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Enhancing Energy Production with Exascale HPC Methods

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hdl:2117/100183

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Camata, José J.
Cela, José M.
Costa, Danilo
Coutinho, Alvaro LGA
Fernández-Galisteo, Daniel
Jiménez, Carmen
Kourdioumov, Vadim
Mattoso, Marta
Mayo-García, Rafael
Miras, Thomas
Moríñigo, José A.
Navarro, Jorge
Navaux, Philippe O.A.
Oliveira, Daniel de
Rodríguez-Pascual, Manuel
Silva, Vítor
Souza, Renan
Valduriez, Patrick
Document typeConference lecture
Defense date2016
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
ProjectHPC4E - HPC for Energy (EC-H2020-689772)
DESARROLLOS COMPUTACIONALES PARA EL RETO DE LA EXAESCALA 2 (MINECO-TIN2015-63562-R)
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.
CitationCamata, José J. [et al.]. Enhancing Energy Production with Exascale HPC Methods. A: 2 016 LatinAmerican High Performance Computing Conference (CARLA), México, Aug 29-Sep 02, 2016. "". 2016. 
URIhttp://hdl.handle.net/2117/100183
Publisher versionhttps://link.springer.com/chapter/10.1007/978-3-319-57972-6_17
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