A Tuesday 11 March 2008, Francesc Altet escrigué: > The thing that makes uint64 so special is that it is the largest > integer (in current processors) that has a native representation > (i.e. the processor can operate directly on them, so they can be > processed very fast), and besides, there is no other (common native) > type that can fully include all its precision (float64 has a mantissa > of 53 bits, so this is not enough to represent 64 bits). So the > problem is basically what to do when operations with uint64 have > overflows (or underflows, like for example, dealing with negative > values).
Mmm, I'm thinking now that there exist a relatively common floating point that have a mantissa of 64 bit (at minimum), namely the extended precision ploating point [1] (in its 80-bit incarnation, it is an IEEE standard). In modern platforms, this is avalaible as a 'long double', and I'm wondering whether it would be useful for Numexpr purposes, but seems like it is. [1] http://en.wikipedia.org/wiki/Extended_precision Cheers, -- >0,0< Francesc Altet http://www.carabos.com/ V V Cárabos Coop. V. Enjoy Data "-" ------------------------------------------------------------------------- This SF.net email is sponsored by: Microsoft Defy all challenges. Microsoft(R) Visual Studio 2008. http://clk.atdmt.com/MRT/go/vse0120000070mrt/direct/01/ _______________________________________________ Pytables-users mailing list Pytables-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/pytables-users
