Other Intel projects for high-performance Python

Intel provides a number of Python* packages which allow you to get the best performance and scalability of numercial, scientific, and data analytics applications. Some of these projects listed below.

Intel-optimized Python* packages

Package Name	Description
numpy	Numpy* accelerated with Intel® MKL
scikit-learn	Scikit-Learn* accelerated with Intel® Data Analytics Library
mkl_fft	Python interfaces for Intel® MKL FFT functionality
mkl_random	Python interfaces for Intel® MKL random number generation functionality
mkl_service	Python interfaces for Intel® MKL service functions
daal4py	Python interfaces for Intel® Data Analytics Library
smp	Python module for composable multi-processing and multi-threading
sdc	Numba* compiler extension for Pandas*

Optimized versions of community projects may dramatically boost performance of Python* codes with minimum to no required code changes. Visit benchmarks webpage for more details.

Intel also directly upstream optimizations to some open source projects such as XGBoost* and Numba*.

For more information please visit Intel® Distribution for Python* product page.