Articles | Volume 15, issue 18
https://doi.org/10.5194/gmd-15-6985-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-6985-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
16 Sep 2022
Development and technical paper |
| 16 Sep 2022
| 16 Sep 2022
The ICON-A model for direct QBO simulations on GPUs (version icon-cscs:baf28a514)
Marco A. Giorgetta
CORRESPONDING AUTHOR
Max-Planck-Institut für Meteorologie, Hamburg, Germany
William Sawyer
Centro Svizzero di Calcolo Scientifico, Lugano, Switzerland
Xavier Lapillonne
Bundesamt für Meteorologie und Klimatologie MeteoSchweiz, Zürich-Flughafen, Switzerland
Panagiotis Adamidis
Deutsches Klimarechenzentrum, Hamburg, Germany
Dmitry Alexeev
NVIDIA, Zürich, Switzerland
Valentin Clément
Center for Climate Systems Modeling, ETH, Zürich, Switzerland
Remo Dietlicher
Bundesamt für Meteorologie und Klimatologie MeteoSchweiz, Zürich-Flughafen, Switzerland
Jan Frederik Engels
Deutsches Klimarechenzentrum, Hamburg, Germany
Monika Esch
Max-Planck-Institut für Meteorologie, Hamburg, Germany
Henning Franke
Max-Planck-Institut für Meteorologie, Hamburg, Germany
International Max Planck Research School on Earth System Modelling, Hamburg, Germany
Claudia Frauen
Deutsches Klimarechenzentrum, Hamburg, Germany
Walter M. Hannah
Lawrence Livermore National Laboratory, Livermore, USA
Benjamin R. Hillman
Sandia National Laboratories, Albuquerque, USA
Luis Kornblueh
Max-Planck-Institut für Meteorologie, Hamburg, Germany
Philippe Marti
Center for Climate Systems Modeling, ETH, Zürich, Switzerland
Matthew R. Norman
Oak Ridge National Laboratory, Oak Ridge, USA
Robert Pincus
Lamont-Doherty Earth Observatory, Columbia University, Palisades, USA
Sebastian Rast
Max-Planck-Institut für Meteorologie, Hamburg, Germany
Daniel Reinert
Deutscher Wetterdienst, Offenbach, Germany
Reiner Schnur
Max-Planck-Institut für Meteorologie, Hamburg, Germany
Uwe Schulzweida
Max-Planck-Institut für Meteorologie, Hamburg, Germany
Bjorn Stevens
Max-Planck-Institut für Meteorologie, Hamburg, Germany
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Cited
10 citations as recorded by crossref.
- Changes of tropical gravity waves and the quasi‐biennial oscillation in storm‐resolving simulations of idealized global warming H. Franke et al. 10.1002/qj.4534
- Improving scalability of Earth system models through coarse-grained component concurrency – a case study with the ICON v2.6.5 modelling system L. Linardakis et al. 10.5194/gmd-15-9157-2022
- Deep Learning Based Cloud Cover Parameterization for ICON A. Grundner et al. 10.1029/2021MS002959
- Pace v0.2: a Python-based performance-portable atmospheric model J. Dahm et al. 10.5194/gmd-16-2719-2023
- Accelerating Lagrangian transport simulations on graphics processing units: performance optimizations of Massive-Parallel Trajectory Calculations (MPTRAC) v2.6 L. Hoffmann et al. 10.5194/gmd-17-4077-2024
- Multiresolution approximation for shallow water equations using summation-by-parts finite differences I. Tretyak et al. 10.1515/rnam-2023-0030
- ICON-Sapphire: simulating the components of the Earth system and their interactions at kilometer and subkilometer scales C. Hohenegger et al. 10.5194/gmd-16-779-2023
- Accelerating atmospheric physics parameterizations using graphics processing units D. Abdi & I. Jankov 10.1177/10943420241238711
- AI-empowered next-generation multiscale climate modelling for mitigation and adaptation V. Eyring et al. 10.1038/s41561-024-01527-w
- Earth system modeling on modular supercomputing architecture: coupled atmosphere–ocean simulations with ICON 2.6.6-rc A. Bishnoi et al. 10.5194/gmd-17-261-2024
10 citations as recorded by crossref.
- Changes of tropical gravity waves and the quasi‐biennial oscillation in storm‐resolving simulations of idealized global warming H. Franke et al. 10.1002/qj.4534
- Improving scalability of Earth system models through coarse-grained component concurrency – a case study with the ICON v2.6.5 modelling system L. Linardakis et al. 10.5194/gmd-15-9157-2022
- Deep Learning Based Cloud Cover Parameterization for ICON A. Grundner et al. 10.1029/2021MS002959
- Pace v0.2: a Python-based performance-portable atmospheric model J. Dahm et al. 10.5194/gmd-16-2719-2023
- Accelerating Lagrangian transport simulations on graphics processing units: performance optimizations of Massive-Parallel Trajectory Calculations (MPTRAC) v2.6 L. Hoffmann et al. 10.5194/gmd-17-4077-2024
- Multiresolution approximation for shallow water equations using summation-by-parts finite differences I. Tretyak et al. 10.1515/rnam-2023-0030
- ICON-Sapphire: simulating the components of the Earth system and their interactions at kilometer and subkilometer scales C. Hohenegger et al. 10.5194/gmd-16-779-2023
- Accelerating atmospheric physics parameterizations using graphics processing units D. Abdi & I. Jankov 10.1177/10943420241238711
- AI-empowered next-generation multiscale climate modelling for mitigation and adaptation V. Eyring et al. 10.1038/s41561-024-01527-w
- Earth system modeling on modular supercomputing architecture: coupled atmosphere–ocean simulations with ICON 2.6.6-rc A. Bishnoi et al. 10.5194/gmd-17-261-2024
Latest update: 23 Nov 2024
Short summary
This work presents a first version of the ICON atmosphere model that works not only on CPUs, but also on GPUs. This GPU-enabled ICON version is benchmarked on two GPU machines and a CPU machine. While the weak scaling is very good on CPUs and GPUs, the strong scaling is poor on GPUs. But the high performance of GPU machines allowed for first simulations of a short period of the quasi-biennial oscillation at very high resolution with explicit convection and gravity wave forcing.
This work presents a first version of the ICON atmosphere model that works not only on CPUs, but...
