All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
- Dropped support for Python 3.9 gh-118
- Fixed the run-time dependencies of
mkl-servicepackage to explicitly depend on a non–free-threaded (GIL-enabled) Python gh-111
- Enabled support of Python 3.14 gh-100
- Used
GIT_DESCRIBE_TAGandGIT_DESCRIBE_NUMBERinmeta.yamlinstead of manual stepping the numbers gh-98
- Updated
meta.yamlwith proper license description to pass the validation rules gh-87
- Resolved import issue in the virtual environment which broke loading of MKL libs gh-85
- Migrated from
setup.pytopyproject.tomlgh-66
Tests checking library version moved to the end of the test suite, as after it is run, the state of the library is finalized, and tests that modify that state may fail.
Updated installation instructions.
Transition from nose to unittest and then to pytest to enable support for Python 3.12.
Added Github Actions CI.
Removed six as a dependency.
Update description for PyPI package installation
Fixed issue #14.
Added mkl.set_num_stripes and mkl.get_num_stripes
Also expanded support isa keyword argument values in mkl.enable_instructions(isa=isa) function per recent Intel® oneAPI Math Kernel Library (oneMKL) support.
Fixed CI to actually execute tests. Populated CBWR constants to match MKL headers.
Added tests checking that cbwr_set and cbwr_get round-trip.
Closed issues #8, #7 and #5.
Extended mkl.cbwr_set to recognize 'avx512_e1', 'avx512_mic_e1', as as strict conditional numerical reproducibility, supported via 'avx2,strict', 'avx512,strict' (see issue/8).
Extended mkl.cbwrt_get() to mean mkl.cbwr('all').
Change in setup script to not use numpy.distutils thus removing numpy as build-time dependency.
Change in conda-recipe to allow conda build to build the recipe, but ignoring run export on mkl-service coming from mkl-devel metadata.
Correction to setup.py to not require Cython at the installation time.
Re-release, with some changes necessary for public CI builds to work.
Work-around for VS 9.0 not having inline keyword, allowing the package to build on Windows for Python 2.7
Rerelease of mkl-service package with version bumped to 2.0.0 to avoid version clash with mkl-service package from Anaconda.
Improved argument checking, which raises an informative error.
Loading the package with import mkl initializes Intel(R) MKL library to use LP64 interface (i.e. use of environment variable MKL_INTERFACE will not have effect).
The choice of threading layer can be controlled with environment variable MKL_THREADING_LAYER. However the unset variable is interpreted differently that in Intel(R) MKL itself. If mkl-service detects that Gnu OpenMP has been loaded in Python space, the threading layer of Intle(R) MKL will be set to Gnu OpenMP, instead of Intel(R) OpenMP.
Initial release of mkl-service package.