The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale
<p>In the simulation of complex multi-scale flows arising in weather and climate modelling, one of the biggest challenges is to satisfy strict service requirements in terms of time to solution and to satisfy budgetary constraints in terms of energy to solution, without compromising the accurac...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2019-10-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://www.geosci-model-dev.net/12/4425/2019/gmd-12-4425-2019.pdf |
| _version_ | 1828406531460169728 |
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| author | A. Müller W. Deconinck C. Kühnlein G. Mengaldo M. Lange N. Wedi P. Bauer P. K. Smolarkiewicz M. Diamantakis S.-J. Lock M. Hamrud S. Saarinen G. Mozdzynski D. Thiemert M. Glinton P. Bénard F. Voitus C. Colavolpe P. Marguinaud Y. Zheng J. Van Bever D. Degrauwe G. Smet P. Termonia P. Termonia K. P. Nielsen B. H. Sass J. W. Poulsen P. Berg C. Osuna O. Fuhrer V. Clement M. Baldauf M. Gillard J. Szmelter E. O'Brien A. McKinstry O. Robinson P. Shukla M. Lysaght M. Kulczewski M. Ciznicki W. Piątek S. Ciesielski M. Błażewicz K. Kurowski M. Procyk P. Spychala B. Bosak Z. P. Piotrowski A. Wyszogrodzki E. Raffin C. Mazauric D. Guibert L. Douriez X. Vigouroux A. Gray P. Messmer A. J. Macfaden N. New |
| author_facet | A. Müller W. Deconinck C. Kühnlein G. Mengaldo M. Lange N. Wedi P. Bauer P. K. Smolarkiewicz M. Diamantakis S.-J. Lock M. Hamrud S. Saarinen G. Mozdzynski D. Thiemert M. Glinton P. Bénard F. Voitus C. Colavolpe P. Marguinaud Y. Zheng J. Van Bever D. Degrauwe G. Smet P. Termonia P. Termonia K. P. Nielsen B. H. Sass J. W. Poulsen P. Berg C. Osuna O. Fuhrer V. Clement M. Baldauf M. Gillard J. Szmelter E. O'Brien A. McKinstry O. Robinson P. Shukla M. Lysaght M. Kulczewski M. Ciznicki W. Piątek S. Ciesielski M. Błażewicz K. Kurowski M. Procyk P. Spychala B. Bosak Z. P. Piotrowski A. Wyszogrodzki E. Raffin C. Mazauric D. Guibert L. Douriez X. Vigouroux A. Gray P. Messmer A. J. Macfaden N. New |
| author_sort | A. Müller |
| collection | DOAJ |
| description | <p>In the simulation of complex multi-scale flows arising in weather and climate modelling, one of the biggest challenges is to satisfy strict service requirements in terms of time to solution and to satisfy budgetary constraints in terms of energy to solution, without compromising the accuracy and stability of the application. These simulations require algorithms that minimise the energy footprint along with the time required to produce a solution, maintain the physically required level of accuracy, are numerically stable, and are resilient in case of hardware failure.</p>
<p>The European Centre for Medium-Range Weather Forecasts (ECMWF) led the ESCAPE (Energy-efficient Scalable Algorithms for Weather Prediction at Exascale) project, funded by Horizon 2020 (H2020) under the FET-HPC (Future and Emerging Technologies in High Performance Computing) initiative. The goal of ESCAPE was to develop a sustainable strategy to evolve weather and climate<span id="page4426"/> prediction models to next-generation computing technologies. The project partners incorporate the expertise of leading European regional forecasting consortia, university research, experienced high-performance computing centres, and hardware vendors.</p>
<p>This paper presents an overview of the ESCAPE strategy: (i) identify domain-specific key algorithmic motifs in weather prediction and climate models (which we term Weather & Climate Dwarfs), (ii) categorise them in terms of computational and communication patterns while (iii) adapting them to different hardware architectures with alternative programming models, (iv) analyse the challenges in optimising, and (v) find alternative algorithms for the same scheme. The participating weather prediction models are the following: IFS (Integrated Forecasting System); ALARO, a combination of AROME (Application de la Recherche à l'Opérationnel à Meso-Echelle) and ALADIN (Aire Limitée Adaptation Dynamique Développement International); and COSMO–EULAG, a combination of COSMO (Consortium for Small-scale Modeling) and EULAG (Eulerian and semi-Lagrangian fluid solver). For many of the weather and climate dwarfs ESCAPE provides prototype implementations on different hardware architectures (mainly Intel Skylake CPUs, NVIDIA GPUs, Intel Xeon Phi, Optalysys optical processor) with different programming models. The spectral transform dwarf represents a detailed example of the co-design cycle of an ESCAPE dwarf.</p>
<p>The dwarf concept has proven to be extremely useful for the rapid prototyping of alternative algorithms and their interaction with hardware; e.g. the use of a domain-specific language (DSL). Manual adaptations have led to substantial accelerations of key algorithms in numerical weather prediction (NWP) but are not a general recipe for the performance portability of complex NWP models. Existing DSLs are found to require further evolution but are promising tools for achieving the latter. Measurements of energy and time to solution suggest that a future focus needs to be on exploiting the simultaneous use of all available resources in hybrid CPU–GPU arrangements.</p> |
| first_indexed | 2024-12-10T11:13:02Z |
| format | Article |
| id | doaj.art-a9e137bd5e1d4ff1bdb4bf2f6c9818ec |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-12-10T11:13:02Z |
| publishDate | 2019-10-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-a9e137bd5e1d4ff1bdb4bf2f6c9818ec2022-12-22T01:51:20ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032019-10-01124425444110.5194/gmd-12-4425-2019The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at ExascaleA. Müller0W. Deconinck1C. Kühnlein2G. Mengaldo3M. Lange4N. Wedi5P. Bauer6P. K. Smolarkiewicz7M. Diamantakis8S.-J. Lock9M. Hamrud10S. Saarinen11G. Mozdzynski12D. Thiemert13M. Glinton14P. Bénard15F. Voitus16C. Colavolpe17P. Marguinaud18Y. Zheng19J. Van Bever20D. Degrauwe21G. Smet22P. Termonia23P. Termonia24K. P. Nielsen25B. H. Sass26J. W. Poulsen27P. Berg28C. Osuna29O. Fuhrer30V. Clement31M. Baldauf32M. Gillard33J. Szmelter34E. O'Brien35A. McKinstry36O. Robinson37P. Shukla38M. Lysaght39M. Kulczewski40M. Ciznicki41W. Piątek42S. Ciesielski43M. Błażewicz44K. Kurowski45M. Procyk46P. Spychala47B. Bosak48Z. P. Piotrowski49A. Wyszogrodzki50E. Raffin51C. Mazauric52D. Guibert53L. Douriez54X. Vigouroux55A. Gray56P. Messmer57A. J. Macfaden58N. New59European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKEuropean Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UKCentre National de Recherches Météorologiques, Météo-France, Toulouse, FranceCentre National de Recherches Météorologiques, Météo-France, Toulouse, FranceCentre National de Recherches Météorologiques, Météo-France, Toulouse, FranceCentre National de Recherches Météorologiques, Météo-France, Toulouse, FranceCentre National de Recherches Météorologiques, Météo-France, Toulouse, FranceCentre National de Recherches Météorologiques, Météo-France, Toulouse, FranceRoyal Meteorological Institute (RMI), Brussels, BelgiumRoyal Meteorological Institute (RMI), Brussels, BelgiumRoyal Meteorological Institute (RMI), Brussels, BelgiumRoyal Meteorological Institute (RMI), Brussels, BelgiumDepartment of Physics and Astronomy, Ghent University, Ghent, BelgiumThe Danish Meteorological Institute (DMI), Copenhagen, DenmarkThe Danish Meteorological Institute (DMI), Copenhagen, DenmarkThe Danish Meteorological Institute (DMI), Copenhagen, DenmarkThe Danish Meteorological Institute (DMI), Copenhagen, DenmarkFederal Office of Meteorology and Climatology MeteoSwiss, Zurich, SwitzerlandFederal Office of Meteorology and Climatology MeteoSwiss, Zurich, SwitzerlandCenter for Climate System Modeling, Zurich, SwitzerlandDeutscher Wetterdienst (DWD), Offenbach, GermanyLoughborough University, Leicestershire, UKLoughborough University, Leicestershire, UKIrish Centre for High-End Computing (ICHEC), National University of Ireland, Galway, IrelandIrish Centre for High-End Computing (ICHEC), National University of Ireland, Galway, IrelandIrish Centre for High-End Computing (ICHEC), National University of Ireland, Galway, IrelandIrish Centre for High-End Computing (ICHEC), National University of Ireland, Galway, IrelandIrish Centre for High-End Computing (ICHEC), National University of Ireland, Galway, IrelandPoznań Supercomputing and Networking Center (PSNC), Poznań, PolandPoznań Supercomputing and Networking Center (PSNC), Poznań, PolandPoznań Supercomputing and Networking Center (PSNC), Poznań, PolandPoznań Supercomputing and Networking Center (PSNC), Poznań, PolandPoznań Supercomputing and Networking Center (PSNC), Poznań, PolandPoznań Supercomputing and Networking Center (PSNC), Poznań, PolandPoznań Supercomputing and Networking Center (PSNC), Poznań, PolandPoznań Supercomputing and Networking Center (PSNC), Poznań, PolandPoznań Supercomputing and Networking Center (PSNC), Poznań, PolandInstitute of Meteorology and Water Management – National Research institute (IMGW-PIB), Warsaw, PolandInstitute of Meteorology and Water Management – National Research institute (IMGW-PIB), Warsaw, PolandATOS, Bezons, FranceATOS, Bezons, FranceATOS, Bezons, FranceATOS, Bezons, FranceATOS, Bezons, FranceNVIDIA Switzerland, Zurich, SwitzerlandNVIDIA Switzerland, Zurich, SwitzerlandOptalysys Ltd., Glasshoughton, UKOptalysys Ltd., Glasshoughton, UK<p>In the simulation of complex multi-scale flows arising in weather and climate modelling, one of the biggest challenges is to satisfy strict service requirements in terms of time to solution and to satisfy budgetary constraints in terms of energy to solution, without compromising the accuracy and stability of the application. These simulations require algorithms that minimise the energy footprint along with the time required to produce a solution, maintain the physically required level of accuracy, are numerically stable, and are resilient in case of hardware failure.</p> <p>The European Centre for Medium-Range Weather Forecasts (ECMWF) led the ESCAPE (Energy-efficient Scalable Algorithms for Weather Prediction at Exascale) project, funded by Horizon 2020 (H2020) under the FET-HPC (Future and Emerging Technologies in High Performance Computing) initiative. The goal of ESCAPE was to develop a sustainable strategy to evolve weather and climate<span id="page4426"/> prediction models to next-generation computing technologies. The project partners incorporate the expertise of leading European regional forecasting consortia, university research, experienced high-performance computing centres, and hardware vendors.</p> <p>This paper presents an overview of the ESCAPE strategy: (i) identify domain-specific key algorithmic motifs in weather prediction and climate models (which we term Weather & Climate Dwarfs), (ii) categorise them in terms of computational and communication patterns while (iii) adapting them to different hardware architectures with alternative programming models, (iv) analyse the challenges in optimising, and (v) find alternative algorithms for the same scheme. The participating weather prediction models are the following: IFS (Integrated Forecasting System); ALARO, a combination of AROME (Application de la Recherche à l'Opérationnel à Meso-Echelle) and ALADIN (Aire Limitée Adaptation Dynamique Développement International); and COSMO–EULAG, a combination of COSMO (Consortium for Small-scale Modeling) and EULAG (Eulerian and semi-Lagrangian fluid solver). For many of the weather and climate dwarfs ESCAPE provides prototype implementations on different hardware architectures (mainly Intel Skylake CPUs, NVIDIA GPUs, Intel Xeon Phi, Optalysys optical processor) with different programming models. The spectral transform dwarf represents a detailed example of the co-design cycle of an ESCAPE dwarf.</p> <p>The dwarf concept has proven to be extremely useful for the rapid prototyping of alternative algorithms and their interaction with hardware; e.g. the use of a domain-specific language (DSL). Manual adaptations have led to substantial accelerations of key algorithms in numerical weather prediction (NWP) but are not a general recipe for the performance portability of complex NWP models. Existing DSLs are found to require further evolution but are promising tools for achieving the latter. Measurements of energy and time to solution suggest that a future focus needs to be on exploiting the simultaneous use of all available resources in hybrid CPU–GPU arrangements.</p>https://www.geosci-model-dev.net/12/4425/2019/gmd-12-4425-2019.pdf |
| spellingShingle | A. Müller W. Deconinck C. Kühnlein G. Mengaldo M. Lange N. Wedi P. Bauer P. K. Smolarkiewicz M. Diamantakis S.-J. Lock M. Hamrud S. Saarinen G. Mozdzynski D. Thiemert M. Glinton P. Bénard F. Voitus C. Colavolpe P. Marguinaud Y. Zheng J. Van Bever D. Degrauwe G. Smet P. Termonia P. Termonia K. P. Nielsen B. H. Sass J. W. Poulsen P. Berg C. Osuna O. Fuhrer V. Clement M. Baldauf M. Gillard J. Szmelter E. O'Brien A. McKinstry O. Robinson P. Shukla M. Lysaght M. Kulczewski M. Ciznicki W. Piątek S. Ciesielski M. Błażewicz K. Kurowski M. Procyk P. Spychala B. Bosak Z. P. Piotrowski A. Wyszogrodzki E. Raffin C. Mazauric D. Guibert L. Douriez X. Vigouroux A. Gray P. Messmer A. J. Macfaden N. New The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale Geoscientific Model Development |
| title | The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale |
| title_full | The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale |
| title_fullStr | The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale |
| title_full_unstemmed | The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale |
| title_short | The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale |
| title_sort | escape project energy efficient scalable algorithms for weather prediction at exascale |
| url | https://www.geosci-model-dev.net/12/4425/2019/gmd-12-4425-2019.pdf |
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