This book presents new concepts, techniques and promising programming models for designing software for chips with "many" (hundreds to thousands) processor cores. Given the scale of parallelism inherent to these chips, software designers face new challenges in terms of operating systems, middleware and applications. This will serve as an invaluable, single-source reference to the state-of-the-art in programming many-core chips. Coverage includes many-core architectures, operating systems, middleware, and programming models.

Multithreading is a requirement for good performance of systems with multi-core chips. This book explains how to maximize the benefits of these processors through a portable C++ library that works on Windows, Linux, Macintosh, and Unix systems, and explains the key tasks in multithreading and how to accomplish them with TBB.

Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing. This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers. - New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more - Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism - Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing

The paradigm shift towards many-core parallelism is accompanied by two fundamental questions: how should the many processors on a single die communicate to each other and what are suitable programming models for these novel architectures? In this thesis, the author tackles both questions by reviewing the reconfigurable mesh model of massively parallel computation for many-cores. The book presents the design, implementation and evaluation of a many-core architecture that is based on the execution principles and communication infrastructure of the reconfigurable mesh. This work fundamentally rests on FPGA implementations and shows that reconfigurable mesh processors with hundreds of autonomous cores are feasible. Several case studies demonstrate the effectiveness of programming and illustrate why the reconfigurable mesh is a promising model for many-cores.

Computing has moved away from a focus on performance-centric serial computation, instead towards energy-efficient parallel computation. This provides continued performance increases without increasing clock frequencies, and overcomes the thermal and power limitations of the dark-silicon era. As the number of parallel cores increases, we transition into the many-core computing era. There is considerable interest in developing methods, tools, architectures and applications to support many-core computing.

This book constitutes the thoroughly refereed post-workshop proceedings of the Third International Workshop on OpenMP, IWOMP 2007, held in Beijing, China, in June 2007. The 14 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 28 submissions. The papers address all topics related to OpenMP, such as OpenMP performance analysis and modeling, OpenMP performance and correctness tools and proposed OpenMP extensions, as well as applications in various domains, e.g., scientific computation, video games, computer graphics, multimedia, information retrieval, optimization, text processing, data mining, finance, signal and image processing, and numerical solvers.