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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
Article

Scale-Up Implementation of a Transportation Network Using Ant Colony Optimization (ACO)

In this article an OpenMP* based implementation of the Ant Colony Optimization algorithm was analyzed for bottlenecks with Intel® VTune™ Amplifier XE 2016 together with improvements using hybrid MPI-OpenMP and Intel® Threading Building Blocks were introduced to achieve efficient scaling across a four-socket Intel® Xeon® processor E7-8890 v4 processor-based system.
Authored by Sunny G. (Intel) Last updated on 07/05/2019 - 19:10
Article
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

Improve Performance of K-Means with Intel® Data Analytics Acceleration Library

This article discusses an unsupervised machine-learning algorithm called K-means that can be used to solve the data problems.
Authored by Nguyen, Khang T (Intel) Last updated on 01/24/2018 - 15:35
Article

Case Study – Using the Intel® Deep Learning SDK for Training Image Recognition Models

In this case study, we explore LeNet*,one of the prominent image recognition topologies for handwritten digit recognition, and show how the training tool can be used to visually set up, tune, and train the Mixed National Institute of Standards and Technology (MNIST) dataset on Caffe* optimized for Intel® architecture. Data scientists are the intended audience.
Authored by Meghana R. (Intel) Last updated on 01/24/2018 - 15:35
Video

Get Started with the Intel® Deep Learning SDK

This video shows the Intel® Deep Learning SDK.

Authored by Gerald M. (Intel) Last updated on 01/24/2018 - 15:35
Article

R 语言中的OpenBLAS*和英特尔® 数学核心函数库的性能比较

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 - 16:30
Article

Intel® Math Kernel Library for Deep Learning Networks: Part 1–Overview and Installation

Learn how to install and build the library components of the Intel MKL for Deep Neural Networks.
Authored by Bryan B. (Intel) Last updated on 03/11/2019 - 13:17
Article

Intel® Math Kernel Library for Deep Neural Networks: Part 2 – Code Build and Walkthrough

Learn how to configure the Eclipse* IDE to build the C++ code sample, along with a code walkthrough based on the AlexNet deep learning topology for AI applications.
Authored by Bryan B. (Intel) Last updated on 05/23/2018 - 11:00