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
Link To Document :
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