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mpiP: Lightweight MPI profiling

Blaise Barney, LLNL ASC Tri-Lab Code Development Tools Workshop Thursday, July 29, 2010. mpiP: Lightweight MPI profiling. Lawrence Livermore National Laboratory, P. O. Box 808, Livermore, CA 94551.

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mpiP: Lightweight MPI profiling

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  1. Blaise Barney, LLNL ASC Tri-Lab Code Development Tools Workshop Thursday, July 29, 2010 mpiP: Lightweight MPI profiling Lawrence Livermore National Laboratory, P. O. Box 808, Livermore, CA 94551 This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 LLNL-PRES-426112

  2. Simple, scalable, portable MPI profiling • How to simplify initial performance analysis • Simple, reliable, low learning overhead • Focus on important, yet easy to access information • mpiP MPI profiling library provides a portable, direct, low-overhead tool for measuring MPI behavior • To use mpiP: • First: "use mpip" • re-link with (or pre-load) the mpiP library • run the application • examine summary or detailed results • text report • GUI browser

  3. How does it work? • MPI calls are intercepted by mpiP wrappers • mpiP wrappers call PMPI functions • All information is task-local • Report generation is done • within MPI_Finalize • arbitrarily (by all tasks) • Task data can be collected quickly by a single collector task or by using MPI collectives

  4. Usage • First: "use mpip" • Re-link application with mpiP library. Example: -L/usr/local/tools/mpip/lib –lmpiP –lbfd –liberty -lunwind • Run-time insertion • srun-mpip or mpirun-mpip script • LD_PRELOAD=/usr/local/tools/mpip/lib/libmpiP.so • Run-time parameters set in MPIP environment variable. Some examples:

  5. How to examine performance data? • Various report formats • Verbose, task-specific information • Concise, omits task-specific detail • Modify report output • Use MPIP environment variable • Filter MPI call sites • Select concise or verbose format or both • Omit task-specific data

  6. How to examine performance data? • Various report sections • Per-task MPI use

  7. How to examine performance data? • Various report sections • Indexed list of MPI routine call locations

  8. How to examine performance data? • Various report sections • Concise, top 20 MPI call sites, by wall clock time

  9. How to examine performance data? • Various report sections • Concise, top 20 MPI call sites, by message volume

  10. How to examine performance data? • Various report sections • Verbose, task-specific information, by wall clock time (shown) and message volume (similar, but not shown)

  11. How to examine performance data? • View report files using the Tool Gear GUI browser. • "use mpipview" then "mpipview mpipoutputfile"

  12. Availability • LLNL • “use mpip” first • Library in /usr/local/tools/mpip/lib • Supported on most production platforms • SNL • Module load tools/mpiP-3.2.0 • /projects/tools_workshop/mpiP

  13. Advanced Topics • MPI_Pcontrol can control mpiP behavior • Example C: MPI_Pcontrol(3); MPI_Pcontrol(2);

  14. References • Initially developed by Jeffrey Vetter and Michael McCracken at LLNL • Version 3.2 released, includes RMA support • Other project members • Philip Roth (ORNL) • Jeffrey Vetter (ORNL) • Tool Gear: John Gyllenhaal (LLNL) & John May (LLNL) • http://computation.llnl.gov/casc/tool_gear/ • Tool POC : Chris Chambreau chcham@llnl.gov • Tool mail list : mpip-help@lists.sourceforge.net • Tool web site: http://mpip.sourceforge.net/

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