[Numpy-discussion] float128 in fact float80
Sun Oct 16 02:28:08 CDT 2011
On Sun, Oct 16, 2011 at 8:04 AM, Matthew Brett <firstname.lastname@example.org> wrote:
> On Sat, Oct 15, 2011 at 11:04 PM, Nadav Horesh <email@example.com> wrote:
>> On 32 bit systems it consumes 96 bits (3 x 32). and hence float96
>> On 64 bit machines it consumes 128 bits (2x64).
>> The variable size is set for an efficient addressing, while the calculation in hardware is carried in the 80 bits FPU (x87) registers.
> Right - but the problem here is that it is very confusing. There is
> something called binary128 in the IEEE standard, and what numpy has is
> not that. float16, float32 and float64 are all IEEE standards called
> binary16, binary32 and binary64.
This one is easy: few CPU support the 128 bits float specified in IEEE
standard (the only ones I know are the expensive IBM ones). Then there
are the cases where it is implemented in software (SPARC use the
So you would need binar80, binary96, binary128, binary128_double_pair,
etc... That would be a nightmare to support, and also not portable:
what does binary80 become on ppc ? What does binary96 become on 32
bits Intel ? Or on windows (where long double is the same as double
for visual studio) ?
binary128 should only be thought as a (bad) synonym to np.longdouble.
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