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

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.

Toward Street‐Level Nowcasting of Flash Floods Impacts Based on HPC Hydrodynamic Modeling at the Watershed Scale and High‐Resolution Weather Radar Data

“…In the future, it would be interesting to extend this modeling approach to bigger watersheds to test the overall run time, even considering more HPC‐enabled solutions to enhance the computational efficiency (Caviedes‐Voullième et al., 2023; Morales‐Hernández et al., 2021; Sharifian et al., 2023).…”

“…However, nowadays, the use of high‐performance computing (HPC) is common and several 2D‐SWEs codes are developed using parallelization schemes. As a consequence, approaches based on both the message passing interface (MPI) or open multi‐processing, compatible with clusters composed of several central processing units and the general purpose graphics processing unit have been shown highly efficient, leading to a drastic reduction of the computational times (Buttinger‐Kreuzhuber et al., 2022; Carlotto et al., 2021; Caviedes‐Voullième et al., 2023; Dazzi et al., 2018; Morales‐Hernández et al., 2021; Noh et al., 2018; Sanders & Schubert, 2019; Vacondio et al., 2017; X. Xia et al., 2019).…”

Influence of building collapse on pluvial and fluvial flood inundation of metro stations in central Shanghai

“…In this work, the flooding of the Huangpu district is simulated with the SERGHEI-SWE model (Caviedes-Voullième et al, 2023). SERGHEI-SWE is an open-source, high-performance hydrodynamic model.…”

“…GPU computing have dramatically reduced the computational cost for large-scale hydrodynamic simulations. Caviedes-Voullième et al (2023) has shown that using SERGHEI-SWE, for a computational domain with 0.5 million grid cells, hydrodynamic simulations on a workstation GPU remain faster than that on 128 CPU threads. Thus, SERGHEI-SWE with GPU computing capability is an ideal tool for completing massive flood simulation scenarios (e.g., the multiple random building collapse scenarios used in this study) within an acceptable time frame.…”

“…The SERGHEI-SWE model is an open-sourced software (Caviedes-Voullième et al, 2023). The topography, building and road layout data of the study area are all publicly available.…”