Releases: IntelPython/mkl_umath
v0.2.0
This release updates mkl_umath to be aligned with both numpy-1.26.x and numpy-2.x.x.
Added
- The definition of 
signfunction for complex floating point data types is updated to match numpy-2.x.x gh-65 ldexpfunction is updated to allowint64explicitly similar to numpy-2.x.x behavior gh-73
Changed
- Migrated from 
setup.pytopyproject tomlgh-63 - Changed to dynamic linking and added interface and threading layers gh-72
 
Fixed
- Fixed a bug for 
mkl_umath.is_patchedfunction gh-66 
v0.1.5
This release
- Fixes failures to import 
mkl_umathfrom virtual environment on Linux 
v0.1.4
This release
- Adds a fix for a bug in in-place addition with negative zeros
 - Adds support for 
mkl_umathout-of-the-box in virtual environments on Windows 
v0.1.2
Update build system from removed NumPy distutils to scikit-build, gain ability to build with Intel LLVM compiler ICX. Update to build with NumPy 2.0 and older.
v0.1.1.post0
v0.1.1
Released version of mkl_umath.
The package implements numpy.ufunc instances which are powered by Intel(R) Math Kernel Library's Vector Math component and Intel(R) C Compiler generated calls to Intel(R) Short Vector Math Library functions for appropriate data types.
The package provides for a way to register typed evaluation loops provided by this package with the numpy.ufunc instances, thus monkey patching NumPy for improved performance (e.g. mkl_umath.use_in_numpy() and mkl_umath.restore().)
Supported types can be queries using attributes of numpy.ufunc  instance:
In [44]: mkl_umath.multiply.types
Out[44]: ['ff->f', 'dd->d', 'FF->F', 'DD->D']