mkl_random started as a part of Intel® Distribution for Python optimizations to NumPy.

Per NumPy's community suggestions, voiced in numpy/numpy#8209, it is being released as a stand-alone package.

Prebuilt mkl_random can be installed into conda environment from Intel's channel using:

  conda install -c https://software.repos.intel.com/python/conda mkl_random

or from conda forge channel:

   conda install -c conda-forge mkl_random

To install mkl_random PyPI package please use following command:

   python -m pip install -i https://software.repos.intel.com/python/pypi --extra-index-url https://pypi.org/simple mkl_random

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

   python -m pip install -i https://software.repos.intel.com/python/pypi --extra-index-url https://pypi.org/simple mkl_random numpy==<numpy_version>

Where <numpy_version> should be the latest version from https://software.repos.intel.com/python/conda/

mkl_random is not fixed-seed backward compatible drop-in replacement for numpy.random, meaning that it implements sampling from the same distributions as numpy.random.

For distributions directly supported in Intel® OneMKL, method keyword is supported:

   mkl_random.standard_normal(size=(10**5, 10**3), method='BoxMuller')

Additionally, mkl_random exposes different basic random number generation algorithms available in MKL. For example to use SFMT19937 use

   mkl_random.RandomState(77777, brng='SFMT19937')

For generator families, such that MT2203 and Wichmann-Hill, a particular member of the family can be chosen by specifying brng=('WH', 3), etc.

The list of supported by mkl_random.RandomState constructor brng keywords is as follows:

• 'MT19937'
• 'SFMT19937'
• 'WH' or ('WH', id)
• 'MT2203' or ('MT2203', id)
• 'MCG31'
• 'R250'
• 'MRG32K3A'
• 'MCG59'
• 'PHILOX4X32X10'
• 'NONDETERM'
• 'ARS5'

To build mkl_random from sources on Linux:

• install a recent version of MKL, if necessary;
• execute source /path_to_oneapi/mkl/latest/env/vars.sh;
• execute python -m pip install .