oneAPI Data Analytics Library (oneDAL) is a powerful machine learning library that helps you accelerate big data analysis at all stages: preprocessing, transformation, analysis, modeling, validation, and decision making.
The library implements classical machine learning algorithms. The boost in their performance is achieved by leveraging the capabilities of Intel® hardware.
oneDAL is part of oneAPI. The current branch implements version 1.1 of oneAPI Specification.
There are different ways for you to build high-performance data science applications that use the advantages of oneDAL:
Check System Requirements before installing oneDAL.
Other related documentation:
oneDAL library is used for Spark MLlib acceleration as part of OAP MLlib project and allows you to get a 3-18x increase in performance compared to the default Apache Spark MLlib.
Technical details: FPType: double; HW: 7 x m5.2xlarge AWS instances; SW: Intel DAAL 2020 Gold, Apache Spark 2.4.4, emr-5.27.0; Spark config num executors 12, executor cores 8, executor memory 19GB, task cpus 8
oneDAL supports distributed computation mode that shows excellent results for strong and weak scaling:
|oneDAL K-Means fit, strong scaling result||oneDAL K-Means fit, weak scaling results|
Technical details: FPType: float32; HW: Intel Xeon Processor E5-2698 v3 @2.3GHz, 2 sockets, 16 cores per socket; SW: Intel® DAAL (2019.3), MPI4Py (3.0.0), Intel® Distribution Of Python (IDP) 3.6.8; Details available in the article https://arxiv.org/abs/1909.11822
Ask questions and engage in discussions with oneDAL developers, contributers, and other users through the following channels:
You may reach out to project maintainers privately at [email protected].
To report a vulnerability, refer to Intel vulnerability reporting policy.
We welcome community contributions. Check our contributing guidelines to learn more.
oneDAL is distributed under the Apache License 2.0 license. See LICENSE for more information.