A Sunday 09 January 2011 23:45:02 Mark Wiebe escrigué: > As a benchmark of C-based iterator usage and to make it work properly > in a multi-threaded context, I've updated numexpr to use the new > iterator. In addition to some performance improvements, this also > made it easy to add optional out= and order= parameters to the > evaluate function. The numexpr repository with this update is > available here: > > https://github.com/m-paradox/numexpr > > To use it, you need the new_iterator branch of NumPy from here: > > https://github.com/m-paradox/numpy > > In all cases tested, the iterator version of numexpr's evaluate > function matches or beats the standard version. The timing results > are below, with some explanatory comments placed inline: [clip]
Your patch looks mostly fine to my eyes; good job! Unfortunately, I've been unable to compile your new_iterator branch of NumPy: numpy/core/src/multiarray/multiarraymodule.c:45:33: fatal error: new_iterator_pywrap.h: El fitxer o directori no existeix Apparently, you forgot to add the new_iterator_pywrap.h file. My idea would be to merge your patch in numexpr and make the new `evaluate_iter()` the default (i.e. make it `evaluate()`). However, by looking into the code, it seems to me that unaligned arrays (this is an important use case when operating with columns of structured arrays) may need more fine-tuning for Intel platforms. When I can compile the new_iterator branch, I'll give a try at unaligned data benchs. Also, I'd like to try out the new thread scheduling that you suggested to me privately (i.e. T0T1T0T1... vs T0T0...T1T1...). Thanks! -- Francesc Alted _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
