Operational numerical weather prediction with ICON on GPUs (version 2024.10)

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Authors: Xavier Lapillonne, Daniel Hupp, Fabian Gessler, André Walser, Andreas Pauling, Annika Lauber, Benjamin Cumming, Carlos Osuna, Christoph Müller, Claire Merker, Daniel Leuenberger, David Leutwyler
+15 more Dmitry Alexeev, Gabriel Vollenweider, Guillaume Van Parys, Jonas Jucker, Lukas Jansing, M. Arpagaus, Marco Induni, Marek Jacob, Matthias Kraushaar, Mikael Stellio, Remo Dietlicher, T. C. Schulthess, Victoria Cherkas, William Sawyer, et al.
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Abstract

Numerical weather prediction and climate models require continuous adaptation to take advantage of advances in high-performance computing hardware. This paper presents the port of the ICON model to GPUs using OpenACC compiler directives for numerical weather prediction applications. In the context of an end-to-end operational forecast application, we adopted a full-port strategy: the entire workflow, from physical parameterizations to data assimilation, was analyzed and ported to GPUs as needed. Performance tuning and mixed-precision optimization yield a 5.5x speed-up compared to the CPU baseline in a socket-to-socket comparison. The ported ICON model meets strict requirements for time-to-solution and meteorological quality, in order for MeteoSwiss to be the first national weather service to run ICON operationally on GPUs with its ICON-CH1-EPS and ICON-CH2-EPS ensemble forecasting systems. We discuss key performance strategies, operational challenges, and the broader implications of transitioning community models to GPU-based platforms.

Fields of Study & Subjects

Parallel Computing and Optimization Techniques Meteorological Phenomena and Simulations Computer Graphics and Visualization Techniques

Publication details

Journal / source
Repository for Publications and Research Data (ETH Zurich)
Publication date
23 January 2026
Language
EN