Detecting phases in parallel applications on shared memory architectures

Erez Perelman, Marzia Polito, Jean Yves Bouguet, John Sampson, Brad Calder, Carole Dulong

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

49 Scopus citations

Abstract

Most programs are repetitive, where similar behavior can be seen at different execution times. Algorithms have been proposed that automatically group similar portions of a program's execution into phases, where samples of execution in the same phase have homogeneous behavior and similar resource requirements. In this paper, we examine applying these phase analysis algorithms and how to adapt them to parallel applications running on shared memory processors. Our approach relies on a separate representation of each thread's activity. We first focus on showing its ability to identify similar intervals of execution across threads for a single run. We then show that it is effective at identifying similar behavior of a program when the number of threads is varied between runs. This can be used by developers to examine how different phases scale across different number of threads. Finally, we examine using the phase analysis to pick simulation points to guide multithreaded simulation.

Original languageEnglish (US)
Title of host publication20th International Parallel and Distributed Processing Symposium, IPDPS 2006
PublisherIEEE Computer Society
ISBN (Print)1424400546, 9781424400546
DOIs
StatePublished - Jan 1 2006
Event20th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2006 - Rhodes Island, Greece
Duration: Apr 25 2006Apr 29 2006

Publication series

Name20th International Parallel and Distributed Processing Symposium, IPDPS 2006
Volume2006

Other

Other20th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2006
CountryGreece
CityRhodes Island
Period4/25/064/29/06

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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