[SciPy-user] Numpy in parallel

Francesc Alted faltet@pytables....
Fri Apr 24 05:15:20 CDT 2009


A Friday 24 April 2009, David Warde-Farley escrigué:
> The Intel MKL, while it can be used on AMD chips (apparently), is
> mainly designed to optimize the heck out of *Intel* chips, and from
> what I understand outperforms ATLAS on that hardware. I would not
> expect it to do very much better than ATLAS (if at all) on non-Intel
> hardware.

Well, following the excellent "Optimizing software in C++" [1], MKL 
explicitely disables its optimizations when an Intel CPU is not 
detected.  However, in this manual it is explained how to override 
MKL's CPU detection for taking advantage of other CPUs (i.e. AMD) too.
In fact, looking at table 11.4 one can see that there is not much 
difference between using Intel or AMD CPUs when the CPU detection has 
been overridden (and sometimes AMDs can be faster, as show there).

[1] http://www.agner.org/optimize/optimizing_cpp.pdf

-- 
Francesc Alted

"One would expect people to feel threatened by the 'giant
brains or machines that think'.  In fact, the frightening
computer becomes less frightening if it is used only to
simulate a familiar noncomputer."

-- Edsger W. Dykstra
   "On the cruelty of really teaching computer science"


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