[Numpy-discussion] Different results from repeated calculation
Fernando Perez
fperez.net at gmail.com
Sun Jan 28 11:39:20 CST 2007
On 1/28/07, Charles R Harris <charlesr.harris at gmail.com> wrote:
> > The problem goes away if I remove atlas (atlas3-sse2 for me). But that
> > just introduces another problem: slowness.
> >
> > So is this something to report to Clint Whaley? Or does it have to do
> > with how numpy uses atlas?
>
>
> Interesting, I wonder if ATLAS is resetting the FPU flags and changing the
> rounding mode? It is just the LSB of the mantissa that looks to be
> changing. Before reporting the problem it might be good to pin it down a bit
> more if possible.
Well, the fact that I don't see the problem on a PentiumIII (with
atlas-sse) but I see it on my desktop (atlas-sse2) should tell us
something. The test code uses double arrays, and SSE2 has double
precision support but it's purely 64-bit doubles. SSE is
single-precision only, which means that for a double computation,
ATLAS isn't used and the Intel FPU does the computation instead.
Intel FPUs use 80 bits internally for intermediate operations (even
though they only return a normal 64-bit double result), so it's fairly
common to see this kind of thing.
You can test things by writing a little program in C that does the
same operations, and use this little trick:
#include <fpu_control.h>
// Define DOUBLE to set the FPU in regular double-precision mode, disabling
// the internal 80-bit mode which Intel FPUs have.
//#define DOUBLE
// ... later in the code's main():
// set FPU control word for double precision
int cword = 4722;
_FPU_SETCW(cword);
This can show you if the problem is indeed caused by rounding
differences between 64-bit and 80-bit mode.
Cheers,
f
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