Every area of science and engineering today has to process voluminous data sets. Using exact, or even approximate, algorithms to solve intractable problems in critical areas, such as computational biology, takes time that is exponential in some of the underlying parameters. Parallel computing addresses this issue and has become affordable with the

Multicore Processors and Systems provides a comprehensive overview of emerging multicore processors and systems. It covers technology trends affecting multicores, multicore architecture innovations, multicore software innovations, and case studies of state-of-the-art commercial multicore systems. A cross-cutting theme of the book is the challenges associated with scaling up multicore systems to hundreds of cores. The book provides an overview of significant developments in the architectures for multicore processors and systems. It includes chapters on fundamental requirements for multicore systems, including processing, memory systems, and interconnect. It also includes several case studies on commercial multicore systems that have recently been developed and deployed across multiple application domains. The architecture chapters focus on innovative multicore execution models as well as infrastructure for multicores, including memory systems and on-chip interconnections. The case studies examine multicore implementations across different application domains, including general purpose, server, media/broadband, network processing, and signal processing. Multicore Processors and Systems is the first book that focuses solely on multicore processors and systems, and in particular on the unique technology implications, architectures, and implementations. The book has contributing authors that are from both the academic and industrial communities.

An overview of the most prominent contemporary parallel processing programming models, written in a unique tutorial style. With the coming of the parallel computing era, computer scientists have turned their attention to designing programming models that are suited for high-performance parallel computing and supercomputing systems. Programming parallel systems is complicated by the fact that multiple processing units are simultaneously computing and moving data. This book offers an overview of some of the most prominent parallel programming models used in high-performance computing and supercomputing systems today. The chapters describe the programming models in a unique tutorial style rather than using the formal approach taken in the research literature. The aim is to cover a wide range of parallel programming models, enabling the reader to understand what each has to offer. The book begins with a description of the Message Passing Interface (MPI), the most common parallel programming model for distributed memory computing. It goes on to cover one-sided communication models, ranging from low-level runtime libraries (GASNet, OpenSHMEM) to high-level programming models (UPC, GA, Chapel); task-oriented programming models (Charm++, ADLB, Scioto, Swift, CnC) that allow users to describe their computation and data units as tasks so that the runtime system can manage computation and data movement as necessary; and parallel programming models intended for on-node parallelism in the context of multicore architecture or attached accelerators (OpenMP, Cilk Plus, TBB, CUDA, OpenCL). The book will be a valuable resource for graduate students, researchers, and any scientist who works with data sets and large computations. Contributors Timothy Armstrong, Michael G. Burke, Ralph Butler, Bradford L. Chamberlain, Sunita Chandrasekaran, Barbara Chapman, Jeff Daily, James Dinan, Deepak Eachempati, Ian T. Foster, William D. Gropp, Paul Hargrove, Wen-mei Hwu, Nikhil Jain, Laxmikant Kale, David Kirk, Kath Knobe, Ariram Krishnamoorthy, Jeffery A. Kuehn, Alexey Kukanov, Charles E. Leiserson, Jonathan Lifflander, Ewing Lusk, Tim Mattson, Bruce Palmer, Steven C. Pieper, Stephen W. Poole, Arch D. Robison, Frank Schlimbach, Rajeev Thakur, Abhinav Vishnu, Justin M. Wozniak, Michael Wilde, Kathy Yelick, Yili Zheng

The first book on parallel MATLAB and the first parallel computing book focused on quickly producing efficient parallel programs.

The hybrid/heterogeneous nature of future microprocessors and large high-performance computing systems will result in a reliance on two major types of components: multicore/manycore central processing units and special purpose hardware/massively parallel accelerators. While these technologies have numerous benefits, they also pose substantial perfo

This text is an introduction to the complex and emerging world of the Parallel Computing. It helps you understand the principles and acquire the practical skills of MPI programming using the C/FORTAN programming language. Our aim is for you to gain sufficient knowledge and experience to perform simple useful programming tasks using the best up-to-date techniques and so we hope for it to be the easiest book from which you can learn the basics of MPI programming. This text is an introduction to the emerging world of the Parallel Computing. It helps you understand the principles, algorithm & implementation of Parallel Computing. Our aim is for you to gain sufficient knowledge and experience with Parallel Computing using the best up-to-date techniques. We have tried for it to be the easiest book from which you can learn the Parallel Computing. We chose the topics for this book to cover what is needed to get started with Parallel Computing, not just what is easy to teach and learn. On the other hand, we wont waste your time with material of marginal practical importance. If an idea is explained here, its because youll almost certainly need it. This book is emphatically focused on the concept. Understanding the fundamental ideas, principles, and techniques is the essence of a good programmer. Only well-designed code has a chance of becoming part of a correct, reliable, and maintainable parallel system. Through this book, we hope that you will see the absolute necessity of understanding Parallel Computing.