Hello. I am a new user to scipy, thinking about
crossing over from Matlab. I have a new AMD 64
machine and just installed fedora 5 and scipy. It is
a dual boot machine with windows XP. I did a small
test to compare the speed of matlab (in 32 bit
windows, Matlab student v14) to the speed of scipy (in
fedora, 64 bit). I generated two random matrices of
10,000 by 2,000 elements and then took their dot
product. The scipy code was:
python
import numpy
import scipy
a = scipy.random.normal(0,1,[10000,2000])
b = scipy.random.normal(0,1,[10000,2000])
c = scipy.dot(a,scipy.transpose(b))
I timed the last line of the code and compared it to
the equivalent code in Matlab. The results were that
Matlab took 3.3 minutes and scipy took 11.5 minutes.
Thats a factor of three. I am surprised with the
difference and am wondering if there is anything I can
do to speed up scipy.
I installed scipy, blas, atlas, numpy and lapack from
source, just as the instructions on the scipy web site
suggested (or as close to the instructions as I
could). The only thing odd was that when installing
numpy, I received messages that the atlas libraries
could not be found. However, it did locate the lapack
libraries. I dont know why it could not find the
atlas libraries, as I told it exactly where to find
them. It did not give the message that it was using
the slower default libraries. I also tried compiling
after an export ATLAS = statement, but that did not
make a difference. Wherever I could, I complied it
specifically for the 64 bit machine. I used the
current gcc compiler. The ATLAS notes suggested that
the speed problems with the 2.9+ compilers had been
fixed.
Any ideas on where to look for a speedup? If the
problem is that it could not locate the atlas
ibraries, how might I assure that numpy finds the
atlas libraries. I can recompile and send along the
results if it would help.
Thanks. John
PS. I first sent this to the scipy mailing list, but
it didnt seem to make it there.
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