Hi Antonio! Apologies for the slow reply, this got filed into a subfolder. The numbers are interesting, I'm also interested in the C version. I'm hoping that my tutorial will be accepted for PyCon next March (the talks are announced in two weeks), assuming I get to talk again I'll update my tutorial. Adding more for PyPy and having a C equivalent will be very useful.
Given that the C version should be very similar to the ShedSkin version, maybe it just comes down to compiler differences? On my Macbook (where I originally wrote the talk) I think the differences in speed came from two versions of gcc (Cython seemed to prefer one, ShedSkin the other, I ran out of time trying to unify that test). Do you definitely use the same optimisation flags? ShedSkin (from memory) requests fast math and a few other things in the generated Makefile. Ian. On 7 November 2011 18:04, Antonio Cuni <anto.c...@gmail.com> wrote: > Hello Ian, > > On 25/07/11 11:00, Ian Ozsvald wrote: >> >> Dear all, I've published v0.2 of my High Performance Python tutorial >> write-up from the session I ran at EuroPython: >> >> http://ianozsvald.com/2011/07/25/high-performance-python-tutorial-v0-2-from-europython-2011/ > > today I and Armin investigated a bit more about the performances of the > mandelbrot algorithm that you wrote for your tutorial. What we found is > very interesting :-). > > We compared three versions of the code: > > - a (slightly modified) pure python one on PyPy > - the Cython one using calculate_z.pyx_2_bettermath > - the shedskin one, using shedskin2.py > > The PyPy version looks like this: > > def calculate_z_serial_purepython(q, maxiter, z): > """Pure python with complex datatype, iterating over list of q and z""" > output = [0] * len(q) > for i in range(len(q)): > zi = z[i] > qi = q[i] > for iteration in range(maxiter): > zi = zi * zi + qi > if (zi.real*zi.real + zi.imag*zi.imag) > 4.0: > output[i] = iteration > break > return output > > i.e., it is exactly the same as pure_python_2.py, but we avoid to use > abs(zi), so it is comparable with the cython and shedskin version. > > First, we ran the programs to calculate passing "1000 1000" as arguments, > and these are the results: > > PyPy: 1.95 secs > Cython: 0.58 secs > Shedskin: 0.42 secs > > so, PyPy is ~4.5x slower than Shedskin. > > However, we realized that using the default values for x1,x2,y1,y2, the > innermost loop runs very few iterations most of the time, and this is one > case in which PyPy suffer most, because it needs to go through a bridge to > continue the execution, and at the moment bridges are slower than loops. > > So, we changed the values of x1,x2,y1,y2 to compute a different region, in > which the innermost loop runs more frequently. We used these values: > x1, x2, y1, y2 = 0.37865401-0.02, 0.37865401+0.02, 0.669227668-0.02, > 0.669227668+0.02 > > and since all programs are faster to compute the image, we used "3000 3000" > as arguments from the command line. These are the results: > > PyPy: 0.89 > Cython: 1.76 > Shedskin: 0.26 > > So, in this case, PyPy is ~2x faster than Cython and ~3.5x slower than > Shedskin. > > In the meantime, Armin wrote a C version of it: > http://paste.pocoo.org/raw/504216/ > > which tooks 0.946 seconds to complete. This is in line with the PyPy's > result, but we are still investigating why the shedskin's version is so much > faster. > > ciao, > Anto > -- Ian Ozsvald (A.I. researcher) i...@ianozsvald.com http://IanOzsvald.com http://MorConsulting.com/ http://StrongSteam.com/ http://SocialTiesApp.com/ http://TheScreencastingHandbook.com http://FivePoundApp.com/ http://twitter.com/IanOzsvald _______________________________________________ pypy-dev mailing list pypy-dev@python.org http://mail.python.org/mailman/listinfo/pypy-dev
