What is VAMPIR, and where is it installed at IU?

VAMPIR is a tool set for analyzing the performance and message-passing characteristics of parallel applications.

VAMPIR has a graphical analysis framework that provides a large set of chart representations of event-based performance data generated through source code instrumentation. Developers can use these graphical displays, including state diagrams, statistics, and timelines, to obtain a better understanding of the inner workings of their parallel programs and how to optimize them.

VAMPIR has a simple and intuitive way of presenting large numbers of performance events. Powerful zooming and scrolling functionality allows you to quickly extract performance characteristics of your code at any desired level of detail. Most displays provide additional context information and customization options.

Extensive filtering capabilities for processes, functions, messages, and collective operations help to identify interesting hot spots in the overall collection of information. Individual displays can be coupled, with automatic statistic updates.

At Indiana University, VAMPIR is available on Big Red.

For information on how to use VAMPIR, see How do I use VAMPIR?

For more background information, see the VAMPIR web site.

For more information about the availability of software on the Indiana University shared central systems, see At IU, what software is available on the research computing systems?

This document was developed with support from National Science Foundation (NSF) grant OCI-1053575. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF.

This document is based upon work supported in part by National Science Foundation (NSF) grant 0910812 to Indiana University for "FutureGrid: An Experimental, High-Performance Grid Test-bed." FutureGrid project partners include the University of California - San Diego and the San Diego Supercomputer Center (SDSC), the University of Chicago/Argonne National Labs, the University of Florida, Purdue University, the University of Southern California, the University of Texas - Austin, and the Center for Information Services and High Performance Computing at Technische Universität Dresden.