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 exas...

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Hauptverfasser: 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
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Sprache:eng
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Zusammenfassung: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 imaging