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

Conda package Build mkl-service with clang OpenSSF Scorecard

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 and runtime dependencies, including mkl, and build mkl-service.

With an existing system or Conda mkl installation, build dependencies

  • mkl-devel
  • meson-python
  • cmake
  • ninja
  • cython

then, simply execute

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