NDLI: In-situ multi-resolution and temporal data compression for visual exploration of large-scale scientific simulations

Content Provider	IEEE Xplore Digital Library
Author	Lehmann, Henry Jung, Bernhard
Copyright Year	2014
Description	Author affiliation: Virtual Reality and Multimedia Group, Technical University Bergakademie Freiberg, Germany (Lehmann, Henry; Jung, Bernhard)
Abstract	Today's large-scale scientific simulations generate massive data sets that pose challenges both for data storage in HPC environments during the simulation phase and the subsequent data analysis phase. A promising approach for reducing the amount of data written out during simulation run is in-situ compression. However, even the compressed data sets are typically still too large for interactive visual data exploration which calls for multi-resolution data layouts. The recently proposed ISABELA method for lossy in-situ compression was shown to outperform other compression methods for scientific data sets. In this paper, we propose two main extensions to the ISABELA method: (1) an interlaced data layout that supports decompression of multi-resolution views of the data without overhead in the compressed format; (2) a new temporal compression scheme for improving the compression rate by exploiting temporal coherence in the data set. The compressed multi-resolution data can easily be transformed to the VTK AMR (adaptive multi-resolution) data format to support interactive exploration in ParaView and other visualization tools based on VTK. During the simulation phase, there is no significant increase of computational demands for the generation of complete multi-resolution compressed data sets as compared to flat ISABELA compression. During the analysis phase, due to the AMR data layout, our method supports selective loading of regions of interests as well as progressive loading of data sets, thus enabling interactive visualizations of large-scale scientific simulations.
Starting Page	51
Ending Page	58
File Size	2966563
Page Count	8
File Format	PDF
ISBN	9781479952151
DOI	10.1109/LDAV.2014.7013204
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-11-09
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Adaptation models In-situ compression High-performance computing Abstracts Approximation algorithms Time-dependent scientific data Indexes Approximation methods Splines (mathematics) Multi-resolution visualization Signal resolution
Content Type	Text
Resource Type	Article

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