Parallel Distributed Hydrology Soil Vegetation Model (DHSVM) using global arrays
Abstract
The Distributed Hydrology Soil Vegetation Model (DHSVM) code was parallelized for distributed memory computers using Global Arrays (GA). To analyze parallel performance, DHSVM was used to simulate two significantly sized river basins located in northwest continental United States and southwest Canada at 90~m resolution: (1) Clearwater (25,000~km2) and (2) Columbia (668,000~km2). Meteorological forcing applied to both basins was dynamically down-scaled from a global circulation model using the Weather Research and Forecasting (WRF) model and read into DHSVM as 2D maps each time step. We report parallel code speed up was significant. Run times for 1-year simulations were reduced by an order of magnitude for both test basins. A maximum speed up of 105 was attained with 480 processors while simulating the Columbia basin. Speed up was limited by input dominated tasks, particularly the input of meteorological forcing data.
- Authors:
-
[1];
[1];
[1];
[2]
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- BATTELLE (PACIFIC NW LAB)
- Publication Date:
- Research Org.:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Water Power Technologies Office; USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1595308
- Alternate Identifier(s):
- OSTI ID: 1574549
- Report Number(s):
- PNNL-SA-141147
Journal ID: ISSN 1364-8152
- Grant/Contract Number:
- AC05-76RL01830; RC-2546; AC02-05CH11231
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Environmental Modelling and Software
- Additional Journal Information:
- Journal Volume: 122; Journal ID: ISSN 1364-8152
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; watershed hydrology; distributed hydrologic model; dynamic downscaling; high performance computing; parallel computing; global arrays; message passing interface; Columbia River basin; Clearwater River basin
Citation Formats
Perkins, William A., Duan, Zhuoran, Sun, Ning, Wigmosta, Mark S., Richmond, Marshall C., Chen, Xiaodong, and Leung, Lai-Yung. Parallel Distributed Hydrology Soil Vegetation Model (DHSVM) using global arrays. United States: N. p., 2019.
Web. doi:10.1016/j.envsoft.2019.104533.
Perkins, William A., Duan, Zhuoran, Sun, Ning, Wigmosta, Mark S., Richmond, Marshall C., Chen, Xiaodong, & Leung, Lai-Yung. Parallel Distributed Hydrology Soil Vegetation Model (DHSVM) using global arrays. United States. https://doi.org/10.1016/j.envsoft.2019.104533
Perkins, William A., Duan, Zhuoran, Sun, Ning, Wigmosta, Mark S., Richmond, Marshall C., Chen, Xiaodong, and Leung, Lai-Yung. Mon .
"Parallel Distributed Hydrology Soil Vegetation Model (DHSVM) using global arrays". United States. https://doi.org/10.1016/j.envsoft.2019.104533. https://www.osti.gov/servlets/purl/1595308.
@article{osti_1595308,
title = {Parallel Distributed Hydrology Soil Vegetation Model (DHSVM) using global arrays},
author = {Perkins, William A. and Duan, Zhuoran and Sun, Ning and Wigmosta, Mark S. and Richmond, Marshall C. and Chen, Xiaodong and Leung, Lai-Yung},
abstractNote = {The Distributed Hydrology Soil Vegetation Model (DHSVM) code was parallelized for distributed memory computers using Global Arrays (GA). To analyze parallel performance, DHSVM was used to simulate two significantly sized river basins located in northwest continental United States and southwest Canada at 90~m resolution: (1) Clearwater (25,000~km2) and (2) Columbia (668,000~km2). Meteorological forcing applied to both basins was dynamically down-scaled from a global circulation model using the Weather Research and Forecasting (WRF) model and read into DHSVM as 2D maps each time step. We report parallel code speed up was significant. Run times for 1-year simulations were reduced by an order of magnitude for both test basins. A maximum speed up of 105 was attained with 480 processors while simulating the Columbia basin. Speed up was limited by input dominated tasks, particularly the input of meteorological forcing data.},
doi = {10.1016/j.envsoft.2019.104533},
journal = {Environmental Modelling and Software},
number = ,
volume = 122,
place = {United States},
year = {Mon Sep 30 00:00:00 EDT 2019},
month = {Mon Sep 30 00:00:00 EDT 2019}
}
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