On 26/02/2018 15:09, Chris Angelico wrote:
On Tue, Feb 27, 2018 at 2:02 AM, bartc <b...@freeuk.com> wrote:
On 26/02/2018 14:04, bartc wrote:
On 26/02/2018 13:42, Ned Batchelder wrote:
Well, once you notice that the
Python code had N=1e5, and the C code had N=1e9 :) If you want to
experiment, with N=1e5, the final number should be 5255210926702073855.
OK, I'll try that.
I have that Python version working now. It's necessary to apply that masking
function to wherever numbers can get bigger.
I don't know how long a 1-billion loop will take, but a 10-million loop took
46 seconds on Python 3.6, and 21 seconds on PyPy 2.7 from a couple of years
ago. (And on Windows, which has a somewhat slower CPython than Linux.)
You're still reimplementing the C code in Python, which is
inefficient. Have you considered going back to the *actual algorithm*
and implementing that idiomatically in Python? I think you'll find
that (a) the code is more readable, and (b) the run time is much
lower.
Do you really think that?
The algorithm seems to require this sequence of calculations to be gone
through. Otherwise anything more efficient can also be done in any language.
So how would idiomatic Python help, by seeing if such a routine already
exists in some library? That wouldn't be playing the game.
If it helps, I remember playing with a version in Algol 68 Genie
(interpreted). Still buggy as the output is different, it does about the
same amount of work.
A 10-million loop would take an estimated 1000 seconds, on the same
machine that CPython took 46 seconds. So four magnitudes slower than C.
--
bartc
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