• DocumentCode
    1917719
  • Title

    Abstract: Exploring Performance Data with Boxfish

  • Author

    Isaacs, Katherine E. ; Landge, Aaditya G. ; Gamblin, Todd ; Bremer, Peer-Timo ; Pascucci, V. ; Hamann, Bernd

  • Author_Institution
    Dept. of Comput. Sci., Univ. of California, Davis, Davis, CA, USA
  • fYear
    2012
  • fDate
    10-16 Nov. 2012
  • Firstpage
    1380
  • Lastpage
    1381
  • Abstract
    The growth in size and complexity of scaling applications and the systems on which they run pose challenges in analyzing and improving their overall performance. With metrics coming from thousands or millions of processes, visualization techniques are necessary to make sense of the increasing amount of data. To aid the process of exploration and understanding, we announce the initial release of Boxfish, an extensible tool for manipulating and visualizing data pertaining to application behavior. Combining and visually presenting data and knowledge from multiple domains, such as the application´s communication patterns and the hardware´s network configuration and routing policies, can yield the insight necessary to discover the underlying causes of observed behavior. Boxfish allows users to query, filter and project data across these domains to create interactive, linked visualizations.
  • Keywords
    data visualisation; information filtering; query processing; Boxfish; application behavior; application communication patterns; data filtering; data manipulation; data projection; data visualization; hardware network configuration; interactive visualizations; linked visualizations; performance data exploration; query; routing policies; visualization techniques;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    High Performance Computing, Networking, Storage and Analysis (SCC), 2012 SC Companion:
  • Conference_Location
    Salt Lake City, UT
  • Print_ISBN
    978-1-4673-6218-4
  • Type

    conf

  • DOI
    10.1109/SC.Companion.2012.202
  • Filename
    6495985