A scalable approach to MPI application performance analysis

Authors:
Shirley Moore;Felix Wolf;Jack Dongarra;Sameer Shende;Allen Malony;Bernd Mohr
Affiliations:
Innovative Computing Laboratory, University of Tennessee, Knoxville, TN;Innovative Computing Laboratory, University of Tennessee, Knoxville, TN;Innovative Computing Laboratory, University of Tennessee, Knoxville, TN;Computer Science Department, University of Oregon, Eugene, OR;Computer Science Department, University of Oregon, Eugene, OR;Forschungszentrum Jülich, ZAM, Jülich, Germany
Venue:
PVM/MPI'05 Proceedings of the 12th European PVM/MPI users' group conference on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Year:
2005

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Abstract

A scalable approach to performance analysis of MPI applications is presented that includes automated source code instrumentation, low overhead generation of profile and trace data, and database management of performance data. In addition, tools are described that analyze large-scale parallel profile and trace data. Analysis of trace data is done using an automated pattern-matching approach. Examples of using the tools on large-scale MPI applications are presented.