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A Hadoop Use Case for Engineering Data

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Cooperative Design, Visualization, and Engineering (CDVE 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9320))

Abstract

This paper presents the VELaSSCo project (Visualization for Extremely LArge-Scale Scientific Computing). It aims to develop a platform to manipulate scientific data used by FEM (Finite Element Method) and DEM (Discrete Element Method) simulations. The project focuses on the development of a distributed, heterogeneous and high-performance platform, enabling the scientific communities to store, process and visualize huge amounts of data. The platform is compatible with current hardware capabilities, as well as future hardware.

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Notes

  1. 1.

    http://cloudtimes.org/2013/11/06/idc-report-hadoop-leads-the-big-data-analytics-tool-for-enterprises/.

  2. 2.

    http://research.microsoft.com/en-us/projects/dryad/.

  3. 3.

    http://www.i-fx.net.

  4. 4.

    http://www.gidhome.com.

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Acknowledgments

This work is supported in part by the EC for the FP7 project VELaSSCo, project number 619439, Call FP7-ICT-2013-11. We thank all the members of the consortium: CIMNE (SP, Coordinator), University of Edinburgh (UK), SINTEF (No.), Fraunhofer IGD (D), JOTNE (No.) and ATOS (SP) for their invaluable contributions and for many fruitful discussions.

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Authors and Affiliations

  1. INRIA Rhône-Alpes, 38334, Saint-Ismier, France

    Benoit Lange & Toan Nguyen

Authors
  1. Benoit Lange
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  2. Toan Nguyen
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Corresponding author

Correspondence to Toan Nguyen .

Editor information

Editors and Affiliations

  1. University of Balearic Islands, Palma de Mallorca, Spain

    Yuhua Luo

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Lange, B., Nguyen, T. (2015). A Hadoop Use Case for Engineering Data. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2015. Lecture Notes in Computer Science(), vol 9320. Springer, Cham. https://doi.org/10.1007/978-3-319-24132-6_16

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  • DOI: https://doi.org/10.1007/978-3-319-24132-6_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24131-9

  • Online ISBN: 978-3-319-24132-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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