Enhancing Energy Production with Exascale HPC Methods

José Camata 1 José Cela 2 Danilo Costa 1 Alvaro Lga Coutinho 1 Daniel Fernández-Galisteo 3 Carmen Jimenez 3 Vadim Kourdioumov 3 Marta Mattoso 1 Rafael Mayo-García 3 Thomas Miras 1 José Moríñigo 3 Jorge Navarro 3 Philippe Navaux 4 Daniel de Oliveira 1 Manuel Rodríguez-Pascual 3 Vítor Silva 1 Renan Souza 1 Patrick Valduriez 5
1 COPPE-UFRJ - COPPE - Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia
2 BSC - CNS - Barcelona Supercomputing Center - Centro Nacional de Supercomputacion
3 CIEMAT - Centro de Investigaciones Energéticas Medioambientales y Tecnológicas [Madrid]
4 UFRGS - Instituto de Informática da UFRGS
5 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : 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.
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José Camata, José Cela, Danilo Costa, Alvaro Lga Coutinho, Daniel Fernández-Galisteo, et al.. Enhancing Energy Production with Exascale HPC Methods. CARLA: Latin American High Performance Computing Conference, Aug 2016, Mexico City, Mexico. pp.233-246, ⟨10.1007/978-3-319-57972-6_17⟩. ⟨lirmm-01654914⟩

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