPI）和C++语言实现了这种新的动态流域分解方法的功能。该算法的目标是平衡计算负载，提高流域水文模拟并行计算的加速比和效率。本文采用了一种改进的二叉树编码方法开发的李等人。（2010）对排水网络进行编码，并使用流域宽度函数来估计可能的最大并行加速和相关效率。以数字黄河模型为例，将该算法应用于北方岔巴沟流域。应用结果表明，新算法能有效地将仿真任务动态分配到计算进程，并行加速比和效率与使用盆宽函数所作的估计相当。
This paper introduces the development of a dynamic parallel algorithm for conducting hydrological model simulations. This new algorithm consists of a river network decomposition method and an enhanced master–slave paradigm. The decomposition method is used to divide a basin river network into a large number of subbasins, and the enhanced master–slave paradigm is adopted to realize the function of this new dynamic basin decomposition method through using the Message-Passing Interface (MPI) and C++ language. This new algorithm aims to balance computation load and then to achieve a higher speedup and efficiency of parallel computing in hydrological simulation for the river basins which are delineated by high-resolution drainage networks. This paper uses a modified binary-tree codification method developed by Li et al. (2010) to code drainage networks, and the basin width function to estimate the possible maximum parallel speedup and the associated efficiency. As a case study, with a hydrological model, the Digital Yellow River Model, this new dynamic parallel algorithm is applied to the Chabagou basin in northern China. The application results reveal that the new algorithm is efficient in the dynamic dispatching of simulation tasks to computing processes, and that the parallel speedup and efficiency are comparable with the estimations made by using the basin width function.
登录
查看更多内容
DOI：
10.1016/j.cageo.2010.04.009
发表时间：
2010-11
期刊：
Comput. Geosci.
影响因子：
--
作者：
Tiejian Li;Guangqian Wang;Ji Chen
通讯作者：
Tiejian Li;Guangqian Wang;Ji Chen
影响因子：
2.8
作者：
Guangqian Wang;Baosheng Wu;Tiejian Li
通讯作者：
Guangqian Wang;Baosheng Wu;Tiejian Li
DOI：
--
发表时间：
2007-12
期刊：
--
影响因子：
--
作者：
N. Muttil;S. Liong;O. Nesterov
通讯作者：
N. Muttil;S. Liong;O. Nesterov
影响因子：
8.9
作者：
O. Kolditz;Y. Du;C. Bürger;J. Delfs;D. Kuntz;M. Beinhorn;M. Hess;W. Wang;B. van der Grift;C. te Stroet
通讯作者：
O. Kolditz;Y. Du;C. Bürger;J. Delfs;D. Kuntz;M. Beinhorn;M. Hess;W. Wang;B. van der Grift;C. te Stroet
影响因子：
6.4
作者：
T. Apostolopoulos;K. Georgakakos
通讯作者：
T. Apostolopoulos;K. Georgakakos