Using the Data Capacitor for Remote Data Collection, Analysis, and Visualization

dc.altmetrics.displaytrue
dc.contributor.authorSimms, Stephen C.
dc.contributor.authorDavy, Matthew
dc.contributor.authorHammond, Bret
dc.contributor.authorLink, Matthew R.
dc.contributor.authorStewart, Craig A.
dc.contributor.authorTeige, Scott
dc.contributor.authorBaik, Mu-Hyun
dc.contributor.authorMantri, Yogita
dc.contributor.authorLord, Richard
dc.contributor.authorMcMullen, D.F. (Rick)
dc.contributor.authorHuffman, John C.
dc.contributor.authorHuffman, Kia
dc.contributor.authorJuckeland, Guido
dc.contributor.authorKluge, Michael
dc.contributor.authorHenschel, Robert
dc.contributor.authorBrunst, Holger
dc.contributor.authorKnuepfer, Andreas
dc.contributor.authorMueller, Matthias
dc.contributor.authorMukund, P.R.
dc.contributor.authorElble, Andrew
dc.contributor.authorPasupuleti, Ajay
dc.contributor.authorBohn, Richard
dc.contributor.authorDas, Sripriya
dc.contributor.authorStefano, James
dc.contributor.authorPike, Gregory G.
dc.contributor.authorBalog, Douglas A.
dc.date.accessioned2011-12-19T20:14:50Z
dc.date.available2011-12-19T20:14:50Z
dc.date.issued2007-11-13
dc.descriptionPresentation 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.
dc.description.abstractIndiana 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.
dc.identifier.urihttps://hdl.handle.net/2022/13991
dc.language.isoen_US
dc.relation.isversionofhttp://sc07.supercomputing.org/schedule/event_detail.php?evid=11464
dc.titleUsing the Data Capacitor for Remote Data Collection, Analysis, and Visualization
dc.typePresentation

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