Tropical Channel NEMO-OASIS-WRF Coupled Simulations at Very High Resolution

International audienc

The ESCAPE project : Energy-efficient Scalable Algorithms for Weather Prediction at Exascale

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. 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 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. 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 a l'Operationnel a Meso-Echelle) and ALADIN (Aire Limitee Adaptation Dynamique Developpement 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. 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

The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale

Abstract. 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. 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 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. 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. 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

Assimilation de données pour les modèles d'hydraulique fluviale. Estimation de paramètres, analyse de sensibilité et décomposition

Flood prediction requires to use every available information. Mathematical equations which allows to build a model, satellite images describing the domain and in situ measurement. Those observations are necessary to make a good prediction because they are the witness of the terrain reality. The aim of this work is to present and test some methods based on the control theory which allows to use optimally every available informations. Some applications of these methods will be treated as parameters estimation, sensitivity analysis and coupling models.Le calcul de prévisions fiables des inondations ne peut se concevoir sans l'utilisation de toutes les informations disponibles. Les équations mathématiques qui permettent la construction d'un modèle, les images satellites par exemple qui décrivent le domaine, mais aussi les mesures faites in situ. Ces observations sont nécessaires à la bonne qualité des prévisions puisqu'elles sont le seul témoin de la réalité du terrain. Le but de ce mémoire est de présenter et de tester des méthodes fondées sur le contrôle optimal permettant une utilisation optimale de toute les informations disponibles. Diverses applications de ces méthodes seront présentées : l'estimation de paramètres, l'analyse de sensibilité et le couplage de modèles

Assimilation de données pour les modèles d'hydraulique fluviale. Estimation de paramètres, analyse de sensibilité et décomposition

Flood prediction requires to use every available information. Mathematical equations which allows to build a model, satellite images describing the domain and in situ measurement. Those observations are necessary to make a good prediction because they are the witness of the terrain reality. The aim of this work is to present and test some methods based on the control theory which allows to use optimally every available informations. Some applications of these methods will be treated as parameters estimation, sensitivity analysis and coupling models.Le calcul de prévisions fiables des inondations ne peut se concevoir sans l'utilisation de toutes les informations disponibles. Les équations mathématiques qui permettent la construction d'un modèle, les images satellites par exemple qui décrivent le domaine, mais aussi les mesures faites in situ. Ces observations sont nécessaires à la bonne qualité des prévisions puisqu'elles sont le seul témoin de la réalité du terrain. Le but de ce mémoire est de présenter et de tester des méthodes fondées sur le contrôle optimal permettant une utilisation optimale de toute les informations disponibles. Diverses applications de ces méthodes seront présentées : l'estimation de paramètres, l'analyse de sensibilité et le couplage de modèles

Assimilation de données pour les modèles d'hydraulique fluviale (estimation de paramètres, analyse de sensibilité et décomposition de domaine)

GRENOBLE1-BU Sciences (384212103) / SudocSudocFranceF

Les irréguliers, un autre après-guerre

« Je suis un irrégulier. Je n’adhère à rien à part entière. Tous les camps me sont tantôt proches, tantôt étrangers », déclarait Romain Gary. « Irrégulier » : combattant qui n’est pas du rang, franc-tireur, partisan. Affirmation d’indépendance provocatrice dans un après-guerre dominé par la surenchère à l’engagement et qui enrégimente les artistes. Les réfractaires en rupture de ban idéologique – Romain Gary, Louis Guilloux, Jean Malaquais, Marc Bernard, Jean Meckert, parmi d’autres – racontent la passionnante (et souvent cuisante) histoire de ceux qui, avec un idéal plutôt ancré à gauche, ont résisté à la pression stalinienne et à ses avatars esthétiques. Car irréguliers politiquement, ils le furent aussi esthétiquement. Pas de parti, pas d’école littéraire. Tirant de la guerre une croyance renouvelée dans les pouvoirs de la fiction, du récit et des personnages, loin de tout conformisme narratif, ils récusèrent, par leurs œuvres, les fausses alternatives de l’embrigadement et du dégoût ou du panache désespéré, tout comme les positions du Nouveau Roman. À l’écart des mouvements littéraires dominants, ils ont ouvert des chemins originaux que les générations suivantes emprunteront à nouveau à la fin du XXe siècle. Ce dossier rapproche des parcours et des œuvres qui, s’ils furent avant tout individuels, révèlent les failles, les contradictions et les aveuglements d’une époque extrêmement politisée, esquissant une autre vision de l’histoire littéraire de cette période