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<publisher>HAL CCSD</publisher>
<title lang=en>High Performance Pre-Computing: Prototype Application to a Coastal Flooding Decision Tool</title>
<creator>Chailan, Romain</creator>
<creator>Laurent, Anne</creator>
<creator>Bouchette, Frédéric</creator>
<creator>Dumontier, Colin</creator>
<creator>Hess, Olivier</creator>
<creator>Lobry, Olivier</creator>
<creator>Michaud, Héloise</creator>
<creator>Nicoud, Sophie</creator>
<creator>Toulemonde, Gwladys</creator>
<contributor>Fouille de données environnementales (TATOO) ; Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM) ; Université de Montpellier (UM) - Centre National de la Recherche Scientifique (CNRS) - Université de Montpellier (UM) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>Géosciences Montpellier ; Université des Antilles et de la Guyane (UAG) - Institut national des sciences de l'Univers (INSU - CNRS) - Université de Montpellier (UM) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>IBM PSSC Montpellier - Innovation Lab. ; IBM PSSC Montpellier</contributor>
<contributor>Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM) ; Université de Montpellier (UM) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>Institut de Mathématiques et de Modélisation de Montpellier (I3M) ; Université Montpellier 2 - Sciences et Techniques (UM2) - Université de Montpellier (UM) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<description>International audience</description>
<source>4th International Conference on Knowledge and Systems Engineering</source>
<source>KSE: Knowledge and Systems Engineering</source>
<coverage>Danang, Vietnam</coverage>
<identifier>lirmm-00736797</identifier>
<identifier>https://hal-lirmm.ccsd.cnrs.fr/lirmm-00736797</identifier>
<identifier>https://hal-lirmm.ccsd.cnrs.fr/lirmm-00736797/document</identifier>
<identifier>https://hal-lirmm.ccsd.cnrs.fr/lirmm-00736797/file/PID2396685.pdf</identifier>
<source>https://hal-lirmm.ccsd.cnrs.fr/lirmm-00736797</source>
<source>KSE: Knowledge and Systems Engineering, Aug 2012, Danang, Vietnam. 4th International Conference on Knowledge and Systems Engineering, pp.195-202, 2012, 〈10.1109/KSE.2012.36〉</source>
<identifier>DOI : 10.1109/KSE.2012.36</identifier>
<relation>info:eu-repo/semantics/altIdentifier/doi/10.1109/KSE.2012.36</relation>
<language>en</language>
<subject>[INFO.INFO-CE] Computer Science [cs]/Computational Engineering, Finance, and Science [cs.CE]</subject>
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<type>Conference papers</type>
<description lang=en>After defining the High Performance Pre- Computing --referred as HPPC-- concept, the aim of the present study is to develop a prototype whether to approve or not the benefits of this concept. Our application case tries to answer the geophysical issue of coastal flooding. This is an example of an alert system based on the HPPC architecture, thus on pre-computed scenarios. The prototype provides the scientists with an ergonomic and on-demand tool allowing the run of scenarios of any implemented numerical models. These runs are available through a web application which submits the corresponding jobs on the remote french public cluster of HPC@LR. In this study we simulate the waves propagation over a Mediterranean grid using the wave model WaveWatch III⃝R . A reference simulation using usual conditions is approximated using the k-NN algorithm over 12, 98 and then 980 pre-computed scenarios. This simple experiment demonstrates how useful the pre-computing of scenarios is for alert systems as far as enough and relevant scenarios are pre-computed. This is the reason why searches continue in each critical points of the HPPC architecture such as the design of experiment, the approximation of the results by meta-models and the research of the closest scenarios in this big data context.</description>
<date>2012-08-17</date>
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