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) and (2) Columbia
(668,000~km) 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.