[llvm-dev] Question on fast-math optimizations

[Nicolai Hähnle via llvm-dev]

On 30.11.18 11:49, Heiko Becker via llvm-dev wrote:
> --Resending my last mail, as it might have gotten lost --
> 
> Thanks Nicolai and Steve for the initial replies.
> 
> So if I understand correctly there are 2 places you can pinpoint at 
> where distributivity is used:
> 
> - simplification of infinity/NaN expressions
> 
> - combination with FMA introduction

Well no, my comment also applied to the FMA introduction.

Stephen was a bit hesitant about what to call the x * (y + 1) --> x * y 
+ x FMA-introducing transform on the grounds that it superficially only 
seems to improve the precision at which the expression is evaluated. My 
point was that this very same transform can introduce very significant, 
qualitative differences in the result when inf is involved.

Cheers,
Nicolai


> 
> 
> @Steve: You mentioned "fast-math flags characterizing when it would be 
> allowed" so is there a point of reference where it is exactly specified 
> what fast-math flags allow and what not beyond the llvm documentation 
> that gives the high-level explanation?
> 
> 
> Thanks again,
> 
> Heiko
> 
> On 11/22/18 11:16 AM, Heiko Becker via llvm-dev wrote:
>> On 11/21/18 12:41 PM, Nicolai Hähnle wrote:
>>
>>> On 20.11.18 16:38, Stephen Canon via llvm-dev wrote:
>>>> Distribution doesn’t seem to be used by many transforms at present. 
>>>> My vague recollection is that the fast math flags didn’t do a great 
>>>> job of characterizing when it would be allowed, and using it 
>>>> aggressively broke a lot of code in practice (code which was 
>>>> numerical unstable already, but depended on getting the same 
>>>> unstable results), so people have been gun-shy about using it. Owen 
>>>> might remember more of the gory details.
>>>>
>>>> Arguably, it is implicitly used when FMA formation is combined with 
>>>> fast-math, e.g.:
>>>>
>>>>     float foo(float x, float y) {
>>>>       return x*(y + 1);
>>>>     }
>>>>
>>>> Compiled with -mfma -ffast-math, this generates fma(x, y, x). Even 
>>>> though this transform superficially appears to use distributivity, 
>>>> that’s somewhat debatable because the fma computes the whole result 
>>>> without any intermediate rounding, so it’s pretty wishy-washy to say 
>>>> that it’s been used here.
>>>
>>> It most definitely has been used here, because of inf/nan behavior.
>>>
>>> inf*(0 + 1) == inf
>>> inf*0 + inf == nan
>>>
>>> (I actually fixed this bug in the past because it occurred in practice.)
>>>
>>> Cheers,
>>> Nicolai
>>>
>>>
>>>>
>>>> – Steve
>>>>
>>>>> On Nov 20, 2018, at 9:21 AM, Heiko Becker via llvm-dev 
>>>>> <llvm-dev at lists.llvm.org> wrote:
>>>>>
>>>>> Dear LLVM developers,
>>>>>
>>>>> I have a question on the fast-math floating-point optimizations 
>>>>> applied by LLVM:
>>>>> Judging by the documentation at 
>>>>> https://llvm.org/docs/LangRef.html#fast-math-flags I understood 
>>>>> that rewriting with associativity and using reciprocal computations 
>>>>> are possible optimizations. As the folklore description of 
>>>>> fast-math is that it "applies real-valued identities", I was 
>>>>> wondering whether LLVM does also rewrite with distributivity.
>>>>>
>>>>> If this is the case, could you point me to some specification when 
>>>>> it is applied? If not, is there any particular reason against 
>>>>> applying distributivity or whether this just has not been looked 
>>>>> into so far?
>>>>>
>>>>> Thank you and best regards,
>>>>>
>>>>> Heiko
>>>>>
>>>>> _______________________________________________
>>>>> LLVM Developers mailing list
>>>>> llvm-dev at lists.llvm.org
>>>>> http://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
>>>>
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>>>
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