Profile parallelized python script with mpi4py

As Rob Latham said you could use cProfile. You can save the output from each process in a different file. If you want to profile a function you could use a decorator like this:

from mpi4py import MPI
import cProfile

def profile(filename=None, comm=MPI.COMM_WORLD):
  def prof_decorator(f):
    def wrap_f(*args, **kwargs):
      pr = cProfile.Profile()
      pr.enable()
      result = f(*args, **kwargs)
      pr.disable()

      if filename is None:
        pr.print_stats()
      else:
        filename_r = filename + ".{}".format(comm.rank)
        pr.dump_stats(filename_r)

      return result
    return wrap_f
  return prof_decorator

@profile(filename="profile_out")
def my_function():
  # do something

The output of each process can be visualized using snakeviz

Why can't you use cprofile? Have you tried?

For MPICH, I ran like this:

$ mpiexec -l -np 4 python -m cProfile ./simple-io.py doodad 

This gives me 4 sets of output, but the '-l' argument lists the MPI rank in front of each bit of output. Note: that '-l' argument is MPICH specific. OpenMPI uses --tag-output. Other implementations might use something else.

I see cprofile can take a file name argument. make a per-rank output file and then process it with the Stats

% python 
Python 2.7.10 (default, Oct 14 2015, 16:09:02) 
[GCC 5.2.1 20151010] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import pstats
>>> pstats.Stats("simple-io.cprofile").sort_stats('cumulative').print_stats()

gives me lots of cprofile information... but my toy program was too tiny to give me anything useful.