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Take the Guesswork Out of Parallelizing Your Code

It’s a given that faster, more efficient code is the goal of any programmer. And among the ways that you can reduce execution time is to add threading, but first you must know where to put it. If it’s your code then it may be obvious, but in my experience, …

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Updated Intel Tools Tune, Optimize Popular App

The Walker Molecular Dynamics Laboratory at the San Diego Supercomputer Center focuses on computational chemistry, molecular biology and high-performance computing research . The lab’s AMBER molecular dynamics simulation software is used by 20,000 researchers for drug discovery, biocatalysis, enzyme engineering and advanced biomaterial development. Recently, the Walker Laboratory wanted to …

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How Vectorization Can Boost Your C# Code

Vectorization can enhance and speed up your C# program during and after development, but there are some things you need to know before you begin. We will begin with a short explanation of what vectorization is. Then the prerequisites to enable hardware-assisted vectorization are presented since the new JIT compiler …

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How Vectorization Feeds Your Need for Speed

So, you’ve written a program but it’s data-intensive and you need more speed without forking out for a new computer? Maybe you’ve tried alternative algorithms, maxed out concurrency but still need more speed.  Could be it’s time to try vectorization. What is Vectorization? Vectorization is CPU hardware that can speed …

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Fine Tune Performance of Auto-Vectorized Loops

Many programmers take advantage of the automatic vectorization features of Xeon Phi coprocessors. However, as this paper by Andrey Vladimirov of Colfax International shows, taking advantage of some common fine-tuning techniques including strength reduction and data alignment can produce dramatic results. See how Colfax was able to improve coprocessor performance …

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Multicore vs. Vectorized: Programming Techniques Compared

Parallel programming includes two separate technologies multicore and vectorized programming. But what is the difference and how can the two work together? Jeff Cogswell tackles this question. Here at Go Parallel, we’ve talked about two primary ways you can use parallel programming: multicore and vectorized. I’ve received a few emails …

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Solving the N-Body Problem in Parallelism

A common problem in physics and science, the n-body problem requires huge amounts of calculations to solve—making it an excellent application for parallel programming. Jeff Cogswell discusses how a new book that tackles big problems with parallel coding helps solve n-body models as well. If you’re interested in taking your …

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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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Modernizing Software with Vectorization

Intel is working with high-performance computing facilities across the planet to establish Parallel Computing Centers. The goal is modernization. In this blog, Jeff Cogswell looks at what that means in terms of vectorization and multicore development, and considers how we can learn from the work of these centers. Over the …

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New Intel Advanced Vector Extensions 512 Instructions Delivered

The Intel Architecture Instruction Set Extensions Programming Reference now includes the definition of additional Intel Advanced Vector Extensions 512 (Intel AVX-512) instructions. Intel AVX-512 instructions are important because they offer higher performance for the most demanding computational tasks. Intel AVX-512 will first be implemented in the coming Intel Xeon Phi …

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