[Numpy-discussion] optimization of arr**-2
tim.hochberg at ieee.org
Sun Jul 15 09:36:33 EDT 2007
On 7/15/07, Sebastian Haase <haase at msg.ucsf.edu> wrote:
> I compared for a 256x256 float32 normal-noise (x0=100,sigma=1) array
> the times to do
> 1./ (a*a)
> >>> U.timeIt('1./(a*a)', 1000)
> (0.00090877471871, 0.00939644563778, 0.00120674694689, 0.000687777554628)
> >>> U.timeIt('a**-2', 1000)
> (0.00876591857354, 0.0263829620803, 0.00952076311375, 0.00173311803255)
> The numbers are min,max, mean, stddev over thousand runs.
> N.__version == 1.0.1
> The slowdown is almost 10 fold. Similar tests for **-1, and **2 show
> that the corresponding times are identical - i.e. those cases are
> optimized to not call the pow routine.
> Can this be fixed for the **-2 case ?
Not without some testing and discussion. If I recall correctly, we fixed all
of the cases where the optimized case had the same accuracy as the
unoptimized case. Optimizing 'x**-2', because it involves two operations (*
and /), starts to become lose accuracy relative to pow(x,-2). The accuracy
loss is relatively minor however; an additional ULP (unit in last place) or
so, I believe. It's been a while however, so I may have the details
So, while I'm not dead set against it, I think we would definitely come to a
consensus on how much accuracy we are willing to forgo for these notational
conveniences. And document accordingly. The uncontroversial ones already got
Then again, we could just leave things as they are and when you're hungry
for speed, you could use '1/x**2'.
. tim.hochberg at ieee.org
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the NumPy-Discussion