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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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Unleashing Powerful Monte Carlo Parallel Methods

The Monte Carlo methods are used in scientific and engineering applications for modeling sophisticated systems. Although they can be complex, there are some easy examples that demonstrate their power. In this video, Jeff Cogswell looks at one such example.

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Installing and Running Intel Software Development Emulator

The Intel Software Development Emulator lets you test out code for instruction sets that aren’t available on your own processor. Jeff Cogswell shows you how to install and get started with it.

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Army of Parallel Programming Experts Shares Tricks of the Trade

In this video, author and Intel parallel computing evangelist James Reinders discusses his latest book, “High Performance Parallelism Pearls: Multicore and Many-core Programming Approaches,” an instructional volume packed with learnings from 69 contributing authors in 28 chapters that are structured to show you how to get the most performance from …

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Putting Every Core to Work: Using Graphics Power for General Purpose Computing

Graphics engines aren’t just for graphics anymore. In this video, Intel Technical Consulting Engineer Anoop Madhusoodhanan Prabha discusses a new use for that graphics power, namely boosting your general purpose computing horsepower. Watch this video to see how you can use the newest compiler features to channel the capabilities of …

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Explicit Vectorization Explained

Vectorizing your code improves performance, which can also save power. The faster an application can compute CPU-intensive regions, the faster the CPU can be set to a lower power state. With resources at a premium, being able to improve performance while saving on energy costs is very attractive indeed. In …

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Barriers in OpenMP: To Use or Not to Use?

Just because barriers are easy to use in OpenMP doesn’t mean you should always turn to them. Jeff Cogswell shows why and when they make sense and when you want to go with an alternative. He also walks you through how to turn them off when they’re not necessary.

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