Defining and Searching Communication Patterns in Event Graphs Using the g-Eclipse Trace Viewer Plugin

Thomas Köckerbauer () and Dieter Kranzlmüller ()
Additional contact information
Thomas Köckerbauer: Ludwig-Maximilans-Universität München (LMU), MNM-Team
Dieter Kranzlmüller: Ludwig-Maximilans-Universität München (LMU), MNM-Team

A chapter in Tools for High Performance Computing 2016, 2017, pp 23-40 from Springer

Abstract: Abstract The use of event graphs is a common approach to debug and analyze message passing parallel programs. Although event graphs are very useful for program understanding and debugging, they get confusing and hard to read for programs with complex communication behavior, long runtimes and a large numbers of processes. An approach to ease this problem is to simplify the event graph by marking occurrences of predefined well known communication structures. This allows to quickly identify different regions of activity in the event graph without further inspection. It also helps to identify parts, where certain communication patterns are expected but do not occur due to a bug in the parallel application, in this case the pattern might only match to a certain degree. In this paper we present a language for the description of such communication patterns, which allows to describe the patterns in a way that also covers variations in process numbers and process mappings. Furthermore it demonstrates a pattern matching plugin for the Trace Viewer of g-Eclipse which uses an specialized algorithm for detecting patterns in prerecorded event traces of parallel programs. Based on the presented approach a variety of improvements for the processing and presentation of event graphs are imaginable. The extracted pattern information could be used to optimize the analyzed program or to reduce the contents of the graph to areas of interest, by substituting non interesting parts by placeholders.

Date: 2017
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-56702-0_2

Ordering information: This item can be ordered from
http://www.springer.com/9783319567020

DOI: 10.1007/978-3-319-56702-0_2

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().