mkl-service - Python package for run-time control of Intel® oneAPI Math Kernel Library (oneMKL).

---

To install conda package, use conda install -c https://software.repos.intel.com/python/conda/ mkl-service, or conda install -c conda-forge mkl-service.

To install PyPI package, use python -m pip install mkl-service.

---

Intel® oneAPI Math Kernel Library (oneMKL) supports functions are subdivided into the following groups according to their purpose:

• Version Information
• Threading Control
• Timing
• Memory Management
• Conditional Numerical Reproducibility Control
• Miscellaneous

A short example, illustrating its use:

>>> import mkl
>>> mkl.domain_set_num_threads(1, domain="fft") # oneMKL FFT functions to run sequentially
# 'success'

For more information about the usage of support functions see Developer Reference for Intel® oneAPI Math Kernel Library for C.

---

Building

A C compiler and Intel(R) oneAPI Math Kernel Library (oneMKL) are required to build mkl-service from source.

Executing

python -m pip install .

will pull in the required build dependencies, including mkl, and build mkl-service.

If you already have mkl installed (from your system or a Conda environment) and want to reuse it instead of pulling a fresh copy into an isolated build, first install the build dependencies:

python -m pip install mkl-devel meson-python cmake ninja cython

then build against the existing installation with:

python -m pip install --no-build-isolation --no-deps .