Title page for ETD etd-0410102-151815


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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