Remote Large Data Visualization in the ParaView Framework

Files

163-170.pdf (662.4 KB)

Date

2006

Authors

Cedilnik, Andy
Geveci, Berk
Moreland, Kenneth
Ahrens, James
Favre, Jean

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.

        @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
}
}