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20 results on '"IBM PSSC Montpellier"'

1. Exploiting Software Product Lines and Formal Concept Analysis for the Design of Data Lake Architectures

Author

André Miralles, Thérèse Libourel Rouge, Anne Laurent, Cédrine Madera, Marianne Huchard, Models And Reuse Engineering, Languages (MAREL), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), WEB-CUBE, UMR 228 Espace-Dev, Espace pour le développement, Université de Guyane (UG)-Université des Antilles (UA)-Institut de Recherche pour le Développement (IRD)-Université de Perpignan Via Domitia (UPVD)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Anne Laurent, Dominique Laurent, and Cédrine Madera

Subjects
Series (mathematics), Software product line, Computer science, business.industry, Formal Concept Analysis, [INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE], Feature model, Terminology, Software, Product (mathematics), Formal concept analysis, Architecture, Software engineering, business, Data lake
Abstract

International audience; This chapter aims to investigate an approach to assisting the user in the design of a data lake architecture. Software product line engineering is an approach that allows for the formalization of a series of similar software products or systems, which only differ in some of their optional components. The chapter introduces a formalization approach based on the model of product lines. Before doing so, it provides an overview of basic notions and terminology related to Software Product Line and Formal Concept Analysis. The chapter shows an approach to assisting and accelerating the construction of a data lake. This approach consists of high‐level modeling, independent from physical tools, relying on existing software product line concepts. The chapter considers existing semi‐automated processes to generate the feature model that provides us with a preliminary formal model regarding the functionalities of the components of a data lake.

Published
2020
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2. Deep brain stimulation treated dystonia-trajectory via status dystonicus

Author

Nerrant, Elodie, Gonzalez, Victoria, Milesi, Christophe, Vasques, Xavier, Ruge, Diane, Roujeau, Thomas, De Antonio Rubio, Isabel, Cyprien, Fabienne, Seng, Emilie Chan, Demailly, Diane, Roubertie, Agathe, Boularan, Alain, Greco, Fréderic, Perrigault, Pierre-François, Cambonie, Gilles, Coubes, Philippe, Cif, Laura, Centre Hospitalier Régional Universitaire de Nîmes (CHRU Nîmes), Département de neurologie [Montpellier], Université Montpellier 1 (UM1)-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Hôpital Gui de Chauliac [Montpellier]-Université de Montpellier (UM), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, Department of Neurology, Philipps University-Center of Nervous Diseases, Service de Neurochirurgie [Montpellier], Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-CHU Gui de Chauliac [Montpellier], Neuropsychiatrie : recherche épidémiologique et clinique, Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Montpellier 1 (UM1)-Université de Montpellier (UM), Institut des Neurosciences de Montpellier - Déficits sensoriels et moteurs (INM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Université de Montpellier (UM), CHU Montpellier, Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Neurochirurgie [Hôpital Gui de Chauliac], Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Hôpital Gui de Chauliac [Montpellier], Centre Hospitalier Universitaire de Nîmes (CHU Nîmes), Institut de Génomique Fonctionnelle (IGF), Université de Montpellier (UM)-Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Montpellier 2 - Sciences et Techniques (UM2)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Recherche en Neurosciences Cliniques, Technische Universität Dortmund [Dortmund] (TU), Neuropsychiatrie : recherche épidémiologique et clinique (PSNREC), Université Montpellier 1 (UM1)-Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hôpital Gui de Chauliac [Montpellier]-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Université Montpellier 1 (UM1)-Université de Montpellier (UM), CHU Gui de Chauliac [Montpellier]-Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), and Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM)

Subjects
Male, Adult, Adolescent, Deep Brain Stimulation, [SDV]Life Sciences [q-bio], deep brian stimulation, Magnetic Resonance Imaging, Cohort Studies, Dystonia, Young Adult, Treatment Outcome, reversibility, Child, Preschool, dystonia trajectory, outcome, status dystonicus, Humans, Female, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Child, Preschool, ComputingMilieux_MISCELLANEOUS
Abstract

International audience; BACKGROUND: Status dystonicus (SD) is a life-threatening condition. OBJECTIVE AND METHODS: In a dystonia cohort who developed status dystonicus, we analyzed demographics, background dystonia phenomenology and complexity, trajectory previous to-, via status dystonicus episodes, and evolution following them. RESULTS: Over 20 years, 40 of 328 dystonia patients who were receiving DBS developed 58 status dystonicus episodes. Dystonia was of pediatric onset (95%), frequently complex, and had additional cognitive and pyramidal impairment (62%) and MRI alterations (82.5%); 40% of episodes occured in adults. Mean disease duration preceding status dystonicus was 10.3 \textpm 8 years. Evolution time to status dystonicus varied from days to weeks; however, 37.5% of patients exhibited progressive worsening over years. Overall, DBS was efficient in resolving 90% of episodes. CONCLUSION: Status dystonicus is potentially reversible and a result of heterogeneous conditions with nonuniform underlying physiology. Recognition of the complex phenomenology, morphological alterations, and distinct patterns of evolution, before and after status dystonicus, will help our understanding of these conditions. \textcopyright 2018 International Parkinson and Movement Disorder Society.

Published
2018
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3. Piezoelectric energy harvesting: application to data center monitoring

Author

Olivier Hess, François Briant, Jean Podlecki, Marie Angele Grilli, Philippe Combette, Alain Foucaran, Youri Poulin, Saniya Ben Hassen, Ricardo Garcia, Institut d’Electronique et des Systèmes (IES), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Matériaux, MicroCapteurs et Acoustique (M2A), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Micro électronique, Composants, Systèmes, Efficacité Energétique (M@CSEE), IBM PSSC Montpellier - Innovation Lab., and IBM PSSC Montpellier

Subjects
Engineering, Cantilever, Maximum power principle, business.industry, Electrical engineering, Capacitance, Industrial and Manufacturing Engineering, [SPI.TRON]Engineering Sciences [physics]/Electronics, Vibration, Acceleration, Electrical and Electronic Engineering, business, Wireless sensor network, Energy harvesting, ComputingMilieux_MISCELLANEOUS, Efficient energy use
Abstract

Purpose – The purpose of this paper is to report the study of vibration energy harvesting from a data center (DC) mainframe computer to power nodes of a wireless sensors network (WSN are used to improve the energy efficiency of a DC). Design/methodology/approach – The piezoelectric vibration energy harvester (VEH) has been designed using an electromechanical analytical model. The VEH is composed of a three-layer cantilever beam with a tip mass. A vibration map (amplitude and acceleration) is presented and the authors show that the optimum frequency is around 90 Hz with maximum amplitude of 1 μm and maximum acceleration of 0.6 m/s2. Modeling results and experimental measurements using an electromagnetic shaker to apply vibrations concord. Findings – The VEH delivers a maximum power of 31 μW on a DC mainframe computer and 2.3 mW at 1g on a test rack. It allows us to use a storage capacitance to successfully power a wireless sensor node for measuring temperature. This paper has been carried out in cooperation with IBM Montpellier and within the framework of the RIDER project financed by the French government and the European Union. Originality/value – A vibration map (amplitude and acceleration) is presented and the authors show that the optimal frequency is around 90 Hz with maximum amplitude of 1 μm and maximum acceleration of 0.6 m/s2. The VEH delivers a maximum power of 31 μW on DC mainframe computer and 2.3 mW at 1 g on test mounted the shaker. It allows us with a storage capacitance to successfully power a wireless sensor node for measuring temperature.

Published
2015
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4. How can the data lake concept influence information system design for agriculture?

Author

Madera, Cédrine, Laurent, Anne, Libourel Rouge, Thérèse, Miralles, André, Fuzziness, Alignments, Data & Ontologies (FADO), 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), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, UMR 228 Espace-Dev, Espace pour le développement, Université des Antilles (UA)-Université de Guyane (UG)-Université de Montpellier (UM)-Université de La Réunion (UR)-Avignon Université (AU)-Université de Perpignan Via Domitia (UPVD)-Institut de Recherche pour le Développement (IRD), Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS), LIBOUREL, Therese, WEB-CUBE, Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Université de Guyane (UG)-Université des Antilles (UA)-Institut de Recherche pour le Développement (IRD)-Université de Perpignan Via Domitia (UPVD)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM), WEB Architecture x Semantic WEB x WEB of Data (WEB3), and Institut de Recherche pour le Développement (IRD)-Université de Perpignan Via Domitia (UPVD)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM)-Université de Guyane (UG)-Université des Antilles (UA)

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], ComputingMilieux_GENERAL, Data Warehouse, Metadata, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], Data Gravity, [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB], Data Governance, Federated Analytics, Data Lake, Data Laboratory, Data Management, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

The conference was launched and is supported by the European Federation for Information Technology in Agriculture, Food and the Environment (EFITA) with the collaboration of the World Congress on Computers in Agriculture (WCCA).; International audience; The agricultural ecosystem has already achieved its technical mechanical revolution, yet, like the whole society it faces with the "digital revolution" (computers, Internet, sensors, connected objects, etc…). This leads to a new phenomenon: the massive arrival of various data and, consequently, the importance of this data for information systems and beyond for decision support systems (usually in the form of a data warehouse exploitable by various exploration methods). In response to emerging issues such as sustainable development and adaptation to climate change, agricultural organizations and governments in charge of information delivery and decision-making systems must manage and implement new information systems to adapt to these new challenges.

Published
2017

5. Artemisinins Target GABA A Receptor Signaling and Impair α Cell Identity

Author

Sara Sdelci, Tibor Harkany, Keiryn L. Bennett, Kilian Huber, Patrick Collombat, Christian Honoré, Florian M. Pauler, Matthias Farlik, Ekaterine Berishvili, Monica Courtney, Igor Baburin, Stefan Kubicek, Nicole Schmitner, Jin Li, Steffen Hering, Peter Májek, Jacob Hecksher-Sørensen, Thierry Sulpice, Martin Distel, Robin A. Kimmel, Charles-Hugues Lardeau, Manuela Gridling, Johanna Klughammer, Camilla Ingvorsen, Alexey Stukalov, Christoph Bock, Andhira Vieira, François Briand, Giulio Superti-Furga, Roman A. Romanov, Thomas Frogne, Dirk Meyer, Caterina Sturtzel, Thomas Penz, Fabio Avolio, Katja Parapatics, Jacques Colinge, Andreas Spittler, Charlotte Barbieux, Tamara Casteels, Harbin Engineering University (HRBEU), Research Center for Molecular Medicine of the Austrian Academy of Sciences [Vienna, Austria] (CeMM ), Austrian Academy of Sciences (OeAW), CeMM Research Center for Molecular Medicine [Vienna, Austria], Novo Nordisk A/S , Danemark, Novo Nordisk, Institut de Biologie Valrose (IBV), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Institute for Research on Cancer and Aging, Nice (IRCAN), INSERM, U1081, CNRS UMR 7284, Nice, Innsbruck Medical University [Austria] (IMU), Leopold Franzens Universität Innsbruck - University of Innsbruck, Medizinische Universität Wien = Medical University of Vienna, Karolinska Institutet [Stockholm], Tumor Immunology [Vienna, Austria] (Children’s Cancer Research Institute), St. Anna Kinderkrebsforschung e.V. [Vienna, Austria], CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria, Physiological Chemistry, Biocenter, Am Hubland, Julius-Maximilians-Universität Würzburg [Wurtzbourg, Allemagne] (JMU), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, Physiogenex, University of Geneva [Switzerland], Geneva University Hospital (HUG), Institut de Recherche en Cancérologie de Montpellier (IRCM - U1194 Inserm - UM), CRLCC Val d'Aurelle - Paul Lamarque-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Children’s Cancer Research Institute [Vienna, Austria], University of Vienna [Vienna], Cancer Center Karolinska [Karolinska Institutet] (CCK), Directors's Laboratory, Novo Nordisk Foundation Center for Biosustainability, and Technical University of Denmark [Lyngby] (DTU)

Subjects
0301 basic medicine, insulin secretion, Artemisinins/administration & dosage/pharmacology, β cell, Carrier Proteins/metabolism, Diabetes Mellitus/drug therapy, Mice, Single-cell analysis, Insulin-Secreting Cells, GABA-receptor signaling, Insulin, artemisinins, gamma-Aminobutyric Acid/metabolism, Cells, Cultured, Zebrafish, gamma-Aminobutyric Acid, pancreatic endocrine transdifferentiation, ddc:617, biology, diabetes, Protein Stability, Receptors, GABA-A/metabolism, Transdifferentiation, Diabetes Mellitus, Type 1/drug therapy/pathology, 3. Good health, Cell biology, medicine.anatomical_structure, Biochemistry, ARX translocation, Artemether, MESH: Animals, Disease models, animal, Insulin/Genetics, Signal transduction, Artemisinins/Pharmacology, Single-Cell Analysis, Signal Transduction, Cell type, regenerative medicine, chemical biology, [SDV.CAN]Life Sciences [q-bio]/Cancer, Cell Transdifferentiation/drug effects, Article, General Biochemistry, Genetics and Molecular Biology, Diabetes Mellitus, Experimental, Islets of Langerhans, 03 medical and health sciences, Genetic model, Protein Stability/drug effects, Diabetes Mellitus, medicine, Homeodomain Proteins/metabolism, Regeneration, Animals, Humans, Transcription Factors/metabolism, Transcription factor, Homeodomain Proteins, Insulin/genetics/metabolism, Gephyrin, Biochemistry, Genetics and Molecular Biology(all), Gene Expression Profiling, Pancreatic islets, Membrane Proteins, Islets of Langerhans/drug effects, Receptors, GABA-A, gephyrin, Rats, Disease Models, Animal, Diabetes Mellitus, Type 1, 030104 developmental biology, Cell Transdifferentiation, biology.protein, Membrane Proteins/metabolism, Carrier Proteins, Transcription Factors
Abstract

Summary Type 1 diabetes is characterized by the destruction of pancreatic β cells, and generating new insulin-producing cells from other cell types is a major aim of regenerative medicine. One promising approach is transdifferentiation of developmentally related pancreatic cell types, including glucagon-producing α cells. In a genetic model, loss of the master regulatory transcription factor Arx is sufficient to induce the conversion of α cells to functional β-like cells. Here, we identify artemisinins as small molecules that functionally repress Arx by causing its translocation to the cytoplasm. We show that the protein gephyrin is the mammalian target of these antimalarial drugs and that the mechanism of action of these molecules depends on the enhancement of GABAA receptor signaling. Our results in zebrafish, rodents, and primary human pancreatic islets identify gephyrin as a druggable target for the regeneration of pancreatic β cell mass from α cells., Graphical Abstract, Highlights • Artemisinins inhibit ARX function and impair α cell identity • Compounds act by stabilizing gephyrin, thus enhancing GABAA receptor signaling • Artemisinins increase β cell mass in zebrafish and rodent models • Functional and transcriptional data indicate a conserved phenotype in human islets, The anti-malarial drug Artemisinin can drive the in vivo conversion of pancreatic α cells into functional β-like cells through enhanced GABA signaling and may have potential as a therapeutic for diabetes.

Published
2017
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6. The next information architecture evolution

Author

Anne Laurent, Cédrine Madera, IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, WEB-CUBE, Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), and Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)

Subjects
Decision support system, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], business.industry, Computer science, Information architecture, Internet of Things, 02 engineering and technology, Digital Transformation, Data laboratory, Data Warehouses, Data science, Data warehouse, Data governance, Data modeling, Data Reservoirs, 020204 information systems, Data quality, Data Lab, 0202 electrical engineering, electronic engineering, information engineering, Information system, 020201 artificial intelligence & image processing, Data Governance, Data architecture, business
Abstract

International audience; Data warehouses and data marts have long been considered as the unique solution for providing end-users with decisional information. More recently, data lakes have been proposed in order to govern data swamps. However, no formal definition has been proposed in the literature. Existing works are not complete and miss important parts of the topic. In particular , they do not focus on the influence of the data gravity , the infrastructure role of those solutions and of course are proposing divergent definitions and positioning regarding the usage and the interaction with existing decision support system. In this paper, we propose a novel definition of data lakes, together with a comparison with other over several criteria as the way to populate them, how to use, what is the Data Lake end user profile. We claim that data lakes are complementary components in decisional information systems and we discuss their position and interactions regarding the other components by proposing an interaction model.

Published
2016
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7. Discovering unexpected information using a building energy visualization tool

Author

Xavier Vasques, William Puech, Nancy Rodriguez, Benoit Lange, Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), ADVanced Analytics for data SciencE (ADVANSE), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Image & Interaction (ICAR), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), and Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)

Subjects
Computer science, 020209 energy, 02 engineering and technology, Information technology, 01 natural sciences, 7. Clean energy, Information visualization, Databases, Component (UML), 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, Buildings, 010306 general physics, Data mining, Visualization, Building management system, business.industry, Sensors, Data science, Surveillance systems, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Volume rendering, Energy efficiency, Scalability, business, Software engineering, Efficient energy use
Abstract

Building energy consumption is an important problem in construction field, old buildings are gap of energy and they need to be refactored. Energy footprint of buildings needs to be reduced. New buildings are designed to be suitable with energy efficiency paradigm. To improve energy efficiency, Building Management Systems (BMS) are used: BMS are IT (Information Technology) systems composed by a rules engine and a database connected to sensors. Unfortunately, BMS are only monitoring systems: they cannot predict and mine efficiently building information. RIDER project has emerged from this observation. This project is conducted by several French companies and universities, IBM at Montpellier, France, leads the project. The main goal of this project is to create a smart and scalable BMS. This new kind of BMS will be able to dig into data and predict events. This IT system is based on component paradigm and the core can be extended with external components. Some of them are developed during the project: data mining, building generation model and visualization. All of these components will provide new features to improve rules used by the core. In this paper, we will focus on the visualization component. This visualization use a volume rendering method based on sensors data interpolation and a correlation method to create new views. We will present the visualization method used and which rules can be provided by this component.

Published
2013
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8. High Performance Pre-computing: Prototype Application to a Coastal Flooding Decision Tool

Author

Romain Chailan, Colin G. Dumontier, Olivier Hess, Sophie Nicoud, Olivier Lobry, Frédéric Bouchette, Héloïse Michaud, Gwladys Toulemonde, Anne Laurent, Fouille de données environnementales (TATOO), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), 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), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Institut de Mathématiques et de Modélisation de Montpellier (I3M), and Centre National de la Recherche Scientifique (CNRS)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)

Subjects
business.industry, Computer science, [INFO.INFO-CE]Computer Science [cs]/Computational Engineering, Finance, and Science [cs.CE], Big data, 0207 environmental engineering, Context (language use), 0102 computer and information sciences, 02 engineering and technology, computer.software_genre, Grid, 01 natural sciences, Industrial engineering, Grid computing, 010201 computation theory & mathematics, Web application, The Internet, Data mining, Architecture, 020701 environmental engineering, business, Coastal flood, computer
Abstract

International audience; 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.

Published
2012
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9. Towards Scalable Data Management for Map-Reduce-based Data-Intensive Applications on Cloud and Hybrid Infrastructures

Author

Gabriel Antoniu, Julien Bigot, Christophe Blanchet, Luc Bougé, François Briant, Franck Cappello, Alexandru Costan, Frédéric Desprez, Gilles Fedak, Sylvain Gault, Kate Keahey, Bogdan Nicolae, Christian Pérez, Anthony Simonet, Frédéric Suter, Bing Tang, Raphael Terreux, Scalable Storage for Clouds and Beyond (KerData), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SYSTÈMES LARGE ÉCHELLE (IRISA-D1), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Algorithms and Software Architectures for Distributed and HPC Platforms (AVALON), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de l'Informatique du Parallélisme (LIP), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Institut de biologie et chimie des protéines [Lyon] (IBCP), Université Claude Bernard Lyon 1 (UCBL), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, Global parallel and distributed computing (GRAND-LARGE), Laboratoire de Recherche en Informatique (LRI), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Laboratoire d'Informatique Fondamentale de Lille (LIFL), Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria), Joint Laboratory for Petascale Computing [Illinois] (JLPC), Institut National de Recherche en Informatique et en Automatique (Inria)-University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Argonne National Laboratory [Lemont] (ANL), Centre de Calcul de l'IN2P3 (CC-IN2P3), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), ANR-10-SEGI-0001,MapReduce,Traitement intensif de données à très grande échelle à l'aide du paradigme MapReduce sur des infrastructures de type cloud et hybrides(2010), University of Illinois at Urbana-Champaign [Urbana], University of Illinois System, Mathematics and Computer Science Division [ANL] (MCS), IBM Research - Ireland, IBM, CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École normale supérieure - Lyon (ENS Lyon), Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Paris-Sud - Paris 11 (UP11)-Laboratoire d'Informatique Fondamentale de Lille (LIFL), Université de Lille, Sciences et Technologies-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Université de Lille, Sciences Humaines et Sociales-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Recherche en Informatique (LRI), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec, and University of Illinois at Urbana Champaign (UIUC)

Subjects
BlobSeer, hybrid infrastructures, HLCM, cloud computing, BitDew, Grid'5000, Map-Reduce, MapReduce, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], Nimbus, ComputingMilieux_MISCELLANEOUS, data-intensive computing
Abstract

International audience; As Map-Reduce emerges as a leading programming paradigm for data-intensive computing, today's frameworks which support it still have substantial shortcomings that limit its potential scalability. In this paper we discuss several directions where there is room for such progress: they concern storage efficiency under massive data access concurrency, scheduling, volatility and fault-tolerance. We place our discussion in the perspective of the current evolution towards an increasing integration of large-scale distributed platforms (clouds, cloud federations, enterprise desktop grids, etc.). We propose an approach which aims to overcome the current limitations of existing Map-Reduce frameworks, in order to achieve scalable, concurrency-optimized, fault-tolerant Map-Reduce data processing on hybrid infrastructures. This approach will be evaluated with real-life bio-informatics applications on existing Nimbus-powered cloud testbeds interconnected with desktop grids.

Published
2012
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10. Data, Models and Theories for Complex Systems: new challenges and opportunities

Author

Valduriez, Patrick, Arnaud, Nicolas, Briand, François, Gascuel, Olivier, Gimenez, Olivier, Godin, Christophe, Jourde, Hervé, Kosuth, Pascal, Neveu, Pascal, Pacitti, Esther, Parmeggiani, Andrea, Scientific Data Management (ZENITH), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Observatoire de REcherche Méditerranéen de l'Environnement (OSU OREME), Université Montpellier 2 - Sciences et Techniques (UM2)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, Laboratoire de Mathématiques Appliquées de Bordeaux (MAB), Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1, Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Université Paul-Valéry - Montpellier 3 (UPVM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut de Recherche pour le Développement (IRD [France-Sud]), Modeling plant morphogenesis at different scales, from genes to phenotype (VIRTUAL PLANTS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Recherche Agronomique (INRA)-Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Hydrosciences Montpellier (HSM), Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-AgroParisTech-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Dynamique des interactions membranaires normales et pathologiques (DIMNP), Université Montpellier 1 (UM1)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), LIRMM, Superviseur : Patrick Valduriez, Partenaires : Université Montpellier 2 (Sciences et Techniques) (UM2), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Inria Sophia Antipolis - Méditerranée (CRISAM), Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de Mathématiques Appliquées (MAB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Centre National de la Recherche Scientifique (CNRS), Université Paul-Valéry - Montpellier 3 (UM3)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Inria Sophia Antipolis - Méditerranée (CRISAM), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Institut de Recherche pour le Développement (IRD)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Montpellier 2 - Sciences et Techniques (UM2), and Institut de Recherche pour le Développement (IRD [France-Sud])-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université Paul-Valéry - Montpellier 3 (UM3)

Subjects
observation of natural and biological medium, agronomy, life science, data production, scientific data management, [INFO]Computer Science [cs], high performance computing (HPC), storage and archiving, Cloud Computing, environmental science, climate, complex systems modeling and simulation
Abstract

INFO/MAB, INFO/ZENITHFinal Report of the ModSysC2020 Working Group at University Montpellier 2; At University Montpellier 2, the modeling and simulation of complex systems has been identified as a major scientific challenge and one of the priority axes in interdisciplinary research, with major potential impact on training, economy and society. Many research groups and laboratories in Montpellier are already working in that direction, but typically in isolation within their own scientific discipline. Several local actions have been initiated in order to structure the scientific community with interdisciplinary projects, but with little coordination among the actions. The goal of the ModSysC2020 (modeling and simulation of complex systems in 2020) working group was to analyze the local situation (forces and weaknesses, current projects), identify the critical research directions and propose concrete actions in terms of research projects, equipment facilities, human resources and training to be encouraged. To guide this perspective, we decomposed the scientific challenge into four main themes, for which there is strong background in Montpellier: (1) modeling and simulation of complex systems; (2) algorithms and computing; (3) scientific data management; (4) production, storage and archiving of data from the observation of the natural and biological media. In this report, for each theme, we introduce the context and motivations, analyze the situation in Montpellier, identify research directions and propose specific actions in terms of interdisciplinary research projects and training. We also provide an analysis of the socio-economical aspects of modeling and simulation through use cases in various domains such as life science and healthcare, environmental science and energy. Finally, we discuss the importance of revisiting students training in fundamental domains such as modeling, computer programming and database which are typically taught too late, in specialized masters.

Published
2012

11. Analysis and Knowledge Discovery from Sensors Data to Improve Energy Efficiency

Author

Vasques, Xavier, Possompès, Thibaut, Rey, Hervé, Le Touzé, Marine, Auboin, Nicolas, Passot, Emmanuelle, Lange, Benoit, IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, Models And Reuse Engineering, Languages (MAREL), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), and Possompès, Thibaut

Subjects
Sensors, Predictive Analysis, Data Centers, Energy-efficient buildings, Data set history, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
Abstract

International audience; Increases in energy prices and the global goal of mitigating CO2 emissions necessitate the development of intelligent Building Management Systems (BMS) that operate on an energy-efficient basis. Data Centers, buildings and/or group of buildings are often responsible for huge energy consumption. One way to monitor and optimize energy consumption is to instrument buildings using sensors (temperature, pressure, humidity ...) in order to track and solve wrong usage of energy management systems. The majority of the BMS are processing the data dynamically without taking into account the data history due to their constraint problems (time, bandwidth and calculation capability) and data resources. The RIDER project brings together a consortium of research laboratories and enterprises including IBM, to share their expertise in research and development of smart Information Technology (IT) energy platforms. In this context, we aim to improve energy efficiency of buildings or group of building (including data centers) using IT. One of the objectives is to identify valid, potentially useful, and ultimately understandable patterns in data for improving energy efficiency. We propose in this paper an approach of using an integrated platform able to interconnect instrumented buildings and sites, and to provide a high-level point of view for increasing our knowledge from sensors. The expected results are to estimate physical parameters that influence energy consumption based on data set history. Different correlation could be found between different variables, for example, indoor air quality and energy consumption. These results could be applied at a location where no sensor is placed and predict energy consumption from different variables.

Published
2011

12. Diagramme de Features, adaptation par transformation dans le contexte des bâtiments intelligents

Author

Thibaut Possompès, François Briant, Christophe Dony, Marianne Huchard, Chouki Tibermacine, Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, Models And Reuse Engineering, Languages (MAREL), and Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)

Subjects
mode-driven engineering, smart buildings, UML profiles, Software product lines, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Feature diagrams
Abstract

National audience; Software product lines in smart buildings involve large feature models in which the variability reflects the instrumentation and composition of the building. Moreover, some variation points must be duplicated on each occurrence of certain elements of the building (e.g., optimisation scenarios dedicated to each room of the building). We propose a model-driven approach to generate and configure feature models specific to a given building. In other ways, a diagram showing only appropriate features for a given building. This paper presents how an infrastructure model (describing a building), and a feature model are transformed to generate a infrastructure-specific feature diagrams.

Published
2011

13. Visualization assisted by parallel processing

Author

Nancy Rodriguez, Benoit Lange, Hervé Rey, William Puech, Xavier Vasques, Image & Interaction (ICAR), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, and FUI RIDER

Subjects
business.industry, Computer science, Delaunay triangulation, Computer programming, 020207 software engineering, 02 engineering and technology, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Real-time rendering, Rendering (computer graphics), Visualization, Computational science, Data visualization, 020204 information systems, Computer graphics (images), Personal computer, 0202 electrical engineering, electronic engineering, information engineering, General-purpose computing on graphics processing units, business
Abstract

International audience; This paper discusses the experimental results of our visualization model for data extracted from sensors. The objective of this paper is to find a computationally efficient method to produce a real time rendering visualization for a large amount of data. We develop visualization method to monitor temperature variance of a data center. Sensors are placed on three layers and do not cover all the room. We use particle paradigm to interpolate data sensors. Particles model the "space" of the room. In this work we use a partition of the particle set, using two mathematical methods: Delaunay triangulation and Vorono ̈ı cells. Avis and Bhattacharya present these two algorithms in1 . Particles provide information on the room temperature at different coordinates over time. To locate and update particles data we define a computational cost function. To solve this function in an efficient way, we use a client server paradigm2 . Server computes data and client display this data on different kind of hardware. This paper is organized as follows. The first part presents related algorithm used to visualize large flow of data. The second part presents different platforms and methods used, which was evaluated in order to determine the better solution for the task proposed. The benchmark use the computational cost of our algorithm that formed based on located particles compared to sensors and on update of particles value. The benchmark was done on a personal computer using CPU, multi core programming, GPU programming and hybrid GPU/CPU. GPU programming method is growing in the research field; this method allows getting a real time rendering instates of a precompute rendering. For improving our results, we compute our algorithm on a High Performance Computing (HPC), this benchmark was used to improve multi-core method. HPC is commonly used in data visualization (astronomy, physic, etc) for improving the rendering and getting real-time.

Published
2011
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14. A 3d particle visualization system for temperature management

Author

Nancy Rodriguez, William Puech, Benoit Lange, Xavier Vasques, Hervé Rey, Institut des Sciences du Calcul et des Données (ISCD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Sorbonne Universités, ADVanced Analytics for data SciencE (ADVANSE), 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), Image & Interaction (ICAR), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), and FUI RIDER

Subjects
Measure (data warehouse), Work (thermodynamics), Computer science, Real-time computing, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 020207 software engineering, 02 engineering and technology, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Visualization, Client–server model, 020204 information systems, Computer graphics (images), 0202 electrical engineering, electronic engineering, information engineering, [INFO]Computer Science [cs], [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], Level of detail, ComputingMilieux_MISCELLANEOUS
Abstract

International audience; This paper deals with a 3D visualization technique proposed to analyze and manage energy efficiency from a data center. Data are extracted from sensors located in the IBM Green Data Center in Montpellier France. These sensors measure different information such as hygrometry, pressure and temperature. We want to visualize in real-time the large among of data produced by these sensors. A visualization engine has been designed, based on particles system and a client server paradigm. In order to solve performance problems, a Level Of Detail solution has been developed. These methods are based on the earlier work introduced by J. Clark in 1976.1 In this paper we introduce a particle method used for this work and subsequently we explain different simplification methods we have applied to improve our solution.

Published
2011
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15. A UML Profile for Feature Diagrams: Initiating a Model Driven Engineering Approach for Software Product Lines

Author

Thibaut Possompès, Christophe Dony, Marianne Huchard, Hervé Rey, Chouki Tibermacine, Xavier Vasques, Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, Models And Reuse Engineering, Languages (MAREL), and Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)

Subjects
software product lines, UML profile, model driven engineering, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Feature diagrams
Abstract

National audience; This paper proposes an instrumented approach to integrate feature diagrams with UML models, via UML profiles and a Rational Software Architect plugin. The concrete contribution is the specification of a new UML profile based upon a meta-model synthesising existing feature diagrams semantics, and a Rational Software Architect (RSA) implementation. Our RSA implementation makes possible to link feature diagrams with UML model artefacts. Indeed, it allows traceability between feature models and other different kinds of models (requirements, class diagrams, sequences or activity diagrams, etc.).

Published
2010

16. Visualisation 3d d'un système de particules issu de capteurs de température

Author

Benoit Lange, Rodriguez, Nancy, Puech, William, Rey, Hervé, Vasques, Xavier, Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Image & Interaction (ICAR), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), IBM PSSC Montpellier - Innovation Lab., and IBM PSSC Montpellier

Subjects
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]
Abstract

National audience; Cet article traite de la visualisation 3D interactive de données issues de capteurs situes dans le centre de calcul IBM Montpellier (data center). Il est important de visualiser ces données dans le but d'analyser et par la suite réduire la consommation d'énergie totale dans des data centers. Un moteur de visualisation a été développé afin de pouvoir comprendre, en temps réel, le comportement des capteurs. Ce moteur se base sur un système de particules qui remplit et représente l'espace d'une salle de calcul. Pour cela, nous utilisons les diagrammes de Voronoï et la triangulation de Delaunay afin de pondérer l'influence de chacune des particules en fonction de leur distance aux capteurs. La visualisation d'une salle en 3D avec un grand nombre de données issues des capteurs est possible grâce à cette solution. La contrainte principale de notre visualisation 3D est l'interactivité du système qui doit garantir un meilleur suivi de l'évolution des mesures prises par les capteurs

Published
2010

17. Towards Software Product Lines Application in the Context of a Smart Building Project

Author

Thibaut Possompès, Christophe Dony, Marianne Huchard, Hervé Rey, Chouki Tibermacine, Xavier Vasques, Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, Models And Reuse Engineering, Languages (MAREL), and Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)

Subjects
traceability, Smart buildings, feature diagrams, model transformations, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation
Abstract

International audience; This paper presents proposals on how to apply software product lines in the context of smart buildings control systems. Our study is held in the context of the RIDER (Research for IT as a Driver of EneRgy efficiency) project, which is led by a consortium of several companies and research laboratories. The paper highlights various issues, including issues related to traceability, variability and automatic transformations in our specific application context. It then proposes solutions to apply existing concepts like feature diagrams, model-driven transformations and component-based architectures, or appropriate extensions of these concepts, in this context. Furthermore, we globally propose an approach to federate the various components involved in smart buildings, and to capitalize on the developed IT components by reusing them at the lower cost in the construction of future buildings.

Published
2010

18. Architectural analysis of root system of sexually vs. vegetatively propagated yam (Dioscorea rotundata Poir.), a tuber monocot

Author

Hervé Rey, Claude Edelin, Tristan Charles-Dominique, Christophe Jourdan, Thomas Mangenet, Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), Fonctionnement et pilotage des écosystèmes de plantations (Cirad-Persyst-UPR 80 Ecosystèmes de plantations), Département Performances des systèmes de production et de transformation tropicaux (Cirad-PERSYST), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD [France-Sud]), Fonctionnement et pilotage des écosystèmes de plantations (UPR Ecosystèmes de plantations), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Institut d'écologie et des sciences de l'environnement de Paris (IEES (UMR_7618 / UMR_D_242 / UMR_A_1392 / UM_113) ), Institut National de la Recherche Agronomique (INRA)-Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, Ecologie fonctionnelle et biogéochimie des sols et des agro-écosystèmes (UMR Eco&Sols), Institut National de la Recherche Agronomique (INRA)-Institut de Recherche pour le Développement (IRD)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut Français Pondicherry

Subjects
0106 biological sciences, Architectural analysis, Root (linguistics), Vegetative reproduction, Dioscoreaceae, Agricultural management, Soil Science, F62 - Physiologie végétale - Croissance et développement, Plant Science, Root system, Biology, Dioscorea rotundata, Development, 01 natural sciences, F50 - Anatomie et morphologie des plantes, Botany, ComputingMilieux_MISCELLANEOUS, Dioscorea rotundata poir, [SDE.BE.BIOI]Environmental Sciences/Biodiversity and Ecology/domain_sde.be.bioi, Tuber, Root functions, Developmental cycle, 04 agricultural and veterinary sciences, 15. Life on land, [SDV.BV.BOT]Life Sciences [q-bio]/Vegetal Biology/Botanics, biology.organism_classification, F02 - Multiplication végétative des plantes, Root, [SDE]Environmental Sciences, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, 010606 plant biology & botany
Abstract

A-09-11; International audience; Architectural descriptors were used to understand root system structure and development in white yam (Dioscorea rotundata Poir., Dioscoreaceae), a tuber monocot. Observations were made on seedlings and plant derived from tuber fragments, cultivated in greenhouses over a developmental cycle. This study demonstrated that both seedlings and plants derived from tubers have two distinct root systems that are highly organized. The first (seminal or tubercular) has been called the temporary root system which is small and short lived. The architectural unit here is made up of two root axis categories. The second (adventitious in both cases) has been called the definitive root system. It is larger and has a far longer lifespan than temporary root systems. The architectural unit here is made up of three root axis categories. Adventitious root systems are formed by structural repetitions of their own architectural unit. The temporary and definitive root systems possess the same structural and functional properties and become established and succeed one another in time following an identical developmental sequence. Neo tuber development is coupled with the root system development. Our results highlight to what extent it is important to study simultaneously the different parts of a root system in order to understand its development. This study confirms how architectural tools can be used to understand root system structure and development and prove accurate informations on root system development for use in agricultural management.

Published
2009
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19. Design of a UML profile for feature diagrams and its tooling implementation

Author

Thibaut Possompès, Christophe Dony, Marianne Huchard, Chouki Tibermacine, Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, Models And Reuse Engineering, Languages (MAREL), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), RIDER project, and Possompès, Thibaut

Subjects
UML profile, software product lines, Computer Science::Software Engineering, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, model driven engineering, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, profile tooling, Feature diagrams
Abstract

International audience; This paper proposes an instrumented solution to integrate feature diagrams with UML models to be used as part of a general approach for designing software product lines and for product generation. The contribution is implemented in IBM Rational Software Architect (RSA). It is intended to be used in the context of large, complex and multi-domain projects, and at allowing model transformations to derive products. Our RSA implementation makes it possible to link feature diagrams with UML model artifacts. It allows traceability between feature models and other different kinds of models (requirements, class diagrams, sequence or activity diagrams, etc.). It is used in a project dedicated to create smart building optimization systems.

20. 3d visualization of particle system with extracted data from sensors

Author

Nancy Rodriguez, Benoit Lange, William Puech, Hervé Rey, Xavier Vasques, Image & Interaction (ICAR), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), IBM PSSC Montpellier - Innovation Lab., IBM PSSC Montpellier, FUI RIDER, and Rodriguez, Nancy

Subjects
[INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR], [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]
Abstract

International audience; This paper deals with 3D visualization and interaction techniques used to analyze data necessary to manage energy consumption. Data comes from sensors located in a green data center in the IBM Montpellier (France) site. The main goal of this work is to visualize, in real-time, the large amount of data produced by different sensors in the data center. A visualization engine has been developed to understand the data extracted from sensors. This engine is based on a particle system which allows representation of the room's interior. Data centers are large warehouse servers, which represent a gap in building's energy consumption. In this paper we present a visual method developed to improve energy management of data center by supporting IT architects activities. Our system use sensors to monitor data center, and allows visualizing temperature air flow. We use 3D models and several multiresolution visualization methods to allow our system to be deployed in different devices.

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