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
sign
function for complex floating point data types is updated to match numpy-2.x.x gh-65 ldexp
function is updated to allowint64
explicitly similar to numpy-2.x.x behavior gh-73
Changed
- Migrated from
setup.py
topyproject toml
gh-63 - Changed to dynamic linking and added interface and threading layers gh-72
Fixed
- Fixed a bug for
mkl_umath.is_patched
function gh-66
v0.1.5
This release
- Fixes failures to import
mkl_umath
from 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_umath
out-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']