On Sun, Mar 8, 2009 at 4:05 AM, Victor Stinner <victor.stin...@haypocalc.com> wrote: > I just downloaded Python 2.6.1, 3.0.1 and 3.1alpha1, compiled them on 32 and > 64 bits CPU, and ran pybench 2.1(*). > > Summary (minimum total) on 32 bits CPU: > * Python 2.6.1: 8762 ms > * Python 3.0.1: 8977 ms > * Python 3.1a1: 9228 ms (slower than 3.0) > > Summary (minimum total) on 64 bits CPU: > * Python 2.6.1: 4219 ms > * Python 3.0.1: 4502 ms > * Python 3.1a1: 4442 ms (faster than 3.0) > > I also ran pybench once, is it enough? See attached files for the details. > > (*) I copied pybench 2.1 from Pthon 3.1alpha1 because 2.6.1 only > includes pybench 2.0
How are these numbers significant? IIUC that is not at all how pybench is supposed to be used. Its strength is that it lets you watch the relative performance of many individual operations. I don't think adding up the numbers for all operations gives a very useful total, since each individual timing loop seems to be scaled to last around 50-100 msec; this means the operation mix is probably vastly different from that occurring in real operations. What I'd be interested in however would be a list of which operations got speeded up the most and which slowed down the most. That might stir up someone's memory of a change that was made in that operations that could explain the performance change (especially for slow-downs, of course :-). -- --Guido van Rossum (home page: http://www.python.org/~guido/) _______________________________________________ Python-Dev mailing list Python-Dev@python.org http://mail.python.org/mailman/listinfo/python-dev Unsubscribe: http://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
