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

Agarose-Based Hydrogels as Suitable Bioprinting Materials for Tissue Engineering

Hydrogels are useful materials as scaffolds for tissue engineering applications. Using hydrogels with additive manufacturing techniques has typically required the addition of techniques such as cross-linking or printing in sacrificial materials that negatively impact tissue growth to remedy inconsistencies in print fidelity. Thus, there is a need for bioinks that can directly print cell-laden constructs. In this study, agarose-based hydrogels commonly used for cartilage tissue engineering were compared to Pluronic, a hydrogel with established printing capabilities. Moreover, new material mixtures were developed for bioprinting by combining alginate and agarose. We compared mechanical and rheological properties, including yield stress, storage modulus, and shear thinning, as well as construct shape fidelity to assess their potential as a bioink for cell-based tissue engineering. The rheological properties and printability of agarose–alginate gels were statistically similar to those of Pluronic for all tests (p > 0.05). Alginate–agarose composites prepared with 5% w/v (3:2 agarose to alginate ratio) demonstrated excellent cell viability over a 28-day culture period (>∼70% cell survival at day 28) as well matrix production over the same period. Therefore, agarose–alginate mixtures showed the greatest potential as an effective bioink for additive manufacturing of biological materials for cartilage tissue engineering