Re: [Numpy-discussion] dot and MKL memory

27 Feb 2015

      On 27/02/15 17:50, Charles R Harris wrote:
...
On Fri, Feb 27, 2015 at 9:02 AM, Mads Ipsen mailto:mads.ipsen@gmail.com> wrote:
Hi,
If I build Python 2.7.2 and numpy-1.9.1 and run the following script
import numpy
    c = numpy.ones((500000, 4))
    mat = numpy.identity(4)
    r = numpy.dot(c, mat)
the evaluation of the 'dot' increases the memory by app. 35 MB.
If, in addition, I build numpy-1.9.1 with MKL support, and run the
    script, the evaluation of the 'dot' increases the memory by app. 450 MB.
Is the expected?
Best regards,
Mads
specs:
Ubuntu 12.04
    ifort (IFORT) 14.0.1 2013100
    gcc version 4.6.3 (Ubuntu/Linaro 4.6.3-1ubuntu5)
No, but I don't know why that is happening with MKL. Can anyone else
reproduce this?
Chuck
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I have now tested and reproduced this on two different Ubuntu 12.04 
boxes. Both were tested with a vanilla Python-2.7.9 install and two 
different MKL setups

*) composer_xe_2015.2.164
    icc (ICC) 15.0.2 20150121
    ifort (IFORT) 15.0.2 20150121

    build: python setup.py build --compiler=intelem
           python setup.py install

*) composer_xe_2013_sp1.1.106
    ifort (IFORT) 14.0.1 20131008
    gcc version 4.6.3

    build: python setup.py config --compiler=unix config_fc 
--fcompiler=intelem install

On both setups I use the following site.cfg

[mkl]
library_dirs = /path_to_intel_composer/mkl/lib/intel64/
include_dirs = /path_to_intel_composer/mkl/lib/intel64/mkl/include/
mkl_libs = mkl_rt
lapack_libs =

If I omit the MKL setup (i.e. build without) the 400 MB memory goes
away.

If I by any means can provide you with some valuable info, please let
me know.

Best regards,

Mads

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