Hi, Le 29/02/2012 16:22, Paweł Biernat a écrit : > Is there any way to interact with Fortran's real(16) (supported by gcc > and Intel's ifort) data type from numpy? By real(16) I mean the > binary128 type as in IEEE 754. (In C this data type is experimentally > supported as __float128 (gcc) and _Quad (Intel's icc).) I googled a bit this "__float128". It seems a fairly new addition (GCC 4.6, released March 2011). The related point in the changelog [1] is :
"GCC now ships with the LGPL-licensed libquadmath library, which
provides quad-precision mathematical functions for targets with a
__float128 datatype. __float128 is available for targets on 32-bit x86,
x86-64 and Itanium architectures. The libquadmath library is
automatically built on such targets when building the Fortran compiler."
It seems this __float128 is newcomer in the "picture of data types" that
Matthew just mentioned.
As David says, arithmetic with such a 128 bits data type is probably not
"hardwired" in most processors (I mean Intel & friends) which are
limited to 80 bits ("long doubles") so it may be a bit slow. However,
this GCC implementation with libquadmath seems to create some level of
abstraction. Maybe this is one acceptably good way for a real "IEEE
float 128" dtype in numpy ?
Best,
Pierre
[1] http://gcc.gnu.org/gcc-4.6/changes.html
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