Intel® Data Analytics Acceleration Library - Samples

Published: 02/12/2016  

Last Updated: 09/17/2017

These Intel® Data Analytics Acceleration Library samples are a collection of code samples for various algorithms that you can include in your program and immediately use with Hadoop*, Spark*, message-passing interface (MPI), MySQL*, or KDB+*. Each of the samples is designed to show how to use Intel DAAL:  

  • with the Intel® MPI Library in  C++ or Python* application
  • with a MySQL* database in a C++ application
  • on the Hadoop* cluster in a Java* application
  • on the Spark* cluster in Scala, Java* or Python* application

New KDB+* database and neural networks samples designed to show how to

  • use Intel DAAL with a KDB+* database in a C++ application
  • create the most common neural network topologies, such as LeNet*, GoogleNet*, AlexNet*, ResNet-50* in a C++ or Python* application.

New Spark* Scala samples designed to show how to:

  • use Intel DAAL on the Spark cluster in a Scala application
  • use Intel DAAL as a faster drop-in replacement for Spark MLlib on couple of algorithms: K-Means clustering, Principal component analysis (PCA) using the correlation method, Singular Value Decomposition (SVD).

Each sample has a "readme.html" in the root folder with system requirements, detailed build and run instructions

For Intel DAAL Sample 2019, please get from

​Sample bundles

​​Open Source

Product and Performance Information


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