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mkl_random
-- a NumPy-based Python interface to Intel (R) MKL Random Number Generation functionality
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 on Anaconda cloud:
conda install -c intel mkl_random
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.
See MKL reference guide for more details: https://software.intel.com/en-us/mkl-developer-reference-c-random-number-generators
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