IntelPython / mkl_umath

Package implementing NumPy's UFuncs based on SVML and MKL VML

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mkl_umath

mkl_umath._ufuncs exposes Intel(R) Math Kernel Library powered version of loops used in the patched version of NumPy, that used to be included in Intel(R) Distribution for Python*.

Patches were factored out per community feedback (NEP-36).

mkl_umath started as a part of Intel (R) Distribution for Python* optimizations to NumPy, and is now being released as a stand-alone package. It can be installed into conda environment using

   conda install -c intel mkl_umath

To install mkl_umath Pypi package please use following command:

   python -m pip install --i https://pypi.anaconda.org/intel/simple -extra-index-url https://pypi.org/simple mkl_umath

If command above installs NumPy package from the Pypi, please use following command to install Intel optimized NumPy wheel package from Anaconda Cloud:

   python -m pip install --i https://pypi.anaconda.org/intel/simple -extra-index-url https://pypi.org/simple mkl_umath numpy==<numpy_version>

Where <numpy_version> should be the latest version from https://anaconda.org/intel/numpy


Building

Intel(R) C compiler and Intel(R) Math Kernel Library are required to build mkl_umath from source:

# ensure that MKL is installed, icc is activated
export MKLROOT=$CONDA_PREFIX
python setup.py config_cc --compiler=intelem build_ext --inplace

About

Package implementing NumPy's UFuncs based on SVML and MKL VML

License:BSD 3-Clause "New" or "Revised" License


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