4.7 Article

SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics

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GEOSCIENTIFIC MODEL DEVELOPMENT
卷 16, 期 3, 页码 977-1008

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COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/gmd-16-977-2023

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SERGHEI is a multi-dimensional, multi-domain, and multi-physics model framework for environmental and landscape simulation, with performance-portable high-performance parallel-computing implementation. One of its modules, SERGHEI-SWE, is designed for solving shallow-water equations and applicable to hydrological and environmental problems. The module achieves excellent results for various shallow-water problems.
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 coreof 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 usingOpenMP and CUDA backends. In this contribution, we introduce the SERGHEI model framework and present with detail its first operational modulefor solving shallow-water equations (SERGHEI-SWE) and its HPC implementation. This module is designed to be applicable to hydrological andenvironmental problems including flooding and runoff generation, with an outlook towards Earth system modelling. Its applicability is demonstratedby testing several well-known benchmarks and large-scale problems, for which SERGHEI-SWE achieves excellent results for the different types ofshallow-water problems. Finally, SERGHEI-SWE scalability and performance portability is demonstrated and evaluated on several TOP500 HPCsystems, with very good scaling in the range of over 20 000 CPUs and up to 256 state-of-the art GPUs.

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