https://gcc.gnu.org/bugzilla/show_bug.cgi?id=26374
--- Comment #17 from beebe at math dot utah.edu ---
>> ... powerpc currently uses what is called double double for 128bit
>> long double. GCC does not know how to constant fold that nicely.
Yes, I know about the double double format that IBM, SGI, and possibly
others introduced in the 1990s for implementing long double. I
strongly disapprove of that decision, and wrote about it extensively
in my big book
The Mathematical-Function Computation Handbook
https://doi.org/10.1007/978-3-319-64110-2
http://www.math.utah.edu/pub/tex/bib/master.html#Beebe:2017:MFC
that addresses accurate computation in binary and decimal arithmetic,
for IEEE 754, and also for some important historical floating-point
designs.
>> GCC does not know how to constant fold that nicely.
Because gcc has used gmp for several years now for correctly rounded
conversions of decimal numbers to binary IEEE 754 formats, I would
have thought that handling a constant expression like "1.0L / 42.0L"
would have been relatively trivial.
>> powerpc linux targets are moving over to use standard 128bit IEEE
>> long double and IIRC for GCC 12 (or is it 13) will default to IEEE
>> long double so this will be less of an issue.
Thanks for that interesting news! It is a big change, because it
affects both -lc and -lm libraries, plus lots of user code.
The IBM POWER architecture was introduced to the world in February
1990, and we here in Utah had some of the earliest models available,
so now that we are 2**5 years later, it is high time to conform to
IEEE 754.
POWER made a big impact for those who learned how to exploit its
interesting features. I wrote about it here:
High-Performance Matrix Multiplication
http://www.math.utah.edu/pub/benchmarks/usirep.pdf
That document showed there that a 44x performance boost was possible
in some cases, without leaving standard programming languages for
assembly code fragments.
I wrote a lot more about the importance of understanding architecture
and memory designs it here:
The Impact of Memory and Architecture on Computer Performance
http://www.math.utah.edu/~beebe/memperf.pdf
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