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: [email protected] [[email protected]] On Behalf Of Matthew Brett [[email protected]] 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 _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
