Quoting Mikkel Krøigård <[EMAIL PROTECTED]>: > Citat Martin Geisler <[EMAIL PROTECTED]>: > > > I've looked at the GMPY code, and it is a fairly straightforward > > wrapper for the GMP library, as you describe. > > > > But I don't know if it makes it easier for us to benchmark just > > because it is split into its own C code... > I never said it would. If you use this approach, it is easy to see how much > is > spent on the dangerous arithmetic, but I guess a profiler could tell you how > much time Python spends on the functions implementing the operators anyway.
If that's the case, then it doesn't make sense w.r.t. the profiling to use GMPY. I was assuming the profiler could not give you information that was so fine-grained. But at least it is good news that Sigurd saw a speed-up from using C, albeit on large numbers. It indicates that the raw computing time is not completely dwarfed by bookkeeping etc. > > It is not completely unimaginable, however, that someone would want to know > how > much actually goes on inside gmpy (arithmetic on big numbers, the data) and > how > much goes on outside (counting variables, various kinds of overhead). That someone is me. I think it is important to know what fraction of the time we spend on computing we HAVE to do. regards, Ivan _______________________________________________ viff-devel mailing list (http://viff.dk/) viff-devel@viff.dk http://lists.viff.dk/listinfo.cgi/viff-devel-viff.dk
