On 21 April 2010 11:03, Pauli Virtanen <p...@iki.fi> wrote: > ke, 2010-04-21 kello 10:47 -0400, Adrien Guillon kirjoitti: > [clip] >> 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). > > Probably the only way to ensure this is to recompile Numpy (and > possibly, also Python) with the -ffloat-store option turned on. > > When compiling Numpy, you should be able to insert the flag via > > OPT="-ffloat-store" python setup.py build
This will certainly work. But maybe you should be careful even so: you can't trust floating-point operations to behave identically across architectures (or even across compilations). Given that, it may be perfectly sufficient to simply do your calculations normally in numpy, without recompiling. Even if x86 FPUs store intermediate results in extended precision, the way numpy structures its computations normally forces all intermediate results out to main memory: r = a*b + c, when applied to arrays, carries out all the multiplications, then all the additions. So extended precision may not be an issue. Anne _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
