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The Best of the First Half

The most popular articles on Dr. Dobb's for the first half of the year, sprinkled with editors' choices of particularly meritorious pieces. Enjoy!

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Will Parallel Code Ever Be Embraced?

The advent of the many-core era is not going to push developers to write more parallel code. That hasn't happened as we've gone from 1- to 2- to 4- to 8-core processors, has it? Writing parallel code...

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Improving Futures and Callbacks in C++ To Avoid Synching by Waiting

In C++, futures are a great way of decomposing a program into concurrent parts, but a poor way of composing those parts into a responsive and scalable program. Microsoft's Parallel Pattern Library...

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Parallel Evolution, Not Revolution

Not all parallel programming is fine-grained. But it's still parallel.

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The OpenACC Execution Model

In this second part of the introduction to OpenACC — the OpenMP-style library for GPU programming — the execution model is explained and samples are benchmarked against straight, OpenMP parallelism.

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What's New in .NET Framework 4.5

From arrays that can now exceed 2 GB to enhanced background garbage collection, changes in this release of .NET provide immediately useful capabilities.

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Parallel In-Place Merge

Merging sorted arrays in parallel and in place can be done very efficiently, using this algorithm. Comparisons with the performance of similar STL functions are included.

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Creating and Using Libraries with OpenACC

How to write reusable methods (libraries, subroutines, and functions) that can transparently call optimized CPU and GPU libraries using OpenACC pragmas.

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AMD's Bold ARM Server Gambit

By combining 64-bit ARM processors with server-side technology, the company that led the x86 architecture into the 64-bit world is hoping to reinvent the data center and give itself new life.

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Cache-Friendly Code: Solving Manycore's Need for Faster Data Access

As the number of cores in multicore chips grows — Intel is poised to release the 50+ core Xeon Phi — ensuring that program data can be delivered fast enough to be consumed by so many processors is a...

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Intel's 50-Core Xeon Phi: The New Era of Inexpensive Supercomputing

The advent of Intel's massively parallel coprocessor will make every server a supercomputer.

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Scaling Up And Out

Most attention today is focused on adding nodes or cloud instances to scale out systems. Guest editor Nikita Shamgunov emphasizes the importance of scaling systems vertically as well.

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Introduction to CUDA C/C++

Nvidia's Mark Ebersole introduces core concepts of heterogeneous computing concepts with CUDA C/C++ in this 30 minute tutorial.

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Heterogeneous Programming

AMD's Ben Sander shares details about the heterogeneous system architecture (HSA) and how it will change the way people program in the future.

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Programming Intel's Xeon Phi: A Jumpstart Introduction

Reaching one teraflop on Intel's new 60-core coprocessor requires a little know-how

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Introduction to OpenCL [video]

Ben Gaster from AMD Research talks about the design and use of the language OpenCL, which has been embraced by Apple, Intel, and Nvidia among other companies, to accelerate programs.

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CUDA vs. Phi: Phi Programming for CUDA Developers

Both CUDA and Phi coprocessors provide high degrees of parallelism that can deliver excellent application performance. For the most part, CUDA programmers with existing application code have already...

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The Best of 2012

The most popular articles of the past 12 months from Dr. Dobb's, plus some additional pieces chosen for your thoughtful consideration by our staff.

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Introduction to OpenACC [video]

Using OpenACC to write your first hybrid application

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Comparing OpenCL, CUDA, and OpenACC [video]

Rob Farber takes you on a tour of the paths to massively parallel x86, MultiGPU, and CPU+GPU applications.

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