Publication Date:
2019
Description:
〈b〉The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale〈/b〉〈br〉
Andreas Müller, Willem Deconinck, Christian Kühnlein, Gianmarco Mengaldo, Michael Lange, Nils Wedi, Peter Bauer, Piotr K. Smolarkiewicz, Michail Diamantakis, Sarah-Jane Lock, Mats Hamrud, Sami Saarinen, George Mozdzynski, Daniel Thiemert, Michael Glinton, Pierre Bénard, Fabrice Voitus, Charles Colavolpe, Philippe Marguinaud, Yongjun Zheng, Joris Van Bever, Daan Degrauwe, Geert Smet, Piet Termonia, Kristian P. Nielsen, Bent H. Sass, Jacob W. Poulsen, Per Berg, Carlos Osuna, Oliver Fuhrer, Valentin Clement, Michael Baldauf, Mike Gillard, Joanna Szmelter, Enda O'Brien, Alastair McKinstry, Oisín Robinson, Parijat Shukla, Michael Lysaght, Michał Kulczewski, Milosz Ciznicki, Wojciech Pia̧tek, Sebastian Ciesielski, Marek Błażewicz, Krzysztof Kurowski, Marcin Procyk, Pawel Spychala, Bartosz Bosak, Zbigniew Piotrowski, Andrzej Wyszogrodzki, Erwan Raffin, Cyril Mazauric, David Guibert, Louis Douriez, Xavier Vigouroux, Alan Gray, Peter Messmer, Alexander J. Macfaden, and Nick New〈br〉
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2018-304,2019〈br〉
〈b〉Manuscript under review for GMD〈/b〉 (discussion: open, 0 comments)〈br〉
This paper presents an overview of the ESCAPE project in which weather prediction models are broken down into smaller building blocks called dwarfs. These are optimised for different hardware architectures. New algorithms are developed that are specifically designed for better energy efficiency and improved portability through domain specific languages. Different numerical techniques are compared in terms of energy efficiency and performance on a variety of computing technologies.
Print ISSN:
1991-9611
Electronic ISSN:
1991-962X
Topics:
Geosciences
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