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 20g000 CPUs and up to 256 state-of-the art GPUs.
| Original language | English |
|---|---|
| Pages (from-to) | 977-1008 |
| Number of pages | 32 |
| Journal | Geoscientific Model Development |
| Volume | 16 |
| Issue number | 3 |
| DOIs | |
| State | Published - Feb 8 2023 |
Funding
The authors gratefully acknowledge the Earth System Modelling Project (ESM) for supporting this work by providing computing time on the ESM partition of the JUWELS supercomputer at the Jülich Supercomputing Centre (JSC) through the compute time project Runoff Generation and Surface Hydrodynamics across Scales with the SERGHEI model (RUGSHAS), project no. 22686. This work used resources of the National Energy Research Scientific Computing Center (NERSC), a US Department of Energy, Office of Science, user facility operated under contract no. DE-AC02-05CH11231. This research was also supported by the US Air Force Numerical Weather Modelling programme and used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is a US Department of Energy (DOE) Office of Science User Facility.