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4 changes: 2 additions & 2 deletions .github/workflows/build-with-clang.yml
Original file line number Diff line number Diff line change
Expand Up @@ -56,7 +56,7 @@ jobs:
shell: bash -l {0}
run: ls /opt/intel/oneapi/compiler

- name: Build mkl_random
- name: Build mkl-service
shell: bash -l {0}
run: |
source /opt/intel/oneapi/setvars.sh
Expand All @@ -68,7 +68,7 @@ jobs:
ls -l ${CC} ${CXX}
python setup.py develop

- name: Run mkl_random tests
- name: Run mkl-service tests
shell: bash -l {0}
run: |
source /opt/intel/oneapi/setvars.sh
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53 changes: 26 additions & 27 deletions CHANGES.rst → CHANGELOG.md
Original file line number Diff line number Diff line change
@@ -1,57 +1,56 @@
=====================
mkl-service changelog
`mkl-service` changelog
=====================

2.3.0
=====

1.0.0
Fixed CI to actually execute tests. Populated CBWR constants to match MKL headers.
Added tests checking that `cbwr_set` and `cbwr_get` round-trip.

2.2.0
=====

Initial release of `mkl-service` package.
Closed issues #8, #7 and #5.

2.0.0
====
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](http://github.com/IntelPython/mkl-service/issues/8)).

Rerelease of `mkl-service` package with version bumped to 2.0.0 to avoid version clash with `mkl-service` package from Anaconda.
Extended `mkl.cbwrt_get()` to mean `mkl.cbwr('all')`.

Improved argument checking, which raises an informative error.
2.1.0
=====

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).
Change in setup script to not use `numpy.distutils` thus removing numpy as build-time dependency.

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.
Change in conda-recipe to allow conda build to build the recipe, but ignoring run export on mkl-service coming from mkl-devel metadata.

2.0.0
====
2.0.2
=====

Work-around for VS 9.0 not having `inline` keyword, allowing the package to build on Windows for Python 2.7
Correction to `setup.py` to not require Cython at the installation time.

2.0.1
=====

Re-release, with some changes necessary for public CI builds to work.

2.0.2
2.0.0
=====

Correction to `setup.py` to not require Cython at the installation time.
Work-around for VS 9.0 not having `inline` keyword, allowing the package to build on Windows for Python 2.7

2.1.0
2.0.0
=====

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.

2.2.0
=====
Rerelease of `mkl-service` package with version bumped to 2.0.0 to avoid version clash with `mkl-service` package from Anaconda.

Closed issues #8, #7 and #5.
Improved argument checking, which raises an informative error.

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](http://github.com/IntelPython/mkl-service/issues/8)).
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).

Extended `mkl.cbwrt_get()` to mean `mkl.cbwr('all')`.
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.

2.3.0
1.0.0
=====

Fixed CI to actually execute tests. Populated CBWR constants to match MKL headers.
Added tests checking that `cbwr_set` and `cbwr_get` round-trip.
Initial release of `mkl-service` package.
2 changes: 1 addition & 1 deletion LICENSE.txt
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
Copyright (c) 2018-2019, Intel Corporation
Copyright (c) 2018, Intel Corporation

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
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8 changes: 4 additions & 4 deletions README.md
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
# ``mkl-service`` - Python package for run-time control of Intel(R) Math Kernel Library.
# `mkl-service` - Python package for run-time control of Intel® OneAPI Math Kernel Library (OneMKL).
[![Conda package](https://github.com/IntelPython/mkl-service/actions/workflows/conda-package.yml/badge.svg)](https://github.com/IntelPython/mkl-service/actions/workflows/conda-package.yml)
[![Build mkl-service with clang](https://github.com/IntelPython/mkl-service/actions/workflows/build-with-clang.yml/badge.svg)](https://github.com/IntelPython/mkl-service/actions/workflows/build-with-clang.yml)
[![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/IntelPython/mkl-service/badge)](https://securityscorecards.dev/viewer/?uri=github.com/IntelPython/mkl-service)
Expand All @@ -8,19 +8,19 @@

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

---

Intel(R) Math Kernel Library support functions are subdivided into the following groups according to their purpose:
Intel® OneMKL support 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 it use:
A short example, illustrating its use:

```python
import tomopy
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2 changes: 1 addition & 1 deletion examples/example.py
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@@ -1,4 +1,4 @@
# Copyright (c) 2018-2019, Intel Corporation
# Copyright (c) 2018, Intel Corporation
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
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2 changes: 1 addition & 1 deletion mkl/__init__.py
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
# Copyright (c) 2018-2024, Intel Corporation
# Copyright (c) 2018, Intel Corporation
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
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2 changes: 1 addition & 1 deletion mkl/_mkl_service.pxd
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@@ -1,4 +1,4 @@
# Copyright (c) 2018-2024, Intel Corporation
# Copyright (c) 2018, Intel Corporation
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
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2 changes: 1 addition & 1 deletion mkl/_mkl_service.pyx
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
# Copyright (c) 2018-2024, Intel Corporation
# Copyright (c) 2018, Intel Corporation
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
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2 changes: 1 addition & 1 deletion mkl/tests/test_mkl_service.py
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
# Copyright (c) 2018-2024, Intel Corporation
# Copyright (c) 2018, Intel Corporation
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
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2 changes: 1 addition & 1 deletion setup.py
Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
#!/usr/bin/env python
# Copyright (c) 2018-2024, Intel Corporation
# Copyright (c) 2018, Intel Corporation
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
Expand Down
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