Carnegie Mellon University
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Data-Intensive Supercomputing: The Case for DISC

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journal contribution
posted on 2006-01-01, 00:00 authored by Randal E. Bryant
Google and its competitors have created a new class of large-scale computer systems to support Internet search. These “Data-Intensive Super Computing” (DISC) systems differ from conventional supercomputers in their focus on data: they acquire and maintain continually changing data sets, in addition to performing large-scale computations over the data. With the massive amounts of data arising from such diverse sources as telescope imagery,medical records, online transaction records, and web pages, DISC systems have the potential to achieve major advances in science, health care, business efficiencies, and information access. DISC opens up many important research topics in system design, resource management, programming models, parallel algorithms, and applications. By engaging the academic research community in these issues, we can more systematically and in a more open forum explore fundamental aspects of a societally important style of computing




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