python - Link ATLAS/MKL to an installed Numpy -


tl;dr how link atlas/mkl existing numpy without rebuilding.

i have used numpy calculate large matrix , found slow because numpy use 1 core calculation. after doing lot of search figure numpy not link optimized library atlas/mkl. here config of numpy:

>>>import numpy np >>>np.__config__.show() blas_info:     libraries = ['blas']     library_dirs = ['/usr/lib']     language = f77 lapack_info:     libraries = ['lapack']     library_dirs = ['/usr/lib']     language = f77 atlas_threads_info:     not available blas_opt_info:     libraries = ['blas']     library_dirs = ['/usr/lib']     language = f77     define_macros = [('no_atlas_info', 1)] atlas_blas_threads_info:   not available openblas_info:   not available lapack_opt_info:     libraries = ['lapack', 'blas']     library_dirs = ['/usr/lib']     language = f77     define_macros = [('no_atlas_info', 1)] atlas_info:   not available lapack_mkl_info:   not available blas_mkl_info:   not available atlas_blas_info:   not available mkl_info:   not available

for reason, want link atlas/mkl numpy. however, numpy installed pip don't want install manually because want use latest version. have done search building scratch. reason, question are:

  • are there way link atlas/mkl numpy without rebuilding again?
  • i have found config info saved in _config_.py in installed folder of numpy. modifying solve problem? if yes, please show me how?

assuming you're running flavour of linux, here's 1 way it:

  1. find out blas library numpy linked against using ldd.

    • for versions of numpy older v1.10:

      $ ldd /<path_to_site-packages>/numpy/core/_dotblas.so

      for example, if install numpy via apt-get, links to

      ... libblas.so.3 => /usr/lib/libblas.so.3 (0x00007fed81de8000) ...

      if _dotblas.so doesn't exist, means numpy failed detect blas libraries when installed, in case doesn't build of blas-dependent components. happens if install numpy using pip without manually specifying blas library (see below). i'm afraid you'll have no option rebuild numpy if want link against external blas library.

    • for numpy v1.10 , newer:

      _dotblas.so has been removed recent versions of numpy, should able check dependencies of multiarray.so instead:

      $ ldd /<path_to_site-packages>/numpy/core/multiarray.so

  2. install atlas/mkl/openblas if haven't already. way, recommend openblas on atlas - take @ this answer (although benchmarking data bit out of date).

  3. use update-alternatives create symlink new blas library of choice. example, if installed libopenblas.so /opt/openblas/lib, do:

    $ sudo update-alternatives --install /usr/lib/libblas.so.3 \                                      libblas.so.3 \                                      /opt/openblas/lib/libopenblas.so \                                      50

    you can have multiple symlinks configured single target library, allowing manually switch between multiple installed blas libraries.

    for example, when call $ sudo update-alternatives --config libblas.so.3, can choose between 1 of 3 libraries:

      selection    path                                    priority   status ------------------------------------------------------------   0            /opt/openblas/lib/libopenblas.so         40        auto mode   1            /opt/openblas/lib/libopenblas.so         40        manual mode   2            /usr/lib/atlas-base/atlas/libblas.so.3   35        manual mode * 3            /usr/lib/libblas/libblas.so.3            10        manual mode

if want "newest" version of numpy, take @ my answer on compiling numpy source openblas integration.

installing numpy blas support using pip

as @tndoan mentioned in comments, it's possible make pip respect particular configuration numpy placing config file in ~/.numpy-site.cfg - see this answer more details.

my personal preference configure , build numpy hand. it's not particularly difficult, , gives better control on numpy's configuration.


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