Parallel Computer Architecture: A Hardware/Software Approach
Parallel Computer Architecture: A Hardware/Software Approach
Parallel Shuffled Complex Evolution Algorithm for Calibration of Hydrological Models
HPCS '06 Proceedings of the 20th International Symposium on High-Performance Computing in an Advanced Collaborative Environment
Scientific Parallel Computing
Parallelisation of a distributed hydrologic model
International Journal of Computer Applications in Technology
A modified binary tree codification of drainage networks to support complex hydrological models
Computers & Geosciences
A parallelization framework for calibration of hydrological models
Environmental Modelling & Software
Parallelization of a hydrological model using the message passing interface
Environmental Modelling & Software
A layered approach to parallel computing for spatially distributed hydrological modeling
Environmental Modelling & Software
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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.