Xavier Lapillonne, Daniel Hupp, Fabian Gessler, André Walser, Andreas Pauling, Annika Lauber, Benjamin Cumming, Carlos Osuna, Christoph Müller, Claire Merker, Daniel Leuenberger, David Leutwyler, Dmitry Alexeev, Gabriel Vollenweider, Guillaume Van Parys, Jonas Jucker, Lukas Jansing, M. Arpagaus, Marco Induni, Marek Jacob, Matthias Kraushaar, Michael Jähn, Mikael Stellio, Oliver Fuhrer, Petra Baumann, P. Steiner, P. Kaufmann, Remo Dietlicher, Ralf Müller, Sergey S. Kosukhin, T. C. Schulthess, Ulrich Schättler, Victoria Cherkas, William Sawyer
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 5.5× 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.