This program only takes 0.68s in C using a pretty naive mpz program on
sage.math. I doubt the memory allocation is really relevant. The
interpreter overhead is by far the greatest component
Bill.
On 9 Sep, 17:57, Nils Bruin <nbr...@sfu.ca> wrote:
> Inspired by a little experiment we did to see if there is room to
> improve to ECL's bignum performance, we ran a little experiment
> computing fibonacci numbers (we wanted to test addition because it was
> mainly ECL's memory management that was under consideration)
>
> with the following defs:
>
> def fibo(n):
> a=1
> b=1
> c=0
> for i in range(n):
> c=a
> a=a+b
> b=c
> return b
>
> def test(n,m):
> for i in range(m):
> _=fibo(n)
>
> sage: timeit("test(4000,4000)")
> 5 loops, best of 3: 6.99 s per loop
> sage: time test(4000,4000)
> CPU times: user 7.10 s, sys: 0.00 s, total: 7.10 s
> Wall time: 7.11 s
> sage: time test(4000,4000)
> CPU times: user 7.24 s, sys: 0.00 s, total: 7.24 s
> Wall time: 7.24 s
> sage: time test(4000,4000)
> CPU times: user 7.38 s, sys: 0.00 s, total: 7.38 s
> Wall time: 7.39 s
> sage: time test(4000,4000)
> CPU times: user 7.10 s, sys: 0.00 s, total: 7.10 s
> Wall time: 7.11 s
> sage: time test(4000,4000)
> CPU times: user 7.05 s, sys: 0.00 s, total: 7.05 s
> Wall time: 7.06 s
>
> In ECL, this took 14.8 sec (uncompiled) and 8.8 sec (compiled). Of
> course, this particular programming exercise was just to see how fast
> one can shove information into GMP and ECL at this point definitely
> doesn't claim to be particularly optimized for that particular task,
> but as you can see, straightforward python and sage do a good job.
>
> For comparison, Magma takes about 8.4 secs, as does the code above
> when I initialize a=int(1) etc.
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