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Roofline Analysis in Intel Advisor 2017

What is Roofline Analysis? First proposed by UC Berkeley professors in 2009, Roofline is designed to analyze performance in multi-core and many core systems, and can uncover the bottlenecks that are impacting overall performance. In this video, Intel Software expert Alex Shinsel takes us for a spin with Advisor’s new …

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Meet The New Intel Storage Performance Snapshot Tool

Helping to Locate, Eliminate Performance Bottlenecks How will changing your storage configuration impact overall system performance? Check out a demo of Intel’s new performance tool with a live demo by Data Center Solutions Architect Ken Letourneau  

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Breaking Down OpenMP Loops

OpenMP can bring amazing performance boosts to your applications. This presentation breaks down OpenMP loops that have no dependencies. It also shows how easy it is to parallelize with OpenMP by using compiler directives.

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2D Fourier Transforms using Intel’s Math Kernel Library

Many tasks can benefit from 2D Fourier transforms, and in this video Slashdot Media Contributing Editor Rick Leinecker demonstrates how the Intel MKL makes the task easy  

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Profiling Python Code with Intel Vtune Amplifier

Even experienced Python programmers fall into coding traps once in a while. To help find out what’s really going on, watch this video where Intel’s Lead Technical Consulting Engineer Kevin O’Leary provides a hands-on demo showing how to use Intel VTune Amplifier to find hot spots in Python code that …

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Using Intel’s Math Kernel Library for Eigenvectors

Eigenvalues and eigenvectors are key in many machine learning tasks from facial recognition to vibration analysis. In this video, Slashdot Media Contributing Editor Rick Leinecker demonstrates what eigenvalues and eigenvectors are, their role in developing code, and how Intel’s Math Kernel Library (MKL) can accelerate their use and adoption.

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Deep Learning, Python and Intel Libraries: A Chat with Intel’s Kent Moffat

Automating the drudgery of repetitive tasks is one of the key applications of Deep Learning, a subset of machine learning. In this interview with Go Parallel Editor Michael Krieger, Intel Sr Product Manager Kent Moffat discusses how developers can take advantage of the new Intel Distribution for Python and libraries that …

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Screaming Fast Analytics with Intel Performance Libraries

Taming the Data Deluge with high-level algorithms and low-level primitives Machine Learning and Big Data demand powerful tools to tame the data beast. Intel has created two libraries, the Math Kernel Library (MKL) and Data Analytics Acceleration Library (DAAL) to serve most every developer’s need. Watch this brief video to …

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Using Intel Performance Primitives (IPP) for Fast Fourier Transforms (FFTs)

Video Presentation shows how easy Fourier Transforms are, and how fast they can execute Fourier Transforms are difficult to do, and the code usually takes a lot of time to execute. But Intel’s Performance Primitives take away the hassle, according to this video by Slashdot Media Contributing Editor Rick Leinecker

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Best Approaches to Multithreading with OpenMP

Multithreading has a lot of facets to cover to be successful. In this video, Slashdot Media Contributing Editor Rick Leinecker examines several targets and methodologies to consider as you get underway.

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