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 https://software.repos.intel.com/python/conda mkl_umath
To install mkl_umath 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_umath
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_umath numpy==<numpy_version>
Where <numpy_version>
should be the latest version from https://software.repos.intel.com/python/conda/
Intel(R) C compiler and Intel(R) OneAPI Math Kernel Library (OneMKL) are required to build mkl_umath
from source.
If these are installed as part of a oneAPI
installation, the following packages must also be installed into the environment
cmake
ninja
cython
scikit-build
numpy
If build dependencies are to be installed with Conda, the following packages must be installed from the Intel(R) channel
mkl-devel
dpcpp_linux-64
(ordpcpp_win-64
for Windows)numpy-base
then the remaining dependencies
cmake
ninja
cython
scikit-build
and for mkl-devel
and dpcpp_linux-64
in a Conda environment, MKLROOT
environment variable must be set
On Linux
export MKLROOT=$CONDA_PREFIX
On Windows
set MKLROOT=%CONDA_PREFIX%
If using oneAPI
, it must be activated in the environment
On Linux
source ${ONEAPI_ROOT}/setvars.sh
On Windows
call "%ONEAPI_ROOT%\setvars.bat"
finally, execute
CC=icx pip install --no-build-isolation --no-deps .