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A Distributed Memory Hierarchy and Data Management for Interactive Scene Navigation and Modification on Tiled Display Walls

Abstract

This dissertation addresses a growing challenge of visualizing and modifying massive 3D geometric models in a collaborative workspace by presenting a new scalable data partitioning algorithm in conjunction with a robust system architecture. The goal is to motivate the idea that utilizing a distributed architecture may solve many performance related challenges in visualization of large 3D data. Drawing data from modeling, simulation, interaction and data fusion to deliver a starting point for scientific discovery, we present a collaborative visual analytics framework providing the abilities to render, display and interact with data at a massive scale on high resolution collaborative display environments. This framework allows users to connect to data when it is needed, where it is needed, and in a format suitable for productivity while providing a means to interactively define a workspace that suits one's need. The presented framework uses a distributed architecture to display content on tiled display walls of arbitrary shape, size, and resolution. These techniques manage the data storage, the communication, and the interaction between many processing nodes that make up the display wall. This hides the complexity from the user while offering an intuitive mean to interact with the system. Multi-modal methods are presented that enables the user to interact with the system in a natural way from hand gesture to laser pointer. The combination of this scalable display method with the natural interaction modality provides a robust foundation to facilitate a multitude of visualization and interaction applications.

The final output from the system is an image on a large display made up of either projection or lcd based displays. Such a system will have many different components working together in parallel to produce an output. By incorporating computer graphics theory with classical parallel processing techniques, performance limitations typically associated with the display of large or numerous items on multiple display devices and multiple input sources are overcome.

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