[SciPy-user] Numpy in parallel

[Ramon Crehuet]

Dear all,
I would like to use the 4 processors in my AMD Phenom machine to do some
calcualtions with Numpy.
According to:
http://www.scipy.org/ParallelProgramming
This can be achieved if numpy is compiled using a BLAS that is able to
use multi-cores. I have installed the rpm numpy that comes with my
Opensuse 11.0 distribution. Apparently only one processor is used when I
calculate things like:
c=numpy.dot(a,b)
d=numpy.linalg.inv(c)
My first question is: is this a good choice? Is this Numpy optimized for
my arquitecture or I could do much better compiling ATLAS and Numpy from
scratch? Or is Intel MKL better?

My second question is: I have to create, many times, a large array of
normally distributed vectors (the stochastic term in a Langevin dynamics
run). Do you know if numpy.random.randn will be able to use multi-cores?

Thanks in advance,
Ramon