Programs for Programmers

Intel(r) Data Analytics Acceleration Library


Boost machine learning & big data analytics performance with easy-to-use library

  • Performance across spectrum of Intel® architecture devices
  • Optimizes data ingestion together with algorithmic computation for highest analytics throughput
  • Includes Python*, C++, and Java* APIs and connectors to popular data sources including Spark* and Hadoop*
  • Free and open source community-supported versions are available, as well as paid versions that include premium support.

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 & consumer preference analysis are just a few examples of areas where high performance analysis of large data sets is a critical competency 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) is designed to help software developers reduce the time it takes to develop their applications and provide them with improved performance. Intel DAAL helps applications make better predictions faster and analyze larger data sets with the available compute resources at hand. The library is updated to take 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.

Intel DAAL Fits in the Big Data Ecosystem

Intel DAAL addresses all stages of the data analytics pipeline: Pre-processing, Transformation, Analysis, Modeling, Validation, and Decision Making.


Data Analytics Library


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 Intel processor-based systems.

Specs at a Glance


Processors Intel® processors, coprocessors and compatibles
Languages Python*, C++, Java
Development Tools and Environments

Microsoft Visual Studio* (Windows*)

Eclipse*/CDT* (Linux*)

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