tungwaiyip.info

home

about me

links

Blog

< July 2009 >
SuMoTuWeThFrSa
    1 2 3 4
5 6 7 8 91011
12131415161718
19202122232425
262728293031 

past articles »

Click for San Francisco, California Forecast

San Francisco, USA

 

ctype performance benchmark

I have done some performance benchmarking for Python's ctypes library. I am planning to use ctypes as an alternative to writing C extension module for performance enhancement. Therefore my use case is slight different from the typical use case for accessing existing third party C libraries. In this case I am both the user and the implementer of the C library.

In order to determine what is the right granularity for context switching between Python and C, I have done some benchmarking. I mainly want to measure the function call overhead. So the test functions are trivial function like returning the first character of a string. I compare a pure Python function versus C module function versus ctypes function. The tests are ran under Python 2.6 on Windows XP with Intel 2.33Ghz Core Duo.

First of all I want to compare the function to get the first character of a string. The most basic case is to reference it as the 0th element of a sequence without calling any function. The produce the fastest result at 0.0659 usec per loop.

  $ timeit "'abc'[0]"

  10000000 loops, best of 3: 0.0659 usec per loop

As soon as I build a function around it, the cost goes up substantially. Both pure Python and C extension method shows similar performance at around 0.5 usec. ctypes function takes about 2.5 times as long at 1.37 usec.

  $ timeit -s "f=lambda s: s[0]"  "f('abc')"

  1000000 loops, best of 3: 0.506 usec per loop

  $ timeit -s "import mylib" "mylib.py_first('abc')"

  1000000 loops, best of 3: 0.545 usec per loop

  $ timeit -s "import ctypes; dll = ctypes.CDLL('mylib.pyd')"
              "dll.first('abc')"

  1000000 loops, best of 3: 1.37 usec per loop

I repeated the test with a long string (1MB). There are not much difference in performance. So I can be quite confident that the parameter is passed by reference (of the internal buffer).

  $ timeit -s "f=lambda s: s[0]; lstr='abcde'*200000"
              "f(lstr)"

  1000000 loops, best of 3: 0.465 usec per loop

  $ timeit -s "import mylib; lstr='abcde'*200000"
              "mylib.py_first(lstr)"

  1000000 loops, best of 3: 0.539 usec per loop

  $ timeit -s "import ctypes; dll = ctypes.CDLL('mylib.pyd')"
           -s "lstr='abcde'*200000"
              "dll.first(lstr)"

  1000000 loops, best of 3: 1.4 usec per loop

Next I have make some attempts to speed up ctypes performance. A measurable improvement can be attained by eliminating the attribute look up for the function. Curiously this shows no improvement in the similar case for C extension.

  $ timeit -s "import ctypes; dll = ctypes.CDLL('mylib.pyd');
           -s "f=dll.first"
              "f('abcde')"

  1000000 loops, best of 3: 1.18 usec per loop

Secondary I have tried to specify the ctypes function prototype. This actually decrease the performance significantly.

  $ timeit -s "import ctypes; dll = ctypes.CDLL('mylib.pyd')"
           -s "f=dll.first"
           -s "f.argtypes=[ctypes.c_char_p]"
           -s "f.restype=ctypes.c_int"
              "f('abcde')"

  1000000 loops, best of 3: 1.57 usec per loop

Finally I have tested passing multiple parameters into the function. One of the parameter is passed by reference in order to return a value. Performance decrease as the number of parameter increase.

  $ timeit -s "charAt = lambda s, size, pos: s[pos]"
           -s "s='this is a test'"
              "charAt(s, len(s), 1)"

  1000000 loops, best of 3: 0.758 usec per loop

  $ timeit -s "import mylib; s='this is a test'"
              "mylib.py_charAt(s, len(s), 1)"

  1000000 loops, best of 3: 0.929 usec per loop

  $ timeit -s "import ctypes"
           -s "dll = ctypes.CDLL('mylib.pyd')"
           -s "s='this is a test'"
           -s "ch = ctypes.c_char()"
              "dll.charAt(s, len(s), 1, ctypes.byref(ch))"

  100000 loops, best of 3: 2.5 usec per loop

One style of coding that improve the performance somewhat is to build a C struct to hold all the parameters.

  $ timeit -s "from test_mylib import dll, charAt_param"
           -s "s='this is a test'"
           -s "obj = charAt_param(s=s, size=len(s), pos=3, ch='')"
              "dll.charAt_struct(obj)"

  1000000 loops, best of 3: 1.71 usec per loop

This may work because most of the fields in the charAt_param struct are invariant in the loop. Having them in the same struct object save them from getting rebuilt each time.

My overall observation is that ctypes function has an overhead that is 2 to 3 times to a similar C extension function. This may become a limiting factor if the function calls are fine grained. Using ctypes for performance enhancement is a lot more productive if the interface can be made to medium or coarse grained.

A snapshot of the source code used for testing is available for download. This is also useful if you want a boiler plate for building your own ctypes library.

2009.07.16 [] - comments

 

 

blog comments powered by Disqus

past articles »

 

BBC News

 

Brett Kavanaugh: Embattled Trump nominee 'not going anywhere' (25 Sep 2018)

 

Rod Rosenstein: Russia inquiry chief set for Trump showdown (24 Sep 2018)

 

Electrical implant helps paralysed people to walk again (24 Sep 2018)

 

Dellen Millard killed father as he slept and inherited millions (24 Sep 2018)

 

Portuguese 400 year old shipwreck found off Cascais (24 Sep 2018)

 

Indiana school bus driver fired for letting kids drive (24 Sep 2018)

 

Weight Watchers drops 'weight' from name (24 Sep 2018)

 

Oil price jumps as Opec keeps output steady (24 Sep 2018)

 

S-300 missile system: Russia to upgrade Syrian air defences (24 Sep 2018)

 

Kenyan governor Okoth Obado charged over Otieno murder (24 Sep 2018)

more »

 

SF Gate

 

Why the gig economy may not be the workforce of the future (24 Sep 2018)

 

Telltale, San Rafael maker of video games, lays off most of its staff (24 Sep 2018)

 

Ship traffic, September 25 (24 Sep 2018)

 

Gilead facing doubts on Wall Street a year after billion Kite deal (24 Sep 2018)

 

Here are the celebs to look out for at this year's massive Dreamforce event (24 Sep 2018)

 

News site to investigate Big Tech, aided by Craigslist founder (24 Sep 2018)

more »


Site feed Updated: 2018-Sep-24 18:00