TeraScope: distributed visual data mining of terascale data sets over photonic networks

Authors:
Chong Zhang;Jason Leigh;Thomas A. DeFanti;Marco Mazzucco;Robert Grossman
Affiliations:
Electronic Visualization Laboratory, University of Illinois at Chicago, MC152, 1120 SEO, 851 S. Morgan Street, Chicago, IL;Electronic Visualization Laboratory, University of Illinois at Chicago, MC152, 1120 SEO, 851 S. Morgan Street, Chicago, IL;Electronic Visualization Laboratory, University of Illinois at Chicago, MC152, 1120 SEO, 851 S. Morgan Street, Chicago, IL;Laboratory for Advanced Computing (LAC), University of Illinois at Chicago, Chicago, IL;Laboratory for Advanced Computing (LAC), University of Illinois at Chicago, Chicago, IL
Venue:
Future Generation Computer Systems - iGrid 2002
Year:
2003

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Abstract

TeraScope is a framework and a suite of tools for interactively browsing and visualizing large terascale data sets. Unique to TeraScope is its utilization of the Optiputer paradigm to treat distributed computer clusters as a single giant computer, where the dedicated optical networks that connect the clusters serve as the computer's system bus. TeraScope explores one aspect of the Optiputer architecture by employing a distributed pool of memory, called LambdaRAM, that serves as a massive data cache for supporting parallel data mining and visualization algorithms.