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

Foto-obrazy architektury: Fotografia jako medium referujące i projektujące architekturę

Praca recenzowana / peer-reviewed paperNiniejszy zbiór prac teoretycznych, fotoesejów i kronika studenckich konkursów fotograficznych organizowanych od 2008 roku na Wydziale Architektury i Sztuk Pięknych Krakowskiej Akademii im. Andrzeja Frycza Modrzewskiego, ma być zapisem refleksji związanych ze specyficzną, jak dotąd mało zbadaną a wszechobecną częścią teorii architektury, jaką jest fotografia. Jej szczególna odmiana ściśle związana ze sztuką budowania jest określana mianem fotografii architektonicznej, jednakże niniejsza monografia nie została tą definicją ograniczona.This book contains a selection of theoretical works and photo essays as well as a chronicle of photo competitions organised in the Faculty of Architecture and Fine Arts at Andrzej Frycz Modrzewski Krakow University since 2008, which is meant as the record of thoughts related to the specific, omnipresent though little examined so far, realm of the theory of architecture, i.e. photography. Its specific variant closely related to the building practice is called architectural photography. This monograph, however, is not restricted by means of the said definition and attempts at a slightly broader description of the phenomenon, reaching beyond its boundaries.Monografia powstała w ramach projektu badawczego nr WAiSP/DS/4/201

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

FabCovidsim

This is a FabSim3 / EasyVVUQ plugin for Covid-19 simulation. It was used to compute the ensembles of the following paper: Edeling, Wouter and Hamid, Arabnejad and Sinclair, Robert and Suleimenova, Diana and Gopalakrishnan, Krishnakumar and Bosak, Bartosz and Groen, Derek and Mahmood, Imran and Crommelin, Daan and Coveney, Peter, The Impact of Uncertainty on Predictions of the CovidSim Epidemiological Code, 2020

EasyVVUQ: Covidsim version

Version of EasyVVUQ used to generate the results of: W. Edeling. H. Arabnejad, R. Sinclair et al, The Impact of Uncertainty on Predictions of the CovidSim Epidemiological Code, Nat Comp Sci, 2021

FabCovidsim

This is a FabSim3 / EasyVVUQ plugin for Covid-19 simulation. It was used to compute the ensembles of the following paper: Edeling, Wouter and Hamid, Arabnejad and Sinclair, Robert and Suleimenova, Diana and Gopalakrishnan, Krishnakumar and Bosak, Bartosz and Groen, Derek and Mahmood, Imran and Crommelin, Daan and Coveney, Peter, The Impact of Uncertainty on Predictions of the CovidSim Epidemiological Code, 2020

Towards making fusion data FAIR

The concept of FAIR data is being increasingly adopted at national and global levels as a way of maximising the impact and transparency of publicly-funded research outcomes and data. In this paper we introduce the FAIR requirements of the Fusion community as well as technological directions proposed by the Fair4Fusion project aiming at increasing the accessibility to fusion data

EasyVVUQ: Covidsim version

Version of EasyVVUQ used to generate the results of: W. Edeling. H. Arabnejad, R. Sinclair et al, The Impact of Uncertainty on Predictions of the CovidSim Epidemiological Code, Nat Comp Sci, 2021