https://github.com/intelpython/mkl_random

Python interface to Intel(R) Math Kernel Library's random number generation functionality
https://github.com/intelpython/mkl_random

mkl numpy python

Last synced: about 5 hours ago
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Python interface to Intel(R) Math Kernel Library's random number generation functionality

• Host: GitHub
• URL: https://github.com/intelpython/mkl_random
• Owner: IntelPython
• License: bsd-3-clause
• Created: 2017-10-05T22:14:29.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2024-10-11T15:34:28.000Z (3 months ago)
• Last Synced: 2025-01-03T18:08:15.368Z (7 days ago)
• Topics: mkl, numpy, python
• Language: Python
• Homepage: https://intelpython.github.io/mkl_random/
• Size: 679 KB
• Stars: 26
• Watchers: 6
• Forks: 11
• Open Issues: 5
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt
  • Codeowners: .github/CODEOWNERS

Awesome Lists containing this project

README

        
## ``mkl_random`` -- a NumPy-based Python interface to Intel (R) MKL Random Number Generation functionality

[![Conda package using conda-forge](https://github.com/IntelPython/mkl_random/actions/workflows/conda-package-cf.yml/badge.svg)](https://github.com/IntelPython/mkl_random/actions/workflows/conda-package-cf.yml)

`mkl_random` has started as Intel (R) Distribution for Python optimizations for NumPy.

Per NumPy's community suggestions, voiced in https://github.com/numpy/numpy/pull/8209, it is being released as a

stand-alone package.

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

```

  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==

```

Where `` 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 (R) Math Kernel Library (MKL), `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'