Multi-Resolution Modeling of Large Scale Scientific Simulation Data [electronic resource].

Published:: Washington, D.C. : United States. Dept. of Energy, 2003.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
Physical Description:: PDF-file: 7 pages; size: 0.3 Mbytes
Additional Creators:: Lawrence Berkeley National Laboratory
United States. Department of Energy
United States. Department of Energy. Office of Scientific and Technical Information
Access Online:: www.osti.gov

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Summary:: This paper discusses using the wavelets modeling technique as a mechanism for querying large-scale spatio-temporal scientific simulation data. Wavelets have been used successfully in time series analysis and in answering surprise and trend queries. Our approach however is driven by the need for compression, which is necessary for viable throughput given the size of the targeted data, along with the end user requirements from the discovery process. Our users would like to run fast queries to check the validity of the simulation algorithms used. In some cases users are welling to accept approximate results if the answer comes back within a reasonable time. In other cases they might want to identify a certain phenomena and track it over time. We face a unique problem because of the data set sizes. It may take months to generate one set of the targeted data; because of its shear size, the data cannot be stored on disk for long and thus needs to be analyzed immediately before it is sent to tape. We integrated wavelets within AQSIM, a system that we are developing to support exploration and analyses of tera-scale size data sets. We will discuss the way we utilized wavelets decomposition in our domain to facilitate compression and in answering a specific class of queries that is harder to answer with any other modeling technique. We will also discuss some of the shortcomings of our implementation and how to address them.
Note:: Published through SciTech Connect.
01/31/2003.
"ucrl-jc-147225"
15th International Conference on Scientific and Statistical, Cambridge, MA, Jul 09 - Jul 11, 2003.
Critchlow, T; Abdulla, G; Baldwin, C.
Funding Information:: W-7405-ENG-48

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