Intel® Data Analytics Acceleration Library (Intel® DAAL)

Boost machine learning and data analytics performance with this easy-to-use library

  • Helps applications deliver better predictions faster
  • Analyzes larger data sets with the same compute resources
  • Optimizes data ingestion and algorithmic compute together for the highest performance
  • Supports offline, streaming, and distributed usage models to meet a range of application needs
  • Take advantage of Priority Support―connect privately with Intel engineers for technical questions

Also available as an open source version

Big data is changing the world of computing by extracting value from the increasing volume, variety, and velocity of data generated in many different industries and domains. Genomics, risk, social network, and consumer preference analysis are just a few examples where high-performance analysis of large data sets is critical in today's compute landscape.

For most of these tasks, computational speed is a key ingredient for success. The Intel® Data Analytics Acceleration Library (Intel® DAAL) helps software developers reduce the time it takes to develop high-performance applications. Intel DAAL enables applications to make better predictions faster and analyze larger data sets with available compute resources. The library also takes advantage of next-generation processors even before they're available. Just link to the newest version and your code is ready for when those new chips hit the market.

Download Options

Intel DAAL is available as part of the Intel® Parallel Studio XE and Intel® System Studio tool suites. It also has free stand-alone and open source versions (available via YUM, APT-GET, and conda* repositories). A license purchase includes Priority Support.

Intel Parallel Studio XE

Intel System Studio

Intel DAAL Fits in the Data Analytics Ecosystem

This library addresses all stages of the data analytics pipeline: preprocessing, transformation, analysis, modeling, validation, and decision-making.

illustration of the data analytics pipeline

Intel DAAL is developed by the same team as the Intel® Math Kernel Library (Intel® MKL)—the leading math library in the world. This team works closely with Intel® processor architects to squeeze performance from systems based on Intel processors.

With this level of performance tuning, Intel DAAL outperforms other solutions for developers and data scientists. The following benchmark compares performance of the XGBoost implementation in Intel DAAL to the XGBoost open source project. The Y axis shows a speedup factor of two to twelve times the performance for four representative classification and regression test cases.

What’s New in the 2019 Edition

  • Logistic regression—the most widely used classification algorithm
  • Extended gradient boosting functionality for inexact split calculations and user-defined callback canceling to provide greater flexibility
  • User-defined data modification procedure supports a wide range of feature extraction and transformation techniques

Benefits of Priority Support

Paid licenses of Intel® Software Development Tools include Priority Support for one year from your date of purchase, with options to extend support at a reduced rate. Benefits include:

  • Direct and private interaction with Intel engineers. Submit confidential inquiries and code samples via the online service center.
  • Responsive help with your technical questions and other product needs.
  • Free access to all new product updates and access to older versions.
  • Learn from other experts via community product forums.
  • Access to a vast library of self-help documents that build off decades of experience for creating high-performance code.

Specs at a Glance

Processors Intel Atom®, Intel Core™, Intel® Xeon®, and Intel® Xeon Phi™ processors and compatible processors
Languages Python*, C++, and Java*
Development Tools and Environments

Microsoft Visual Studio* (Windows*)

Eclipse* and CDT* (Linux*)

Operating Systems Use the same API for application development on multiple operating systems: Windows, Linux, and macOS*

For complete information, see the release notes and documentation.