![]() * 3 /usr/lib/libblas/libblas.so.3 10 manual mode You can have multiple symlinks configured for a single target library, allowing you to manually switch between multiple installed BLAS libraries.įor example, when I call $ sudo update-alternatives -config libblas.so.3, I can choose between one of 3 libraries: Selection Path Priority StatusĠ /opt/OpenBLAS/lib/libopenblas.so 40 auto modeġ /opt/OpenBLAS/lib/libopenblas.so 40 manual modeĢ /usr/lib/atlas-base/atlas/libblas.so.3 35 manual mode For example, if you installed libopenblas.so into /opt/OpenBLAS/lib, you would do: $ sudo update-alternatives -install /usr/lib/libblas.so.3 \ ![]() Use update-alternatives to create a symlink to the new BLAS library of your choice. 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recommend OpenBLAS over ATLAS - take a look at this answer (although the benchmarking data is now probably a bit out of date). Install ATLAS/MKL/OpenBLAS if you haven't already. _dotblas.so has been removed from recent versions of numpy, but you should be able to check the dependencies of multiarray.so instead: $ ldd //numpy/core/multiarray.so I'm afraid you'll have no option but to rebuild numpy if you want to link against an external BLAS library. This often happens if you install numpy using pip without manually specifying a BLAS library (see below). 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. So will modifying it solve my problem? If yes, would you please show me how?Īssuming you're running some flavour of linux, here's one way you could do it:įind out what BLAS library numpy is currently linked against using ldd.įor versions of numpy older than v1.10: $ ldd //numpy/core/_dotblas.soįor example, if I install numpy via apt-get, it links to.
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