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dc.contributor.authorCedilnik, Andyen_US
dc.contributor.authorGeveci, Berken_US
dc.contributor.authorMoreland, Kennethen_US
dc.contributor.authorAhrens, Jamesen_US
dc.contributor.authorFavre, Jeanen_US
dc.contributor.editorAlan Heirich and Bruno Raffin and Luis Paulo dos Santosen_US
dc.date.accessioned2014-01-26T16:30:50Z
dc.date.available2014-01-26T16:30:50Z
dc.date.issued2006en_US
dc.identifier.isbn3-905673-40-1en_US
dc.identifier.issn1727-348Xen_US
dc.identifier.urihttp://dx.doi.org/10.2312/EGPGV/EGPGV06/163-170en_US
dc.description.abstractScientists 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.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.1 [Computer Graphics]: Parallel Processingen_US
dc.titleRemote Large Data Visualization in the ParaView Frameworken_US
dc.description.seriesinformationEurographics Symposium on Parallel Graphics and Visualizationen_US


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