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Machine Learning with Parallel Studio

Parallel Studio can make many difficult tasks much easier, and have them perform better. Specifically, the Math Kernel Library is used to perform regression testing on data sets using five lines of code. As an alternate, regression testing using OpenMP is shown as an additional way to use Parallel Studio …

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IPC Boot Camp: How to Use MPI in Your Programs

Intel’s MPI technology has replaced other interprocess communication techniques with a state-of-the-art API. Rick Leinecker walks you through several code examples that show you how to get up and running very quickly. See everything you need to know to start using MPI in your programs, providing a robust interprocess communication …

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Destroy Data Races with Intel Inspector XE

Multithreading can speed up your programs but introduces a new kind of bug–a data race, where two or more threads try to write to the same variable at the same time. David Bolton shows how to catch data races using Intel Inspector XE 2015 and demonstrates a real bug, then …

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Fast Matrix Multiply Fortran Program Using OpenMP

David Bolton demonstrates how to speed up an intensive Fortran program, making it three times as fast by using OpenMP. First, he runs an unoptimized version that takes about 18 seconds to do a matrix multiplication of two 650 x 650 arrays. Then he runs it optimized in just six …

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Speed Up Image Processing with OpenMP

Image processing can be significantly optimized with the help of OpenMP. Rick Leinecker shows you how, walks you through the OpenMP techniques employed that make the processing faster, and analyzes an iterative OpenMP construct. Since OpenMP applies concurrent processor operations, synchronization is essential to avoid race conditions. In the demonstration …

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How to Make C++ Run Faster with Vectorization and Parallelization

If you want your C++ program to run significantly faster, turn to vectorization and parallelization. David Bolton walks you through these two high-performance techniques and shows you the steps toward speeding up your code.

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Parallelizing Your Code with Advisor XE 2015

Jeff Cogswell takes on the N-Queens problem he introduced in the previous video and shows how the samples that ship with Parallel Studio implement a solution. He then takes this example into Parallel Advisor and tries out a place for parallelism.

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Holding Court with N-Queens Problem

The N-Queens problem is used in many of the Parallel Studio examples. But what exactly is it and how do you approach it in C++ code? Jeff Cogswell introduces this computer science problem and how it works.

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Inside the Different Editions of Parallel Studio

Parallel Studio XE 2015 consists of three different editions that are comprised of several components with different names. Jeff Cogswell guides you through the components and shows you how to decide which edition is right for you.

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Tapping into Random Number Generators in MKL

The Math Kernel Library (MKL) includes a whole set of random number generators that are parallel-friendly and thread-safe. These generators can quickly fill entire arrays with random numbers, even when the arrays contain millions of elements, all with a single function call. Jeff Cogswell puts them to use and looks …

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