On Fri, Sep 29, 2017 at 11:16:24AM +0200, Alexandre Ratchov wrote:
> On Wed, Sep 27, 2017 at 03:09:48PM +0200, Joerg Sonnenberger wrote:
> > On Wed, Sep 27, 2017 at 08:40:26AM +0200, Alexandre Ratchov wrote:
> > > Even on modern amd64s integer arithmetics and bitwise operations are
> > > faster (and more precise in many cases) than floating point
> > > equivalents.
> >
> > Can you actually substanciate this claim?
>
> [OT]
>
> I'm working on typical signal processing code doing mostly
> multiplications, additions and table lookups. For instance, when we do
> the following with floats:
>
> float a, b, x, y;
> y = a * x + b;
>
> we get 24 bits of precision as floats have 24-bit mantissa. If, with
> proper typedefs and #ifdefery, we replace floats by ints representing
> the same numbers as 1:4:27 fixed-points:
>
> int a, b, x, y;
> y = ((long long)a * x >> 27) + b;
>
> we get 28 bits of precision, i.e. 4 extra bits of precision compared
> to floats.
>
> I just did a quick test on a i5, gcc 4.2. The fixed-point version
> consumes 10% to 50% less CPU depending on the algorithm. To test, I
> just run the algorithm during 10 seconds and measure the throughput.
>
> In the past, I've tested on other CPUs, with other compilers and the
> floating point version of this code was never faster than the
> fixed-point.
Add to that this is platform indepedent code and that we run or at
least ran on platforms having softfloat, where the speed difference is
significant.
-Otto
