The Framework for Approximate Queries on Simulation Data
B. Lee, R. Snapp
Department of Computer Science
University of Vermont
{bslee, snap}@cs.uvm.edu
T. Critchlow, G. Abdulla, C. Baldwin, R. Kamimura, N. Tang
Center for Applied Scientific Computing
Lawrence Livermore National Laboratory
P.O. Box 808, L-561, Livermore, CA 94551
{critchlow, abdulla1, baldwin5, kamimura1, tangn}@llnl.gov
Ron Musick*
iKuni, Inc
Palo Alto, CA 94304
musick@ikuni.com
Abstract
AQSim is a system intended to enable scientists to query and analyze a
large volume of scientific simulation data. The system uses the state
of the art in approximate query processing techniques to build a novel
framework for progressive data analysis. These techniques are used to
define a multi-resolution index, where each node contains multiple
models of the data. The benefits of these models are two-fold: 1) the
are compact representations, reconstructing only the information
relevant to the analysis, and 2) the variety of models capture
different aspects of the data which may be of interest to the user but
are not readily apparent in their raw form. To be able to deal with
the data interactively, AQSim allows the scientist to make an informed
tradeoff between query response accuracy and time. In this paper, we
present the framework of AQSim with a focus on its architectural
design. We also show the results from an initial proof-of-concept
prototype developed at LLNL. The presented framework is generic
enough to handle other most types of simulation data, and other
classes of scientific data as well.
Appeared in
Information Sciences, Volume 157, Spring 2003.
Look at the Paper (pdf.gz)
* Work done while author at
Center for Applied Scientific Computing
Lawrence Livermore National Laboratory
P.O. Box 808, L-561, Livermore, CA 94551