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IDF'15 Webcast: Data Analytics and Machine Learning

This Technology Insight will demonstrate how to optimize data analytics and machine learning workloads for Intel® Architecture based data center platforms. Speaker: Pradeep Dubey Intel Fellow, Intel Labs Director, Parallel Computing Lab, Intel Corporation
Authored by Mike P. (Intel) Last updated on 07/06/2019 - 16:40
Article

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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Live Webinar: Boost Python* Performance with Intel® Math Kernel Library

Python* is a popular open-source scripting language known for its easy-to-learn syntax and active developer community.
Authored by Mike P. (Intel) Last updated on 06/07/2017 - 10:28
Article

Set Up Intel® Software Optimization for Theano* and Supporting Tools

Get recipes for installing development tools and libraries on various platforms for the Python library.
Authored by Sunny G. (Intel) Last updated on 05/08/2018 - 10:50
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

MeritData Speeds Up a Big Data Platform

MeritData has to ensure its data mining algorithms are as efficient as possible. Intel worked with MeritData’s algorithm engineers to optimize the company’s multiple data mining algorithms using Intel® Data Analytics Acceleration Library (Intel® DAAL) and Intel® Math Kernel Library (Intel® MKL). The result was average performance improvements ranging from 3x all the way to 14x.
Authored by Sally Sams (Intel) Last updated on 06/01/2017 - 11:26
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
Article

Distributed Deep Learning with Docker*, Intel® Nervana™ technology, neon™, and Pachyderm*

The recent advances in machine learning and artificial intelligence are amazing! It seems like we see something groundbreaking every day, from self-driving cars, to AIs learning complex games.

Authored by Daniel W. Last updated on 06/08/2018 - 11:40
Video

Techniques Employed to Accelerate NumPy & SciPy in Intel® Distribution for Python*

Get high performance Python* at your fingertips with the free Intel® Distribution for Python, and experience significant speedups for NumPy and SciPy with the In

Authored by Gerald M. (Intel) Last updated on 06/04/2019 - 08:21
Video

Intel® Distribution for Python – Highlights & Overview

Get high performance Python at your fingertips with the free Intel® Distribution for Python.

Authored by Gerald M. (Intel) Last updated on 06/04/2019 - 08:25