Hi,
I'm working on a program to compute Pi and noticed two interesting
situations.
1. Bug #445 "RxMath functions do not honor precision on Windows" is back.
2. Something I accept, but can't figure out why and would like to
understand.
Bug 445: RxMath functions do not honor precision on Windows
The Pi program I'm writing is using Chudnovsky and as such needs the square
root of K3 to the same precision as the final result (say Pi to 100,000
places or even more). Yet, when I call RxCalcSqrt(k3), the number of
places is only 11, which is not close enough to provide valid results. I
tried it and the result wasn't even close to the known results of Pi at the
100,000 places.
As I read bug 445, Mark closed it as "Committed revision 986." Thus it
looks like bug 445 is back in 4.2.0 64-bit.
As for the second item: Something just doesn't make sense, as when I
change the values of the variables used in the MATH (same precision) the
amount of time it takes to compute is up to 10X longer. The code is the
same and precision is the same for both runs. I know you need details to
be specific. The "heart" of the loop is:
s = -s *,
(6*n) * (6*n-1) * (6*n-2) * (6*n-3) * (6*n-4) * (6*n-5),
/,
((3*n) * (3*n-1) * (3*n-2) * n * n * n * k3_power3)
t = t + s * (k1 + n*k2)
and what I'm seeing is more time spent here when the values for s,
k3_power3, k1, k2, and t are different, but the precisions are the same.
They are different because the code supports a fast and normal convergence
(14 versus 25). The difference is the fast and normal have different
values for the previously mentioned variables, but the same precision. I'm
noticing the "fast" is actually 10X slower than the normal. I just don't
understand why and thus am thinking there is something "inside" Rexx
causing it to go slower, but what?
Well, thanks for listening. :-)
Bertram Moshier
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