SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics
-
Published:2023-02-08
Issue:3
Volume:16
Page:977-1008
-
ISSN:1991-9603
-
Container-title:Geoscientific Model Development
-
language:en
-
Short-container-title:Geosci. Model Dev.
Author:
Caviedes-Voullième DanielORCID, Morales-Hernández MarioORCID, Norman Matthew R., Özgen-Xian IlhanORCID
Abstract
Abstract. The Simulation EnviRonment for Geomorphology, Hydrodynamics, and Ecohydrology in Integrated form (SERGHEI) is a multi-dimensional, multi-domain,
and multi-physics model framework for environmental and landscape simulation, designed with an outlook towards Earth system modelling. At the core
of SERGHEI's innovation is its performance-portable high-performance parallel-computing (HPC) implementation, built from scratch on the Kokkos portability layer, allowing SERGHEI to be deployed, in a performance-portable fashion, in graphics processing unit (GPU)-based heterogeneous systems. In this work, we explore combinations of MPI and Kokkos using
OpenMP and CUDA backends. In this contribution, we introduce the SERGHEI model framework and present with detail its first operational module
for solving shallow-water equations (SERGHEI-SWE) and its HPC implementation. This module is designed to be applicable to hydrological and
environmental problems including flooding and runoff generation, with an outlook towards Earth system modelling. Its applicability is demonstrated
by testing several well-known benchmarks and large-scale problems, for which SERGHEI-SWE achieves excellent results for the different types of
shallow-water problems. Finally, SERGHEI-SWE scalability and performance portability is demonstrated and evaluated on several TOP500 HPC
systems, with very good scaling in the range of over 20 000 CPUs and up to 256 state-of-the art GPUs.
Publisher
Copernicus GmbH
Reference178 articles.
1. Abderrezzak, K. E. K., Paquier, A., and Mignot, E.:
Modelling flash flood propagation in urban areas using a two-dimensional numerical model, Nat. Hazards, 50, 433–460, https://doi.org/10.1007/s11069-008-9300-0, 2008. a 2. Alexander, F., Almgren, A., Bell, J., Bhattacharjee, A., Chen, J., Colella, P., Daniel, D., DeSlippe, J., Diachin, L., Draeger, E., Dubey, A., Dunning, T., Evans, T., Foster, I., Francois, M., Germann, T., Gordon, M., Habib, S., Halappanavar, M., Hamilton, S., Hart, W., Huang, Z. H., Hungerford, A., Kasen, D., Kent, P. R. C., Kolev, T., Kothe, D. B., Kronfeld, A., Luo, Y., Mackenzie, P., McCallen, D., Messer, B., Mniszewski, S., Oehmen, C., Perazzo, A., Perez, D., Richards, D., Rider, W. J., Rieben, R., Roche, K., Siegel, A., Sprague, M., Steefel, C., Stevens, R., Syamlal, M., Taylor, M., Turner, J., Vay, J.-L., Voter, A. F., Windus, T. L., and Yelick, K.:
Exascale applications: skin in the game, Philos. T. R. Soc. A, 378, 20190056, https://doi.org/10.1098/rsta.2019.0056, 2020. a 3. An, H., Yu, S., Lee, G., and Kim, Y.:
Analysis of an open source quadtree grid shallow water flow solver for flood simulation, Quatern. Int., 384, 118–128, https://doi.org/10.1016/j.quaint.2015.01.032, 2015. a 4. Arpaia, L. and Ricchiuto, M.:
r-adaptation for Shallow Water flows: conservation, well balancedness, efficiency, Comput. Fluids, 160, 175–203, https://doi.org/10.1016/j.compfluid.2017.10.026, 2018. a 5. Artigues, V., Kormann, K., Rampp, M., and Reuter, K.:
Evaluation of performance portability frameworks for the implementation of a particle-in-cell code, Concurr. Comput.-Pract. E., 32, https://doi.org/10.1002/cpe.5640, 2019. a
Cited by
22 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|