Enhancing Energy Production with Exascale HPC Methods

High Performance Computing (HPC) resources have become the key actor for achieving more ambitious challenges in many disciplines. In this step beyond, an explosion on the available parallelism and the use of special purpose processors are crucial. With such a goal, the HPC4E project applies new exascale HPC techniques to energy industry simulations, customizing them if necessary, and going beyond the state-of-the-art in the required HPC exascale simulations for different energy sources. In this paper, a general overview of these methods is presented as well as some specific preliminary results.The research leading to these results has received funding from the European Union's Horizon 2020 Programme (2014-2020) under the HPC4E Project (www.hpc4e.eu), grant agreement n° 689772, the Spanish Ministry of Economy and Competitiveness under the CODEC2 project (TIN2015-63562-R), and from the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP). Computer time on Endeavour cluster is provided by the Intel Corporation, which enabled us to obtain the presented experimental results in uncertainty quantification in seismic imagingPostprint (author's final draft

Addressing the Challenges in Federating Edge Resources

This book chapter considers how Edge deployments can be brought to bear in a global context by federating them across multiple geographic regions to create a global Edge-based fabric that decentralizes data center computation. This is currently impractical, not only because of technical challenges, but is also shrouded by social, legal and geopolitical issues. In this chapter, we discuss two key challenges - networking and management in federating Edge deployments. Additionally, we consider resource and modeling challenges that will need to be addressed for a federated Edge.Comment: Book Chapter accepted to the Fog and Edge Computing: Principles and Paradigms; Editors Buyya, Sriram

Itzï (version 17.1):an open-source, distributed GIS model for dynamic flood simulation

Worldwide, floods are acknowledged as one of the most destructive hazards. In human-dominated environments, their negative impacts are ascribed not only to the increase in frequency and intensity of floods but also to a strong feedback between the hydrological cycle and anthropogenic development. In order to advance a more comprehensive understanding of this complex interaction, this paper presents the development of a new open-source tool named <q>Itzï</q> that enables the 2-D numerical modelling of rainfall–runoff processes and surface flows integrated with the open-source geographic information system (GIS) software known as GRASS. Therefore, it takes advantage of the ability given by GIS environments to handle datasets with variations in both temporal and spatial resolutions. Furthermore, the presented numerical tool can handle datasets from different sources with varied spatial resolutions, facilitating the preparation and management of input and forcing data. This ability reduces the preprocessing time usually required by other models. Itzï uses a simplified form of the shallow water equations, the damped partial inertia equation, for the resolution of surface flows, and the Green–Ampt model for the infiltration. The source code is now publicly available online, along with complete documentation. The numerical model is verified against three different tests cases: firstly, a comparison with an analytic solution of the shallow water equations is introduced; secondly, a hypothetical flooding event in an urban area is implemented, where results are compared to those from an established model using a similar approach; and lastly, the reproduction of a real inundation event that occurred in the city of Kingston upon Hull, UK, in June 2007, is presented. The numerical approach proved its ability at reproducing the analytic and synthetic test cases. Moreover, simulation results of the real flood event showed its suitability at identifying areas affected by flooding, which were verified against those recorded after the event by local authorities