[Numpy-discussion] Precision difference between dot and sum
Charles R Harris
Mon Nov 1 21:43:11 CDT 2010
On Mon, Nov 1, 2010 at 7:49 PM, Robert Kern <email@example.com> wrote:
> On Mon, Nov 1, 2010 at 20:21, Charles R Harris
> <firstname.lastname@example.org> wrote:
> > On Mon, Nov 1, 2010 at 5:30 PM, Joon <email@example.com> wrote:
> >> Hi,
> >> I just found that using dot instead of sum in numpy gives me better
> >> results in terms of precision loss. For example, I optimized a function
> >> scipy.optimize.fmin_bfgs. For the return value for the function, I tried
> >> following two things:
> >> sum(Xb) - sum(denominator)
> >> and
> >> dot(ones(Xb.shape), Xb) - dot(ones(denominator.shape), denominator)
> >> Both of them are supposed to yield the same thing. But the first one
> >> me -589112.30492110562 and the second one gave me -589112.30492110678.
> >> In addition, with the routine using sum, the optimizer gave me "Warning:
> >> Desired error not necessarily achieved due to precision loss." With the
> >> routine with dot, the optimizer gave me "Optimization terminated
> >> successfully."
> >> I checked the gradient value as well (I provided analytical gradient)
> >> gradient was smaller in the dot case as well. (Of course, the the
> >> was e-5 to e-6, but still)
> >> I was wondering if this is well-known fact and I'm supposed to use dot
> >> instead of sum whenever possible.
> >> It would be great if someone could let me know why this happens.
> > Are you running on 32 bits or 64 bits? I ask because there are different
> > floating point precisions on the 32 bit platform and the results can
> > on how the compiler does things.
> Eh, what? Are you talking about the sometimes-differing intermediate
> precisions? I wasn't aware that was constrained to 32-bit processors.
It seems to be more of a problem on 32 bits, what with the variety of sse*.
OTOH, all 64 bit systems have at least sse2 available together with more sse
registers and I believe the x87 instruction set is not available when
running in 64 bit mode. I may be wrong about that, these nasty details are
hard to verify, but that has also been my experience.
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