[Numpy-discussion] Numpy 1.7.0 with Intel MKL 11.0.2.146

[QT]

Dear Warren,

It's an Intel i7 950, 4 cores, 8 with hyper-threading.

I used MKL 11.0.2.146, but I will read your link.  It seems spot on.

Best,
Quyen

On Sun, Mar 10, 2013 at 10:31 PM, Warren Weckesser <
warren.weckesser at gmail.com> wrote:

> On 3/10/13, Warren Weckesser <warren.weckesser at gmail.com> wrote:
> > On 3/10/13, QT <rdirective at gmail.com> wrote:
> >> Dear all,
> >>
> >> I'm at my wits end.  I've followed Intel's own
> >> instructions<
> http://software.intel.com/en-us/articles/numpyscipy-with-intel-mkl>on
> >> how to compile Numpy with Intel MKL.  Everything compiled and linked
> >> fine and I've installed it locally in my user folder...There is one
> nasty
> >> problem.  When one calls the numpy library to do some computation, it
> >> does
> >> not use all of the available threads.  I have 8 "cores" on my machine
> and
> >> it only uses 4 of them.  The MKL_NUM_THREADS environmental variable can
> >> be
> >> set to tune the number of threads but setting it to 8 does not change
> >> anything.  Indeed, setting it to 3 does limit the threads to 3....What
> is
> >> going on?
> >
> >
> > Does your computer have 8 physical cores, or 4 cores that look like 8
> > because of hyperthreading?
> >
>
>
> Here's why I ask this: http://software.intel.com/en-us/forums/topic/294954
>
>
> > Warren
> >
> >
> >>
> >> As a comparison, the numpy (version 1.4.1, installed from yum, which
> uses
> >> BLAS+ATLAS) uses all 8 threads.  I do not get this.
> >>
> >> You can run this test program
> >>
> >> python -mtimeit -s'import numpy as np; a = np.random.randn(1e3,1e3)'
> >> 'np.dot(a, a)'
> >>
> >> There is one saving grace, the local numpy built with MKL is much faster
> >> than the system's numpy.
> >>
> >> I hope someone can help me.  Searching the internet has been fruitless.
> >>
> >> Best,
> >> Quyen
> >>
> >> My site.cfg for numpy (1.7.0)
> >> [mkl]
> >> library_dirs = /opt/intel/mkl/lib/intel64
> >> include_dirs = /opt/intel/mkl/include
> >> mkl_libs = mkl_rt
> >> lapack_libs =
> >>
> >> I've edited line 37 of numpy/distutils/intelcompiler.py
> >> self.cc_exe = 'icc -O3 -fPIC -fp-model strict -fomit-frame-pointer
> >> -openmp
> >> -parallel -DMKL_ILP64'
> >>
> >> Also line 54 of numpy/distutils/fcompiler/intel.py
> >> return ['-i8 -xhost -openmp -fp-model strict']
> >>
> >> My .bash_profile also contains the lines:
> >> source /opt/intel/bin/compilervars.sh intel64
> >> source /opt/intel/mkl/bin/mklvars.sh intel64
> >>
> >> The above is needed to set the LD_LIBRARY_PATH so that Python can source
> >> the intel dynamic library when numpy is called.
> >>
> >
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