[Numpy-discussion] float128 in fact float80

Nadav Horesh nadavh@visionsense....
Sun Oct 16 01:04:57 CDT 2011


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.

  Nadav

________________________________________
From: numpy-discussion-bounces@scipy.org [numpy-discussion-bounces@scipy.org] On Behalf Of Matthew Brett [matthew.brett@gmail.com]
Sent: 16 October 2011 01:29
To: Discussion of Numerical Python
Subject: [Numpy-discussion] float128 in fact float80

Hi,

After getting rather confused, I concluded that float128 on a couple
of Intel systems I have, is in fact an 80 bit extended precision
number:

http://en.wikipedia.org/wiki/Extended_precision

>>> np.finfo(np.float128).nmant
63
>>> np.finfo(np.float128).nexp
15

That is rather confusing.   What is the rationale for calling this
float128?  It is not IEEE 754 float128, and yet it seems to claim so.

Best,

Matthew
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