Parallelisation of storage cell flood models using OpenMP |
| |
| Authors: | Jeffrey Neal Timothy Fewtrell Mark Trigg |
| |
| Affiliation: | 1. Institute of Fluid Mechanics and Environmental Physics in Civil Engineering, Leibniz Universität Hannover, Appelstrasse 9a, 30167 Hannover, Germany;2. Institute for Technical and Scientific Hydrology (itwh GmbH), Engelbosteler Damm 22, 30167 Hannover, Germany;1. NASA Jet Propulsion Laboratory, Caltech, Pasadena, CA 91109, USA;2. Cabot Institute and School of Geographical Sciences, Bristol BS8 1SS, UK;1. Monash Infrastructure Research Institute, Department of Civil Engineering, Monash University, Clayton 3800, VIC, Australia;2. School of Civil and Environmental Engineering, University of New South Wales Sydney, NSW 2052, Australia;3. Department of Environmental Engineering, DTU Environment, Technical University of Denmark, Miljøvej, Building 113, 2800Kgs., Lyngby, Denmark;4. Swiss Federal Institute of Aquatic Science & Technology (Eawag), Überlandstrasse 133, Dübendorf 8600, Switzerland;5. Institute of Environmental Engineering, ETH Zürich, 8093 Zürich, Switzerland |
| |
| Abstract: | This paper describes the implementation and benchmarking of a parallel version of the LISFLOOD-FP hydraulic model based on the OpenMP Application Programming Interface. The motivation behind the study was that reducing model run time through parallelisation would increase the utility of such models by expanding the domains over which they can be practically implemented, allowing previously inaccessible scientific questions to be addressed. Parallel speedup was calculated for 13 models distributed over seven study sites and implemented on one, two, four and in selected cases eight processor cores. The models represent a range of previous applications from large area, coarse resolution models of the Amazon, to fine resolution models of urban areas, to orders of magnitude smaller models of rural floodplains. Parallel speedups were greater for larger model domains, especially for models with over 0.2–0.4 million cells where parallel efficiencies of up to 0.75 on four and eight cores were achieved. A key advantage of using OpenMP and an explicit rather than implicit model was the ease of implementation and minimal code changes required to run simulations in parallel. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
