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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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Allocate Memory Effectively in TBB

Threading Building Blocks (TBB) includes drop-in replacement functions for the C-type memory allocation functions, as well as replacements for the C++-type allocators. Jeff Cogswell introduces them. When you’re using Threading Building Blocks and writing an app that makes use of the basic memory allocation functions, there’s a feature whereby you …

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Cray Enters New Territory with Chapel Parallel Language

Supercomputer manufacturer Cray is developing a general-purpose, parallel programming language called Chapel that supports Intel architecture. Jeff Cogswell gives you a quick tour. When people think of Cray, they usually think of supercomputers. But something else is coming out of the company: A language for parallel programming that is portable …

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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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