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The Tenets of Code Modernization

Code modernization starts with taking advantage of the resources that are available to an application. The easiest way to modernize is by attempting to parallelize sections, since multiple processors or cores can greatly speed execution time if you parallelize your code. This presentation gets you started.

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Want Faster Code Faster? Check Out Parallel Studio XE?

Modern code needs to be both threaded and vectorized to get the most out of today’s multicore systems. The fastest way to get there is to take advantage of the libraries and tools that comprise Intel’s Parallel Studio XE (PSXE). This brief video demonstrates the benefits of PSXE while designing, …

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Thread Synchronization and OpenMP: Mechanisms Ease Code Integrity

  Spawning multiple threads can pose numerous problems, including ensuring that sensitive sections of code can only be accessed by one thread at a time. This video shows how to use some of the OpenMP mechanisms such as critical, atomic, and barrier to keep things working correctly.

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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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