SGI TPL (Linux: Developer/MPT_UG - Chapter 8. MPI Performance Profiling)

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Chapter 8. MPI Performance Profiling
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Chapter 8. MPI Performance Profiling

This chapter describes the perfcatch utility used to profile the performance of an MPI program. It covers the following topics:

For information on additional profiling tools, see “Using Profiling Tools with MPI Applications” in Chapter 6.

Overview of `perfcatch` Utility

The perfcatch utility runs an MPI program with a wrapper profiling library that prints MPI call profiling information to a summary file upon MPI program completion. This MPI profiling result file is called MPI_PROFILING_STATS, by default (see “ MPI_PROFILING_STATS Results File Example”). It is created in the current working directory of the MPI process with rank 0.

Using the `perfcatch` Utility

The syntax of the perfcatch utility is, as follows:

perfcatch [-v | -vofed | -i] cmd args

The perfcatch utility accepts the following options:

No option		Supports MPT
`-v`		Supports Voltaire MPI
`-vofed`		Supports Voltaire OFED MPI
`-i`		Supports Intel MPI

To use perfcatch with an SGI Message Passing Toolkit MPI program, insert the perfcatch command in front of the executable name. Here are some examples:

mpirun -np 64 perfcatch a.out arg1

and

mpirun host1 32, host2 64 perfcatch a.out arg1

To use perfcatch with Intel MPI, add the -i options. An example is, as follows:

mpiexec -np 64 perfcatch -i a.out arg1

For more information, see the perfcatch (1) man page.

`MPI_PROFILING_STATS` Results File Example

The MPI profiling result file has a summary statistics section followed by a rank-by-rank profiling information section. The summary statistics section reports some overall statistics, including the percent time each rank spent in MPI functions, and the MPI process that spent the least and the most time in MPI functions. Similar reports are made about system time usage.

The rank-by-rank profiling information section lists every profiled MPI function called by a particular MPI process. The number of calls and the total time consumed by these calls is reported. Some functions report additional information such as average data counts and communication peer lists.

An example MPI_PROFILING_STATS results file is, as follows:

============================================================
PERFCATCHER version 22 
(C) Copyright SGI.  This library may only be used
on SGI hardware platforms. See LICENSE file for
details.
============================================================
MPI program profiling information
Job profile recorded Wed Jan 17 13:05:24 2007
Program command line:                                /home/estes01/michel/sastest/mpi_hello_linux 
Total MPI processes                                  2

Total MPI job time, avg per rank                    0.0054768 sec
Profiled job time, avg per rank                     0.0054768 sec
Percent job time profiled, avg per rank             100%

Total user time, avg per rank                       0.001 sec
Percent user time, avg per rank                     18.2588%
Total system time, avg per rank                     0.0045 sec
Percent system time, avg per rank                   82.1648%

Time in all profiled MPI routines, avg per rank     5.75004e-07 sec
Percent time in profiled MPI routines, avg per rank 0.0104989%

Rank-by-Rank Summary Statistics
-------------------------------

Rank-by-Rank: Percent in Profiled MPI routines
        Rank:Percent
        0:0.0112245%    1:0.00968502%
  Least:  Rank 1      0.00968502%
  Most:   Rank 0      0.0112245%
  Load Imbalance:  0.000771%

Rank-by-Rank: User Time
        Rank:Percent
        0:17.2683%      1:19.3699%
  Least:  Rank 0      17.2683%
  Most:   Rank 1      19.3699%

Rank-by-Rank: System Time
        Rank:Percent
        0:86.3416%      1:77.4796%
  Least:  Rank 1      77.4796%
  Most:   Rank 0      86.3416%

Notes
-----

Wtime resolution is                   5e-08 sec

Rank-by-Rank MPI Profiling Results
----------------------------------

Activity on process rank 0

           Single-copy checking was not enabled.
comm_rank            calls:      1  time: 6.50005e-07 s  6.50005e-07 s/call

Activity on process rank 1

           Single-copy checking was not enabled.
comm_rank            calls:      1  time: 5.00004e-07 s  5.00004e-07 s/call

------------------------------------------------

recv profile

             cnt/sec for all remote ranks
local   ANY_SOURCE        0            1    
 rank

------------------------------------------------

recv wait for data profile

             cnt/sec for all remote ranks
local        0            1    
 rank
------------------------------------------------

recv wait for data profile

             cnt/sec for all remote ranks
local        0            1    
 rank

------------------------------------------------

send profile

             cnt/sec for all destination ranks
  src        0            1    
 rank

------------------------------------------------

ssend profile

             cnt/sec for all destination ranks
  src        0            1    
 rank

------------------------------------------------

ibsend profile

             cnt/sec for all destination ranks
  src        0            1    
 rank

MPI Performance Profiling Environment Variables

The MPI performance profiling environment variables are, as follows:

Variable	Description
`MPI_PROFILE_AT_INIT`	Activates MPI profiling immediately, that is, at the start of MPI program execution.
`MPI_PROFILING_STATS_FILE`	Specifies the file where MPI profiling results are written. If not specified, the file `MPI_PROFILING_STATS` is written.

MPI Supported Profiled Functions

The MPI supported profiled functions are, as follows:

Note: Some functions may not be implemented in all language as indicated below.

Languages	Function
C Fortran	`mpi_allgather`
C Fortran	`mpi_allgatherv`
C Fortran	`mpi_allreduce`
C Fortran	`mpi_alltoall`
C Fortran	`mpi_alltoallv`
C Fortran	`mpi_alltoallw`
C Fortran	`mpi_barrier`
C Fortran	`mpi_bcast`
C Fortran	`mpi_comm_create`
C Fortran	`mpi_comm_free`
C Fortran	`mpi_comm_group`
C Fortran	`mpi_comm_rank`
C Fortran	`mpi_finalize`
C Fortran	`mpi_gather`
C Fortran	`mpi_gatherv`
C	`mpi_get_count`
C Fortran	`mpi_group_difference`
C Fortran	`mpi_group_excl`
C Fortran	`mpi_group_free`
C Fortran	`mpi_group_incl`
C Fortran	`mpi_group_intersection`
C Fortran	`mpi_group_range_excl`
C Fortran	`mpi_group_range_incl`
C Fortran	`mpi_group_union`
C	`mpi_ibsend`
C Fortran	`mpi_init`
C	`mpi_init_thread`
C Fortran	`mpi_irecv`
C Fortran	`mpi_isend`
C	`mpi_probe`
C Fortran	`mpi_recv`
C Fortran	`mpi_reduce`
C Fortran	`mpi_scatter`
C Fortran	`mpi_scatterv`
C Fortran	`mpi_send`
C Fortran	`mpi_sendrecv`
C Fortran	`mpi_ssend`
C Fortran	`mpi_test`
C Fortran	`mpi_testany`
C Fortran	`mpi_wait`
C Fortran	`mpi_wait`

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Message Passing Toolkit (MPT) User's Guide
(document number: 007-3773-012 / published: 2009-10-22)    table of contents  |  additional info  |  download

    Front Matter
    New Features in This Manual
    About This Manual
    Chapter 1. Introduction
    Chapter 2. Administrating MPT
    Chapter 3. Getting Started
    Chapter 4. Programming with SGI MPI
    Chapter 5. Debugging MPI Applications
    Chapter 6. Profiling MPI Applications
    Chapter 7. Run-time Tuning
    Chapter 8. MPI Performance Profiling
    Chapter 9. Troubleshooting and Frequently Asked Questions
    Index

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Chapter 8. MPI Performance Profiling

Overview of perfcatch Utility

Using the perfcatch Utility

MPI_PROFILING_STATS Results File Example

MPI Performance Profiling Environment Variables

MPI Supported Profiled Functions

Overview of `perfcatch` Utility

Using the `perfcatch` Utility

`MPI_PROFILING_STATS` Results File Example