Floating point performance issue

David Brown david@westcontrol.com
Tue Dec 20 13:43:00 GMT 2011

On 20/12/2011 13:01, Vincent Lefevre wrote:
> On 2011-12-20 12:48:53 +0100, Dario Saccavino wrote:
>> In the second program, if 0.5<  f<  1 the values of a and b eventually
>> become the smallest representable denormal value and never change
>> afterwards, resulting in a large number of operations involving
>> denormal numbers.
> Yes, I agree (I forgot about that)... except that if f is close enough
> to 1, you won't have subnormals and the program will be fast (like in
> the case f<= 0.5).
>> gcc enables FTZ when using SSE and ffast-math (I think the specific
>> compiler flag is -funsafe-math-optimizations).
> Thanks, good to know...
>> Therefore the flags needed are -msse2 -mfpmath=sse -ffast-math
> I would discourage the use of -ffast-math, which can affect generic
> code very badly (due to -funsafe-math-optimizations). Isn't there
> an option to enable FTZ?

There are times when you want IEEE-accurate floating point, because you 
are pushing the limits of accuracy, or you want high repeatability.  But 
normally when you use floating point, you are accepting a certain amount 
of inaccuracy.  If your code is going to produce incorrect answers 
because of the way the compiler/cpu rounds calculations, orders your 
sums, or treats denormals and other specials, then I would argue that 
your code is probably wrong - perhaps you should be using decimal types, 
long doubles, __float128, or some sort of multi-precision maths library 

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