Reconciling sampling and direct instrumentation for unintrusive call-path profiling of MPI programs

Zoltán Szebenyi, Todd Gamblin, Martin Schulz, Bronis R. De Supinski, Felix Wolf, Brian J.N. Wylie

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations

Abstract

We can profile the performance behavior of parallel programs at the level of individual call paths through sampling or direct instrumentation. While we can easily control measurement dilation by adjusting the sampling frequency, the statistical nature of sampling and the difficulty of accessing the parameters of sampled events make it unsuitable for obtaining certain communication metrics, such as the size of message payloads. Alternatively, direct instrumentation, which is preferable for capturing message-passing events, can excessively dilate measurements, particularly for C++ programs, which often have many short but frequently called class member functions. Thus, we combine these techniques in a unified framework that exploits the strengths of each approach while avoiding their weaknesses: We use direct instrumentation to intercept MPI routines while we record the execution of the remaining code through low-overhead sampling. One of the main technical hurdles mastered was the inexpensive and portable determination of call-path information during the invocation of MPI routines. We show that the overhead of our implementation is sufficiently low to support substantial performance improvement of a C++ fluid-dynamics code.

Original languageEnglish
Title of host publicationProceedings - 25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011
Pages640-651
Number of pages12
DOIs
StatePublished - 2011
Externally publishedYes
Event25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011 - Anchorage, AK, United States
Duration: 16 May 201120 May 2011

Publication series

NameProceedings - 25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011

Conference

Conference25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011
Country/TerritoryUnited States
CityAnchorage, AK
Period16/05/1120/05/11

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