Andy Cedilnik, Berk Geveci, Kenneth Moreland, James Ahrens, and Jean Favre. "Remote Large Data Visualization in the ParaView Framework." In Eurographics Parallel Graphics and Visualization 2006, pg. 163–170, May 2006.
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.
Full Paper
Remote Large Data Visualization in the ParaView Framework
Software
The software is easily retrieved by downloading ParaView.