Parallel Distributed Hydrology Soil Vegetation Model (DHSVM) using global arrays. (December 2019)

• Record Type: Journal Article
• Authors: Perkins, William A.; Duan, Zhuoran; Sun, Ning; Wigmosta, Mark S.; Richmond, Marshall C.; Chen, Xiaodong; Leung, L. Ruby
• Is Part Of: Environmental modelling & software. Volume 122(2019)
• Publication Date: 2019-12
• Subjects: Watershed hydrology -- Distributed hydrology model -- High-performance computing -- Parallel computing -- Columbia River basin -- Clearwater River basin; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2019.104533
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The Distributed Hydrology Soil Vegetation Model (DHSVM) code was parallelized for distributed memory computers using the Global Arrays (GA) programming model. To analyze parallel performance, DHSVM was used to simulate the hydrology in two river basins of significant size located in the northwest continental United States and southwest Canada at 90 m resolution: the (1) Clearwater (25, 000 km 2 ) and (2) Columbia (668, 000 km 2 ) River basins. Meteorological forcing applied to both basins was dynamically down-scaled from a regional reanalysis using the Weather Research and Forecasting (WRF) model and read into DHSVM as 2D maps for each time step. Parallel code speedup was significant. Run times for 1-year simulations were reduced by an order of magnitude for both test basins. A maximum parallel speedup of 105 was attained with 480 processors while simulating the Columbia River basin. Speedup was limited by input-dominated tasks, particularly the input of meteorological forcing data. Highlights: The well established Distributed Hydrology Vegetation Soil Model (DHSVM) was parallelized for distributed memory platforms. The Global Arrays (GA) partitioned global address space (PGAS) library for distributed arrays was used for inter-process communication. Parallel DHSVM was used to simulate the hydrology of two large river basins, with areas of 25, 000 and 668, 000 square kilometers, at a 90 meter resolution. Maximum parallel speed up of 105 was measured using 480 processors with the Columbia River basin simulation.