Researchers: Charles Zhang, Jason Leigh, Rajvikram Singh
TeraScope is a massively parallelized set of information visualization tools for Visual Data Mining. TeraScope enables researchers to interactively navigate and visualize more than a terabyte of data either on a tiled display or on a desktop workstation.
TeraScope consists of new algorithms and tools to interactively query and mine terabyte datasets, correlate the data, and then visualize the data using parallelized rendering software on tiled displays. TeraScope’s main foci are to develop techniques for creating TeraMaps (visualizations that summarize rather than plot enormous datasets) and to develop a distributed memory cache (called OptiMem) that collects pools of memory from optically connected computer clusters, or TeraNodes. These caches are used by TeraScope to bridge the impedance mismatch between large and slow distributed data stores and fast local memory.
Currently TeraScope is designed to work with Project DataSpace’s distributed data servers; however, it can be adapted to work with other database systems. DataSpace is an infrastructure for the publication, analysis and mining of business, e-business, scientific, engineering, and health care data, developed by the University of Illinois at Chicago’s National Center for Data Mining.
Date: August 1, 2001 - August 1, 2002