• DocumentCode
    229063
  • Title

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

  • Author

    Lehmann, Hartmut ; Jung, Byung-Ik

  • Author_Institution
    Virtual Reality & Multimedia Group, Tech. Univ. Bergakad. Freiberg, Freiberg, Germany
  • fYear
    2014
  • fDate
    9-10 Nov. 2014
  • Firstpage
    51
  • Lastpage
    58
  • 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.
  • Keywords
    computational geometry; data compression; data visualisation; interactive systems; parallel processing; scientific information systems; AMR data layout; HPC environments; ISABELA method; ParaView visualization tool; VTK AMR data format; adaptive multiresolution data format; compressed data sets; compressed multiresolution data; compression rate improvement; data analysis phase; data storage; in-situ compression; in-situ multiresolution; interactive exploration; interactive visual data exploration; interactive visualizations; interlaced data layout; large-scale scientific simulations; lossy in-situ compression; multiresolution data layouts; multiresolution data view decompression; progressive data set loading; scientific data sets; selective region-of-interest loading; simulation phase; temporal coherence; temporal compression scheme; temporal data compression; visual exploration; Abstracts; Adaptation models; Approximation algorithms; Approximation methods; Indexes; Signal resolution; Splines (mathematics); high-performance computing; in-situ compression; multi-resolution visualization; time-dependent scientific data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Large Data Analysis and Visualization (LDAV), 2014 IEEE 4th Symposium on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/LDAV.2014.7013204
  • Filename
    7013204