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dc.contributor.author Simms, Stephen C.
dc.contributor.author Davy, Matthew
dc.contributor.author Hammond, Bret
dc.contributor.author Link, Matthew R.
dc.contributor.author Stewart, Craig A.
dc.contributor.author Teige, Scott
dc.contributor.author Baik, Mu-Hyun
dc.contributor.author Mantri, Yogita
dc.contributor.author Lord, Richard
dc.contributor.author McMullen, D.F. (Rick)
dc.contributor.author Huffman, John C.
dc.contributor.author Huffman, Kia
dc.contributor.author Juckeland, Guido
dc.contributor.author Kluge, Michael
dc.contributor.author Henschel, Robert
dc.contributor.author Brunst, Holger
dc.contributor.author Knuepfer, Andreas
dc.contributor.author Mueller, Matthias
dc.contributor.author Mukund, P.R.
dc.contributor.author Elble, Andrew
dc.contributor.author Pasupuleti, Ajay
dc.contributor.author Bohn, Richard
dc.contributor.author Das, Sripriya
dc.contributor.author Stefano, James
dc.contributor.author Pike, Gregory G.
dc.contributor.author Balog, Douglas A.
dc.date.accessioned 2011-12-19T20:14:50Z
dc.date.available 2011-12-19T20:14:50Z
dc.date.issued 11/13/2007
dc.identifier.uri http://sc07.supercomputing.org/schedule/event_detail.php?evid=11464 en
dc.identifier.uri http://hdl.handle.net/2022/13991
dc.description Presentation given as Bandwidth Challenge Finalist at SC07. This team led by Indiana University, with partners from the Technische Universitaet Dresden, Rochester Institute of Technology, Oak Ridge National Laboratory and the Pittsburgh Supercomputing Center, was awarded first place in an international competition for leading-edge, high-bandwidth computing applications. en
dc.description.abstract Indiana University provides powerful compute, storage, and network resources to a diverse local and national research community. In the past year, through the use of Lustre across the wide area network, IU has been able to extend the reach of its advanced cyberinfrastructure across the nation and across the ocean to Technische Universitaet Dresden. For this year's bandwidth challenge, a handful of researchers from IU, Rochester Institute of Technology, and the Technische Universitaet Dresden will run a set of data-intensive applications crossing a range of disciplines from the digital humanities to computational chemistry. Using IU's 535 TB Data Capacitor and an additional component installed on the exhibit floor, we will mount Lustre across the wide area network to demonstrate data collection, analysis, and visualization across distance. en
dc.language.iso en_US en
dc.title Using the Data Capacitor for Remote Data Collection, Analysis, and Visualization en
dc.type Presentation en
dc.altmetrics.display true en_US


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