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
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