David M. Cooke wrote:
$ opstack -t 1 /usr/bin/python self % child % image name symbol name 132281 10.5031 0 0 python (no symbols) ------------------------------------------------------------------------------- 704810 55.9618 0 0 _numpy.so check_array ------------------------------------------------------------------------------- 309384 24.5650 0 0 umath.so DOUBLE_add ------------------------------------------------------------------------------- 112974 8.9701 0 0 libc-2.3.2.so (no symbols) -------------------------------------------------------------------------------
The -t 1 limits the display to those routines taking more than 1% of the runtime. 10% for python, and 10% for the C-library probably aren't so bad (I'm thinking that's calls to malloc() and friends). However, the big problem is that only 25% of the time is actually doing useful work. What's check_array doing? We can delve deeper:
Thanks for this *excellent* tutorial and analysis. I would love to see more of this. I've never liked the check_array concept. In fact, if you use SciPy which makes several changes to things that Numeric does, check_array never runs, because self->check_return is 0 for all SciPy Ufuncs (e.g. those in fastumath). So, perhaps some of these basic benchmarks should be run by SciPy users. I forgot about this little speed-up that SciPy users enjoy all the time. SciPy has also added inf and Nan. I would be very willing to remove check_array from all Numeric ufuncs and create a separate interface for checking results, after the fact. What is the attitude of the community. -Travis --------------040503020304000703090102--