[Numpy-discussion] Numpy x Matlab: some synthetic benchmarks

Travis Oliphant oliphant.travis at ieee.org
Thu Jan 19 12:25:03 CST 2006


Francesc Altet wrote:

>http://oprofile.sourceforge.net
>
>It is a nice way to do profiling at C level on Linux machines. Running
>the Paulo benchmarks through oprofile can surely bring some light.
>  
>
I ran the following code snippet (timed under a Timeit instance) through 
the oprofile profiler for both NumPy and Numeric, to look at indexing 
speeds.

op = "b = A[::2,::2]; d = A[1:80,:]"

This is what I found:  overall

   61242 53.9606 /usr/bin/python
    17647 15.5488 /usr/lib/python2.4/site-packages/numpy/core/multiarray.so
    15942 14.0466 /lib/tls/libc-2.3.3.so
     7158  6.3069 /no-vmlinux
     6995  6.1633 /usr/lib/python2.4/site-packages/Numeric/_numpy.so

Showing that more time is spent in NumPy than in Numeric doing indexing...

Here's the breakdown for NumPy
 
samples  %        symbol name
2353     13.3337  PyArray_PyIntAsIntp      # This is also slower --- 
called more often?
2060     11.6734  PyArray_MapIterNew    # This calls fancy_indexing_check.
1980     11.2200  slice_GetIndices
1631      9.2424  parse_index
1149      6.5110  arraymapiter_dealloc       # Interesting this is 
taking so long?
1142      6.4714  array_subscript
1121      6.3524  _IsAligned
1069      6.0577  array_dealloc
780       4.4200  fancy_indexing_check
684       3.8760  PyArray_NewFromDescr
627       3.5530  parse_subindex
538       3.0487  PyArray_DescrFromType
534       3.0260  array_subscript_nice
455       2.5783  _IsContiguous
370       2.0967  _IsFortranContiguous
334       1.8927  slice_coerce_index
294       1.6660  PyArray_UpdateFlags
234       1.3260  anonymous symbol from section .plt
161       0.9123  PyArray_Return
120       0.6800  array_alloc
2         0.0113  PyArray_Broadcast
2         0.0113  PyArray_IterNew
1         0.0057  LONG_setitem
1         0.0057  PyArray_EquivTypes
1         0.0057  PyArray_FromAny
1         0.0057  PyArray_FromStructInterface
1         0.0057  PyArray_IntpConverter
1         0.0057  PyArray_SetNumericOps
1         0.0057  initialize_numeric_types


Here's the breakdown for Numeric:

1577     22.5447  slice_GetIndices
1155     16.5118  parse_index
912      13.0379  PyArray_FromDimsAndDataAndDescr
792      11.3224  array_subscript
675       9.6497  PyArray_IntegerAsInt
517       7.3910  parse_subindex
401       5.7327  array_dealloc
379       5.4182  slice_coerce_index
339       4.8463  array_subscript_nice
161       2.3016  anonymous symbol from section .plt
82        1.1723  PyArray_Return
5         0.0715  do_sliced_copy


Anybody interested in optimization?

-Travis










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