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    Remote Large Data Visualization in the ParaView Framework

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    163-170.pdf (662.4Kb)
    Date
    2006
    Author
    Cedilnik, Andy
    Geveci, Berk
    Moreland, Kenneth
    Ahrens, James ORCID
    Favre, Jean
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    Abstract
    Scientists are using remote parallel computing resources to run scientific simulations to model a range of scientific problems. Visualization tools are used to understand the massive datasets that result from these simulations. A number of problems need to be overcome in order to create a visualization tool that effectively visualizes these datasets under this scenario. Problems include how to effectively process and display massive datasets and how to effectively communicate data and control information between the geographically distributed computing and visualization resources. We believe a solution that incorporates a data parallel data server, a data parallel rendering server and client controller is key. Using this data server, render server, client model as a basis, this paper describes in detail a set of integrated solutions to remote/distributed visualization problems including presenting an efficient M to N parallel algorithm for transferring geometry data, an effective server interface abstraction and parallel rendering techniques for a range of rendering modalities including tiled display walls and CAVEs.
    BibTeX
    @inproceedings {10.2312:EGPGV:EGPGV06:163-170,
    booktitle = {Eurographics Symposium on Parallel Graphics and Visualization},
    editor = {Alan Heirich and Bruno Raffin and Luis Paulo dos Santos},
    title = {{Remote Large Data Visualization in the ParaView Framework}},
    author = {Cedilnik, Andy and Geveci, Berk and Moreland, Kenneth and Ahrens, James and Favre, Jean},
    year = {2006},
    publisher = {The Eurographics Association},
    ISSN = {1727-348X},
    ISBN = {3-905673-40-1},
    DOI = {10.2312/EGPGV/EGPGV06/163-170}
    }
    URI
    http://dx.doi.org/10.2312/EGPGV/EGPGV06/163-170
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA