Intel Distributed for Python

The Intel Distribution for Python repository does not appear to be stable. Please consider using Miniforge if your software is complete with the software provided in the conda-forge repository.

The Modules software package can dynamically switch and configure the environment settings required to use the application by executing the module command. You can also easily change the environment settings when switching between different versions of an application. Please refer to Modules for details.

You can check a list of available module files with the module avail command.

Version Python Version Module File Name System A System B/C/G Cloud System
2024.2 (default) 3.9.19 intel-python/2024.2 + + +

+ ： Available for all users
AU ： Available for academic users only
KU ： Available for Kyoto University members only
- ： Not available

Set up the environment by executing the module command. (Load the version of the module file which you want to use.)

$ module load intel-python

You can check the standard installed libraries with the conda command.

$ conda list
# packages in environment at /opt/system/app/intelpython/2024.2.0:
#
# Name                    Version                   Build  Channel
_libgcc_mutex             0.1                 conda_forge    conda-forge
_openmp_mutex             4.5                       2_gnu    conda-forge
absl-py                   1.4.0              pyhd8ed1ab_0    conda-forge
aiohttp                   3.9.5            py39hd1e30aa_0    conda-forge
aiosignal                 1.3.1              pyhd8ed1ab_0    conda-forge

...

Name 2024.2
conda 23.9.0
jupyterlab 4.2.2
keras 2.15.0
matplotlib 3.8.4
numpy 1.26.4
pandas 1.5.3
pip 24.0
python 3.9.19
pytorch 2.0.1
scikit-learn 1.4.2
tensorflow 2.15.0

You can add applications by creating a virtual environment

  1. Creation of a virtual environment

    conda create -n myenv
    • When you create a virtual environment, you will be asked to run "conda init," but we recommend that you do not run conda init because the necessary environment settings are already made in the module file.

  2. Switch to the created virtual environment. If the left-most part of the terminal changes (myenv), it is switched to the virtual environment you created. 

    conda activate myenv

  3. Software Installation

    $ conda install tensorflow

When you log in again, you will need to load the module file and switch to virtual environment.

Please refer to Python for the use of the standard python.
You can use Jupyter Notebook and Jupyter Lab in the Intel Distribution for Python environment. Please refer to Jupyter Lab for the details.