The following article will show you how to create an Intel® Distribution for Python environment with Anaconda.
The Intel® Distribution for Python provides the following benefits1
- Achieve faster Python application performance — right out of the box — with minimal or no changes to your code.
- Accelerate NumPy, SciPy, and scikit-learn with integrated Intel® Performance Libraries such as Intel® Math Kernel Library and Intel® Data Analytics Acceleration Library (Intel® DAAL)
- Access the latest vectorization and multithreading instructions, Numba and Cython, composable parallelism with Threading Building Blocks, and more
First update Conda:
$ conda update conda
Tell Conda to choose Intel packages over default packages, when available:
$ conda config -add channels intel
Create an environment with the full Intel distribution, like this:
$ conda create -n intel intelpython3_full python=3
Then follow the usual directions for activating the environment:
$ conda activate intel
To deactivate the environment:
$ conda deactivate
You should now see accelerated performance from installed packages including Python, NumPy, SciPy and more.
You can use the usual conda install commands for additional packages.
- Intel® Distribution for Python — https://software.intel.com/en-us/distribution-for-python ↩