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Performance Comparison of OpenBLAS* and Intel® Math Kernel Library in R

Today, scientific and business industries collect large amounts of data, analyze them, and make decisions based on the outcome of the analysis. This paper compares the performance of Basic Linear Algebra Subprograms (BLAS), libraries OpenBLAS, and the Intel® Math Kernel Library (Intel® MKL).
Authored by Nguyen, Khang T (Intel) Last updated on 07/06/2019 - 16:40
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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
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Building Large-Scale Image Feature Extraction with BigDL at JD.com

This article shares the experience and lessons learned from Intel and JD teams in building a large-scale image feature extraction framework using deep learning on Apache Spark* and BigDL.
Authored by Jason Dai (Intel) Last updated on 05/30/2019 - 15:56
File Wrapper

Parallel Universe Magazine - Issue 28, April 2017

Authored by admin Last updated on 03/21/2019 - 12:00