Skip to end of metadata
Go to start of metadata

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 3 Next »

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

Using

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

Version

Conda Activate

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
 Installed Packages:
(/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

  • No labels