Type of Document	Master's Thesis
Author	Sharma, Ashish
Author's Email Address	asharm2@lsu.edu
URN	etd-0410102-151815
Title	Techniques and Algorithms for Immersive and Interactive Visualization of Large Datasets
Degree	Master of Science in Systems Science (M.S.S.S.)
Department	Computer Science
Advisory Committee	Advisor Name Title Aiichiro Nakano Committee Chair Don Kraft Committee Member S. Sitharama Iyengar Committee Member
Keywords	distributed visibility culling parallel
Date of Defense	2001-11-15
Availability	unrestricted
Abstract Advances in computing power have made it possible for scientists to perform atomistic simulations of material systems that range in size, from a few hundred thousand atoms to one billion atoms. An immersive and interactive walkthrough of such datasets is an ideal method for exploring and understanding the complex material processes in these simulations. However rendering such large datasets at interactive frame rates is a major challenge. A scalable visualization platform is developed that is scalable and allows interactive exploration in an immersive, virtual environment. The system uses an octree based data management system that forms the core of the application. This reduces the amount of data sent to the pipeline without a per-atom analysis. Secondary algorithms and techniques such as modified occlusion culling, multiresolution rendering and distributed computing are employed to further speed up the rendering process. The resulting system is highly scalable and is capable of visualizing large molecular systems at interactive frame rates on dual processor SGI Onyx2 with an InfinteReality2 graphics pipeline.
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