Remote Large Data Visualization in the ParaView Framework

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Date
2006
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
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.
Description

        
@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
} }
Citation