[Numpy-discussion] Disabling Extended Precision in NumPy (like -ffloat-store)

[David]

On 04/21/2010 11:47 PM, Adrien Guillon wrote:
> Hello all,
>
> I've recently started to use NumPy to prototype some numerical
> algorithms, which will eventually find their way to a GPU (where I
> want to limit myself to single-precision operations for performance
> reasons).  I have recently switched to the use of the "single" type in
> NumPy to ensure I use single-precision floating point operations.
>
> My understanding, however, is that Intel processors may use extended
> precision for some operations anyways unless this is explicitly
> disabled, which is done with gcc via the -ffloat-store operation.
> Since I am prototyping algorithms for a different processor
> architecture, where the extended precision registers simply do not
> exist, I would really like to force NumPy to limit itself to using
> single-precision operations throughout the calculation (no extended
> precision in registers).

I don't think it is a good idea - even if you compile numpy itself with 
-ffloat-store, most runtime capabilities are built without this, so you 
will have differences wether the computation is done in the C library, 
in numpy, in the fortran runtime, or by the compiler (when computing 
constants). This sounds worse than what you can get from numpy by default,

cheers,

David