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A Cluster Infrastructure to Support Retrieval, Management and Visualization of Massive Amounts of Data

$116,000FY2004CSENSF

University Of Utah, Salt Lake City UT

Investigators

Abstract

This project, developing an infrastructure for data intensive applications, aims at establishing a cluster and display-wall infrastructure to facilitate experimental research in systems that support retrieval, querying, modeling, and visualization of massive amounts of data in a broad range of scenarios. The infrastructure, consisting of a cluster of graphics-capable workstation with fast network infrastructure, a high-resolution display wall, and a dedicated file server, supports three research projects: Exploiting the Hidden Web, Large Scientific Visualization, and Modeling and Rendering Large 3D Environments. The first project searches, indexes, and queries the hidden Web data. Often crawlers, which visit pages by following hyperlinks, cannot find needed information without searching the individual sites. This project develops techniques to enable a crawler to navigate through hidden pages, building a search engine that allows these data to be queried. The second relates to the development of visualization technology that is suitable for very large scientific datasets. This research includes the development of out-of-core algorithms for scientific visualization, parallel graphics and scalable-display technology, novel rendering algorithms, and better visualization modeling primitives. The project expects to build visualization systems that effectively decouple the visualization requirements from the available hardware resources, allowing visualization of arbitrarily large datasets on any reasonable device. The third project looks into models of real-world objects and scenes from which applications such as entertaining, training and simulation, special effects, analysis of forensic records, telepresence, and remote walkthroughs can benefit. This work requires tackling expensive optimization problems related to registering and cleaning raw data, and high-resolution display for real-time rendering. This infrastructure enables the establishing of a lab in Visualization and Geometric Computing and WebDB; which in turn will benefit many students. An outreach component is in place; the research currently supports several female and minorities. Moreover, two new related courses are under development

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