On Sat, Apr 19, 2003 at 04:23:25PM +0200, Olivier Baur wrote
Le vendredi, 18 avr 2003, à 23:01 Europe/Paris, Joseph Heled a écrit :
Third, I need to see numbers on how faster this is on non scalar,
regular x86 machine.
I don't know if this is a typo, but please note a "scalar" processor is
what you call a "regular" processor; on the other hand, "non-scalar"
and "super-scalar" refer to vector-computing.
Please note the speed increase I have measured in sigmoid2 (+60%) was
for a regular scalar (ie *non* vector) implementation (on a PPC G4
processor); with a vector implementation of sigmoid2 (on the same
processor), I actually got a whopping +250% speed increase...
So let me know what figures you get on a scalar x86 :-)
I tried your code:
I pasted it into neuralnet.c, made a call to ComputeSigTable and
replaced all calls to sigmoid with sigmoid2.
I analysed a 172 move match on 2-ply. It took 475 seconds with the old
code and 463 seconds with the new code.
In your posted code you use 201 points, but I tried with both 201 and
1001 points.
I also got slightly different results with typical differences in the
third or fourth digit.
Jørn
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