Article

Introducing DNN primitives in Intel® Math Kernel Library

Please notes: Deep Neural Network(DNN) component in MKL is deprecated since intel® MKL ​2019 and will be removed in the next intel® MKL Release.

Authored by Vadim Pirogov (Intel) Last updated on 03/21/2019 - 12:00
Article

Enabling Intel® MKL in PETSc applications

 
Authored by Gennady F. (Blackbelt) Last updated on 05/24/2018 - 15:48
Article

Maximize TensorFlow* Performance on CPU: Considerations and Recommendations for Inference Workloads

This article will describe performance considerations for CPU inference using Intel® Optimization for TensorFlow*
Authored by Nathan Greeneltch (Intel) Last updated on 04/01/2019 - 13:01
Article

Tutorial for Intel® DAAL: Using Simple C++ Examples

System Environment

Intel® DAAL version : 2016 Gold Initial Release (w_daal_2016.0.110.exe)

OS : Windows* 8.1

IDE : Visual Studio 2013

 

Authored by JON J K. (Intel) Last updated on 07/03/2019 - 10:17
Blog post

The True Benefits of Computing

For anyone what wasn't able to attend the Microsoft Worldwide Partner Conference, one of the 3 key finds that I learned was that there are many ways in which computing benefits people, but not all of them are readily apparent - so here's a review of some ways in which computing helps us!
Authored by CaptGeek (Intel) Last updated on 07/04/2019 - 17:43
Article

A Tutorial on the C++ API of Intel® Data Analytics Acceleration Library

Intel® DAAL is a part of Intel® Parallel Studio XE 2016, a developer toolkit for HPC and technical computing applications. Intel® DAAL is a powerful library for big data developers that turns large data clusters into meaningful information with advanced analytics algorithms. In this tutorial, we will see how to build and run Intel® DAAL C++ examples included in the package.
Authored by Zhang, Zhang (Intel) Last updated on 07/06/2019 - 10:53
Article

A Tutorial on the Java API of Intel® Data Analytics Acceleration Library

Intel® DAAL is a part of Intel® Parallel Studio XE 2016, a developer toolkit for HPC and technical computing applications. Intel® DAAL is a powerful library for big data developers that turns large data clusters into meaningful information with advanced analytics algorithms. In this tutorial, we will see how to build and run Intel® DAAL Java examples included in the package.
Authored by Zhang, Zhang (Intel) Last updated on 07/06/2019 - 10:54
Article

Intel® Data Analytics Acceleration Library - Decision Trees

Decision trees method is one of most popular approaches in machine learning. They can easily be used to solve different classification and regression tasks.
Authored by Gennady F. (Blackbelt) Last updated on 07/06/2019 - 10:58
Article

Tutorial for Intel® DAAL : Using Simple Java* Examples

System Environment

Intel® DAAL version : 2016 Gold Initial Release (w_daal_2016.0.110.exe)

OS : Windows 8.1

Authored by JON J K. (Intel) Last updated on 07/06/2019 - 11:41
Article

Using Intel® Data Analytics Acceleration Library to Improve the Performance of Naïve Bayes Algorithm in Python*

This article discusses machine learning and describes a machine learning method/algorithm called Naïve Bayes (NB) [2]. It also describes how to use Intel® Data Analytics Acceleration Library (Intel® DAAL) [3] to improve the performance of an NB algorithm.
Authored by Nguyen, Khang T (Intel) Last updated on 07/06/2019 - 16:40