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Overview

Intel Distribution for Python: provides:
- Near-native performance through acceleration of core numerical and machine learning packages with libraries like the Intel® oneAPI Math Kernel Library and Intel® oneAPI Data Analytics Library.
- Support for the latest CPU instructions to accelerate workloads.
- Performance using all available CPU cores on laptops, desktops, and powerful servers.
- Productivity tools for compiling Python code into optimized instructions.
- Essential Python bindings for easing integration of Intel native tools with your Python project.

Using

On Bearooth, these come in the form of conda environments. The following are currently available:

Version

Conda Activate

2023.1

/apps/u/opt/compilers/oneapi/2023.1/intelpython/latest

2023.0

/apps/u/opt/compilers/oneapi/2023.0/intelpython/latest

2022.3

/apps/u/opt/compilers/oneapi/2022.3/intelpython/latest

Example:

[]$ module load miniconda3/23.1.0
[]$ conda activate /apps/u/opt/compilers/oneapi/2022.3/intelpython/latest
(/apps/u/opt/compilers/oneapi/2022.3/intelpython/latest) []$ python --version
Python 3.9.12 :: Intel Corporation

(/apps/u/opt/compilers/oneapi/2022.3/intelpython/latest) [salexan5@bmgt1 ~]$ pip list
Package                Version
---------------------- -----------------------
asn1crypto             1.5.1
brotlipy               0.7.0
certifi                2022.6.15
cffi                   1.15.1
chardet                4.0.0
charset-normalizer     2.0.12
conda                  4.11.0
conda-package-handling 1.8.1
cryptography           36.0.2
cycler                 0.10.0
Cython                 0.29.25
dpctl                  0.13.0+8.g921229cca
dpnp                   0.10.1
funcsigs               1.0.2
future                 0.18.2
idna                   2.10
joblib                 1.0.1
kiwisolver             1.3.2
libarchive-c           2.9
llvmlite               0.38.1+0.g650c36d.dirty
matplotlib             3.4.3
mkl-fft                1.3.1
mkl-random             1.2.2
mkl-service            2.4.0
mkl-umath              0.1.1
mpi4py                 3.0.3
numba                  0.55.1
numba-dpex             0.18.1+8.ga7a1065
numexpr                2.8.1
numpy                  1.21.2
packaging              21.3
pandas                 1.3.5
pdfminer.six           20220506
Pillow                 8.4.0
pip                    22.1.2
pycosat                0.6.3
pycparser              2.21
pyeditline             2.0.1
pyOpenSSL              22.0.0
pyparsing              3.0.3
PySocks                1.7.1
python-dateutil        2.8.2
pytz                   2022.1
PyYAML                 6.0
requests               2.25.1
ruamel-yaml-conda      0.15.100
scikit-learn           0.24.2
scipy                  1.7.3
setuptools             58.0.4
six                    1.16.0
SMP                    0.1.4
TBB                    0.2
threadpoolctl          2.2.0
tqdm                   4.62.2
urllib3                1.26.11
wheel                  0.37.1
xgboost                1.4.2