Link ATLAS/MKL to an installed Numpy

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Assuming you’re running some flavour of linux, here’s one way you could do it:

  1. Find out what BLAS library numpy is currently linked against using ldd.

    • For versions of numpy older than v1.10:

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

      For example, if I install numpy via apt-get, it links to

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

      If _dotblas.so doesn’t exist, this probably means that numpy failed to detect any BLAS libraries when it was originally installed, in which case it simply doesn’t build any of the BLAS-dependent components. This often happens if you install numpy using pip without manually specifying a BLAS library (see below). I’m afraid you’ll have no option but to rebuild numpy if you want to link against an external BLAS library.

    • For numpy v1.10 and newer:

      _dotblas.so has been removed from recent versions of numpy, but you should be able to check the dependencies of multiarray.so instead:

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

  2. Install ATLAS/MKL/OpenBLAS if you haven’t already. By the way, I would definitely recommend OpenBLAS over ATLAS – take a look at this answer (although the benchmarking data is now probably a bit out of date).

  3. Use update-alternatives to create a symlink to the new BLAS library of your choice. For example, if you installed libopenblas.so into /opt/OpenBLAS/lib, you would 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 for a single target library, allowing you to manually switch between multiple installed BLAS libraries.

    For example, when I call $ sudo update-alternatives --config libblas.so.3, I can choose between one 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 you really want the “newest” version of numpy, you could also take a look at my answer on compiling numpy from source with OpenBLAS integration.

Installing numpy with BLAS support using pip

As @tndoan mentioned in the comments, it’s possible to make pip respect a particular configuration for numpy by placing a config file in ~/.numpy-site.cfg – see this answer for more details.

My personal preference is to configure and build numpy by hand. It’s not particularly difficult, and it gives you better control over numpy’s configuration.

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