Exploring performance data with boxfish

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings - 2012 SC Companion
Subtitle of host publicationHigh Performance Computing, Networking Storage and Analysis, SCC 2012
Pages1380-1381
Number of pages2
DOIs
StatePublished - Dec 1 2012
Externally publishedYes
Event2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012 - Salt Lake City, UT, United States
Duration: Nov 10 2012Nov 16 2012

Publication series

NameProceedings - 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012

Conference

Conference2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012
CountryUnited States
CitySalt Lake City, UT
Period11/10/1211/16/12

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software

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