On 27/02/15 17:50, Charles R Harris wrote:
On Fri, Feb 27, 2015 at 9:02 AM, Mads Ipsen <mads.ipsen@gmail.com <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 -- +---------------------------------------------------------------------+ | Mads Ipsen | +----------------------------------+----------------------------------+ | Overgaden Oven Vandet 106, 4.tv | phone: +45-29716388 | | DK-1415 København K | email: mads.ipsen@gmail.com | | Denmark | map : https://goo.gl/maps/oQ6y6 | +----------------------------------+----------------------------------+