The real challenges for climate and weather modelling on its way to sustained exascale performance: a case study using ICON (v2.6.6)

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发表在:Geoscientific Model Development vol. 18, no. 4 (2025), p. 905
主要作者: Adamidis, Panagiotis
其他作者: Pfister, Erik, Bockelmann, Hendryk, Zobel, Dominik, Jens-Olaf Beismann, Jacob, Marek
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Copernicus GmbH
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100 1 |a Adamidis, Panagiotis  |u Application Support, German Climate Computing Centre (DKRZ), Bundesstraße 45a, 20146 Hamburg, Germany 
245 1 |a The real challenges for climate and weather modelling on its way to sustained exascale performance: a case study using ICON (v2.6.6) 
260 |b Copernicus GmbH  |c 2025 
513 |a Case Study Journal Article 
520 3 |a The weather and climate model ICON (ICOsahedral Nonhydrostatic) is being used in high-resolution climate simulations, in order to resolve small-scale physical processes. The envisaged performance for this task is 1 simulated year per day for a coupled atmosphere–ocean setup at global 1.2 km resolution. The necessary computing power for such simulations can only be found on exascale supercomputing systems. The main question we try to answer in this article is where to find sustained exascale performance, i.e. which hardware (processor type) is best suited for the weather and climate model ICON, and consequently how this performance can be exploited by the model, i.e. what changes are required in ICON's software design so as to utilize exascale platforms efficiently. To this end, we present an overview of the available hardware technologies and a quantitative analysis of the key performance indicators of the ICON model on several architectures. It becomes clear that parallelization based on the decomposition of the spatial domain has reached the scaling limits, leading us to conclude that the performance of a single node is crucial to achieve both better performance and better energy efficiency. Furthermore, based on the computational intensity of the examined kernels of the model it is shown that architectures with higher memory throughput are better suited than those with high computational peak performance. From a software engineering perspective, a redesign of ICON from a monolithic to a modular approach is required to address the complexity caused by hardware heterogeneity and new programming models to make ICON suitable for running on such machines. 
653 |a Modular engineering 
653 |a Software 
653 |a Hardware 
653 |a Microprocessors 
653 |a Bandwidths 
653 |a Weather 
653 |a Redesign 
653 |a Energy efficiency 
653 |a Computer applications 
653 |a Workloads 
653 |a Energy consumption 
653 |a High performance computing 
653 |a Heterogeneity 
653 |a Quantitative analysis 
653 |a Programming languages 
653 |a Spatial memory 
653 |a Climate models 
653 |a Climate and weather 
653 |a Climate 
653 |a Climate science 
653 |a Array processors 
653 |a Design engineering 
653 |a Environmental 
700 1 |a Pfister, Erik  |u Application Support, German Climate Computing Centre (DKRZ), Bundesstraße 45a, 20146 Hamburg, Germany 
700 1 |a Bockelmann, Hendryk  |u Application Support, German Climate Computing Centre (DKRZ), Bundesstraße 45a, 20146 Hamburg, Germany 
700 1 |a Zobel, Dominik  |u Application Support, German Climate Computing Centre (DKRZ), Bundesstraße 45a, 20146 Hamburg, Germany 
700 1 |a Jens-Olaf Beismann  |u NEC Deutschland GmbH, Fritz-Vomfelde-Straße 14, 40547 Düsseldorf, Germany 
700 1 |a Jacob, Marek  |u Research and Development, Deutscher Wetterdienst (DWD), Frankfurter Straße 135, 63067 Offenbach, Germany 
773 0 |t Geoscientific Model Development  |g vol. 18, no. 4 (2025), p. 905 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3167797880/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3167797880/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3167797880/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch