The AOCL-Data Analytics Library (AOCL-DA) provides optimized building blocks for data analysis and classical machine learning. APIs are available in C, C++, and Python. There is also a patch to enable scikit-learn users to benefit from the performance of AOCL-DA with minimal code changes.
AOCL-Data Analytics provides ability to:
- Load data from CSV files
- Preprocess data by standardizing, removing missing values and extracting subsets
- Process data using a variety of algorithms, including linear models, clustering methods, decompositions, decision forest and nearest neighbor algorithms
Highlights of AOCL-Data Analytics 5.1
- New APIs for DBSCAN clustering, support vector machines and pairwise distances
- Dynamic dispatch: multiple Zen generation code paths compiled in a single binary, with appropriate code path selected at runtime
- Performance improvements to decision trees, random forest and k-nearest neighbors algorithms
Documentation
- Source code: GitHub
- AOCL-DA API Guide
Downloads
| File Name | Version | Size | Launch Date | OS | Bitness | Description |
| Binary Packages Compiled with AOCC 5.0 | ||||||
| aocl-da-linux-aocc-5.1.0.tar.gz | 5.1 | 37MB | 8/18/2025 | RHEL, Ubuntu, SLES | 64-bit | AOCC compiled AOCL-Data Analytics library binary package SHA-256 checksum: 93623dab705cd4ad1ca689d19b6c81340fd62f40d35f0d27aeab05e3d3be49dd |
| Binary Packages Compiled with GCC 14.2.1 | ||||||
| aocl-da-linux-gcc-5.1.0.tar.gz | 5.1 | 31MB | 05/07/2025 | RHEL, Ubuntu, SLES | 64-bit | GCC compiled AOCL-Data Analytics library binary package sha256 Checksum: eea772f5ec120f44201562919d8c38fa4eeccdeed32bbff0396f952d3bd604f3 |
| Windows Installer Containing AOCL-Data Analytics | ||||||
| AOCL_Windows-setup-5.1.0.408-AMD.exe | 5.1 | 140MB | 05/07/2025 | Windows 11, Windows 10 | 64-bit | Windows installer file containing all the AOCL library binaries compiled with Clang 18. SHA-256 checksum: 61de98148459270ba3bd01f5b0c409299d8c0c144a925f3701e10f72678a328a |
Python Wheels
| File Name | Version | Python Version | Size | Launch Date | OS | Bitness | Description |
| aoclda-5.1.0-cp39-cp39-manylinux_2_35_x86_64.whl | 5.1 | 3.9 | 22MB | 8/18/2025 | RHEL, Ubuntu, SLES | 64-bit | Python package of the AOCC compiled AOCL-Data Analytics library SHA-256 checksum: 47f4de738fe23b157b031876870d92d7eff72a203215de4d66689b2d74e5966e |
| aoclda-5.1.0-cp310-cp310-manylinux_2_35_x86_64.whl | 5.1 | 3.10 | 22MB | 8/18/2025 | RHEL, Ubuntu, SLES | 64-bit | Python package of the AOCC compiled AOCL-Data Analytics library SHA-256 checksum: e0cd9c2c346b87b73577fdb48a66febee78609c50b9077e1add53049f90cadf8 |
| aoclda-5.1.0-cp311-cp311-manylinux_2_35_x86_64.whl | 5.1 | 3.11 | 22MB | 8/18/2025 | RHEL, Ubuntu, SLES | 64-bit | Python package of the AOCC compiled AOCL-Data Analytics library SHA-256 checksum: 8cf61fc6cf8fe880b1b875669ef9bd6008337d477c4daf2c4d0957b99d2cc297 |
| aoclda-5.1.0-cp312-cp312-manylinux_2_35_x86_64.whl | 5.1 | 3.12 | 22MB | 8/18/2025 | RHEL, Ubuntu, SLES | 64-bit | Python package of the AOCC compiled AOCL-Data Analytics library SHA-256 checksum: 15e8e4b2eabcb7093a46bece2adfec36da539885d79b6c86d9c2bb86a993a8c4 |