Alan Gauld, 08.03.2011 09:51:
"Knacktus" wrote
He doesn't have to write it, as it is very obvious, that no Python code
on earth (even written by Guido himself ;-)) stands a chance compared to
Fortran or C. Look at this:
There is one big proviso. The C or Fortran needs to be well written
in the first place. It's quite possible to write code in Python that
outperforms badly written C. And it is quite easy to write bad C!
It's seriously hard to write computational Python code that is faster than
C code, though. It shifts a bit if you can take advantage of Python's
dynamic container types, especially dicts, but that's rarely the case for
mathematic computation code, which would usually deploy NumPy etc. in
Python. Writing that in pure Python is bound to be incredibly slow, and
likely still several hundred times slower than even a simple approach in C.
There's a reason people use NumPy, C, Fortran and Cython for these things.
Remember that the OP's topic was a BLAS implementation. The BLAS libraries
are incredibly well optimised for all sorts of platforms, including GPUs.
They are building blocks that C programmers can basically just plug into
their code to run hugely fast computations. There is no way Python code
will ever be able to get any close to that.
Stefan
_______________________________________________
Tutor maillist - Tutor@python.org
To unsubscribe or change subscription options:
http://mail.python.org/mailman/listinfo/tutor
