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Article: Dynamic parallelization of hydrological model simulations
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TitleDynamic parallelization of hydrological model simulations
 
AuthorsLi, T2 1
Wang, G2
Chen, J1
Wang, H2
 
KeywordsBasin width function
Digital drainage network
Domain decomposition
Dynamic parallelization
Master-slave paradigm
Modified binary-tree codification
 
Issue Date2011
 
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/envsoft
 
CitationEnvironmental Modelling And Software, 2011, v. 26 n. 12, p. 1736-1746 [How to Cite?]
DOI: http://dx.doi.org/10.1016/j.envsoft.2011.07.015
 
AbstractThis 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 etal. (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. © 2011 Elsevier Ltd.
 
ISSN1364-8152
2013 Impact Factor: 4.538
2013 SCImago Journal Rankings: 2.061
 
DOIhttp://dx.doi.org/10.1016/j.envsoft.2011.07.015
 
ISI Accession Number IDWOS:000298270300031
Funding AgencyGrant Number
National Key Basic Research Program of China2007CB714100
2011CB409901
Ministry of Water Resources of China200901016
200901019
Funding Information:

This research was supported by the National Key Basic Research Program of China (Grant No. 2007CB714100, 2011CB409901) and the Non-profit Fund Program of the Ministry of Water Resources of China (Grant No. 200901016, 200901019). The authors are grateful for the constructive comments and suggestions from two anonymous reviewers and the Editor, Dr. Rizzoli.

 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorLi, T
 
dc.contributor.authorWang, G
 
dc.contributor.authorChen, J
 
dc.contributor.authorWang, H
 
dc.date.accessioned2011-09-23T05:44:59Z
 
dc.date.available2011-09-23T05:44:59Z
 
dc.date.issued2011
 
dc.description.abstractThis 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 etal. (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. © 2011 Elsevier Ltd.
 
dc.description.naturepostprint
 
dc.identifier.citationEnvironmental Modelling And Software, 2011, v. 26 n. 12, p. 1736-1746 [How to Cite?]
DOI: http://dx.doi.org/10.1016/j.envsoft.2011.07.015
 
dc.identifier.doihttp://dx.doi.org/10.1016/j.envsoft.2011.07.015
 
dc.identifier.epage1746
 
dc.identifier.hkuros207996
 
dc.identifier.isiWOS:000298270300031
Funding AgencyGrant Number
National Key Basic Research Program of China2007CB714100
2011CB409901
Ministry of Water Resources of China200901016
200901019
Funding Information:

This research was supported by the National Key Basic Research Program of China (Grant No. 2007CB714100, 2011CB409901) and the Non-profit Fund Program of the Ministry of Water Resources of China (Grant No. 200901016, 200901019). The authors are grateful for the constructive comments and suggestions from two anonymous reviewers and the Editor, Dr. Rizzoli.

 
dc.identifier.issn1364-8152
2013 Impact Factor: 4.538
2013 SCImago Journal Rankings: 2.061
 
dc.identifier.issue12
 
dc.identifier.scopuseid_2-s2.0-84855511358
 
dc.identifier.spage1736
 
dc.identifier.urihttp://hdl.handle.net/10722/139104
 
dc.identifier.volume26
 
dc.languageeng
 
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/envsoft
 
dc.publisher.placeUnited Kingdom
 
dc.relation.ispartofEnvironmental Modelling and Software
 
dc.relation.referencesReferences in Scopus
 
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in Environmental Modelling & Software. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Environmental Modelling & Software, 2011, v. 26 n. 12, p. 1736-1746. DOI: 10.1016/j.envsoft.2011.07.015
 
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License
 
dc.subjectBasin width function
 
dc.subjectDigital drainage network
 
dc.subjectDomain decomposition
 
dc.subjectDynamic parallelization
 
dc.subjectMaster-slave paradigm
 
dc.subjectModified binary-tree codification
 
dc.titleDynamic parallelization of hydrological model simulations
 
dc.typeArticle
 
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<description.abstract>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 etal. (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. &#169; 2011 Elsevier Ltd.</description.abstract>
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Author Affiliations
  1. The University of Hong Kong
  2. Tsinghua University