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change to dynamic linking and add interface and threading layers #72

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dbb707e
change to dynamic linking and add interface and threading layers
vtavana May 7, 2025
f97cb04
Merge branch 'main' into add-ilp64
vtavana May 12, 2025
e76a550
update changelog
vtavana May 15, 2025
65ce08d
Merge branch 'main' into add-ilp64
vtavana May 15, 2025
e5e5454
fix typos
vtavana May 15, 2025
edde112
Merge branch 'main' into add-ilp64
vtavana May 20, 2025
471292d
Merge branch 'main' into add-ilp64
vtavana May 23, 2025
af2acec
switch to lp64
vtavana May 23, 2025
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3 changes: 1 addition & 2 deletions .github/workflows/build_pip.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -42,10 +42,9 @@ jobs:

- name: Install Compiler and MKL
run: |
conda install mkl-devel mkl-service dpcpp_linux-64
conda install mkl-devel tbb-devel dpcpp_linux-64
python -c "import sys; print(sys.executable)"
which python
python -c "import mkl; print(mkl.__file__)"

- name: Build conda package
run: |
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5 changes: 4 additions & 1 deletion CHANGELOG.md
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Expand Up @@ -5,12 +5,15 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

## [dev] (MM/DD/YY)
This release updates `mkl_umath` to be aligned with both numpy-1.26.x and numpy-2.x.x.

### Added
* `mkl_umath` is now aligned with both numpy-1.26,x and numpy-2.x.x [gh-65](https://github.com/IntelPython/mkl_umath/pull/65)
* The definition of `sign` function for complex floating point data types is updated to match numpy-2.x.x [gh-65](https://github.com/IntelPython/mkl_umath/pull/65)
* `ldexp` function is updated to allow `int64` explicitly similar to numpy-2.x.x behavior [gh-73](https://github.com/IntelPython/mkl_umath/pull/73)

### Changed
* Migrated from `setup.py` to `pyproject toml` [gh-63](https://github.com/IntelPython/mkl_umath/pull/63)
* Changed to dynamic linking and added interface and threading layers [gh-72](https://github.com/IntelPython/mkl_umath/pull/72)

### Fixed
* Fixed a bug for `mkl_umath.is_patched` function [gh-66](https://github.com/IntelPython/mkl_umath/pull/66)
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6 changes: 5 additions & 1 deletion CMakeLists.txt
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Expand Up @@ -23,7 +23,11 @@ cmake_print_variables(Python_NumPy_INCLUDE_DIRS)
set(CYTHON_FLAGS "-t -w \"${CMAKE_SOURCE_DIR}\"")
find_package(Cython REQUIRED)

set(MKL_LINK sdl)
find_package(TBB REQUIRED)
set(MKL_ARCH "intel64")
set(MKL_LINK "dynamic")
set(MKL_THREADING "tbb_thread")
set(MKL_INTERFACE "lp64")
find_package(MKL REQUIRED)

if(WIN32)
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3 changes: 2 additions & 1 deletion README.md
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Expand Up @@ -47,6 +47,7 @@ If these are installed as part of a `oneAPI` installation, the following package

If build dependencies are to be installed with Conda, the following packages must be installed from the Intel(R) channel
- `mkl-devel`
- `tbb-devel`
- `dpcpp_linux-64` (or `dpcpp_win-64` for Windows)
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side question - why dpcpp compiler referenced here as there is no sycl us in mkl_umath?

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The build instructions have been recommending using the Intel LLVM compiler for some time now—mostly to have a working C compiler, especially one we test with

- `numpy-base`

Expand All @@ -56,7 +57,7 @@ then the remaining dependencies
- `cython`
- `scikit-build`

and for `mkl-devel` and `dpcpp_linux-64` in a Conda environment, `MKLROOT` environment variable must be set
and for `mkl-devel`, `tbb-devel` and `dpcpp_linux-64` in a Conda environment, `MKLROOT` environment variable must be set
On Linux
```sh
export MKLROOT=$CONDA_PREFIX
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3 changes: 1 addition & 2 deletions conda-recipe-cf/meta.yaml
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Expand Up @@ -28,11 +28,10 @@ requirements:
- scikit-build
- python
- mkl-devel
- tbb-devel
- numpy
run:
- python
- mkl
- mkl-service
- {{ pin_compatible('intel-cmplr-lib-rt') }}

test:
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3 changes: 1 addition & 2 deletions conda-recipe/meta.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -28,11 +28,10 @@ requirements:
- scikit-build
- python
- mkl-devel
- tbb-devel
- numpy-base
run:
- python
- mkl
- mkl-service
- {{ pin_compatible('intel-cmplr-lib-rt') }}
- {{ pin_compatible('numpy') }}

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