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2010
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PreDatA - preparatory data analytics on peta-scale machines

8 years 9 months ago
PreDatA - preparatory data analytics on peta-scale machines
Peta-scale scientific applications running on High End Computing (HEC) platforms can generate large volumes of data. For high performance storage and in order to be useful to science end users, such data must be organized in its layout, indexed, sorted, and otherwise manipulated for subsequent data presentation, visualization, and detailed analysis. In addition, scientists desire to gain insights into selected data characteristics `hidden' or `latent' in the massive datasets while data is being produced by simulations. PreDatA, short for Preparatory Data Analytics, is an approach for preparing and characterizing data while it is being produced by the large scale simulations running on peta-scale machines. By dedicating additional compute nodes on the peta-scale machine as staging nodes and staging simulation's output data through these nodes, PreDatA can exploit their computational power to perform selected data manipulations with lower latency than attainable by first m...
Fang Zheng, Hasan Abbasi, Ciprian Docan, Jay F. Lo
Added 13 Feb 2011
Updated 13 Feb 2011
Type Journal
Year 2010
Where IPPS
Authors Fang Zheng, Hasan Abbasi, Ciprian Docan, Jay F. Lofstead, Qing Liu, Scott Klasky, Manish Parashar, Norbert Podhorszki, Karsten Schwan, Matthew Wolf
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