Patterns for Parallel Programming

The Parallel Programming Guide for Every Software DeveloperFrom grids and clusters to next-generation game consoles, parallel computing is going mainstream. Innovations such as Hyper-Threading Technology, HyperTransport Technology, and multicore microprocessors from IBM, Intel, and Sun are accelerating the movement's growth. Only one thing is missing: programmers with the skills to meet the soaring demand for parallel software. That's where Patterns for Parallel Programming comes in. It's the first parallel programming guide written specifically to serve working software developers, not just computer scientists. The authors introduce a complete, highly accessible pattern language that will help any experienced developer "think parallel"-and start writing effective parallel code almost immediately. Instead of formal theory, they deliver proven solutions to the challenges faced by parallel programmers, and pragmatic guidance for using today's parallel APIs in the real world. Coverage includes: Understanding the parallel computing landscape and the challenges faced by parallel developersFinding the concurrency in a software design problem and decomposing it into concurrent tasksManaging the use of data across tasksCreating an algorithm structure that effectively exploits the concurrency you've identifiedConnecting your algorithmic structures to the APIs needed to implement themSpecific software constructs for implementing parallel programsWorking with today's leading parallel programming environments: OpenMP, MPI, and JavaPatterns have helped thousands of programmers master object-oriented development and other complex programming technologies. With this book, you will learn that they're the best way to master parallel programming too.

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Parallel Scientific Computing in C++ and MPI

This book provides a seamless approach to numerical algorithms, modern programming techniques and parallel computing. These concepts and tools are usually taught serially across different courses and different textbooks, thus observing the connection between them. The necessity of integrating these subjects usually comes after such courses are concluded (e.g., during a first job or a thesis project), thus forcing the student to synthesize what is perceived to be three independent subfields into one in order to produce a solution. The book includes both basic and advanced topics and places equal emphasis on the discretization of partial differential equations and on solvers. Advanced topics include wavelets, high-order methods, non-symmetric systems and parallelization of sparse systems. A CD-ROM accompanies the text.

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An Introduction to Parallel Programming

User-friendly teaching practice studentshow to compile, run and modify the sample program. Main features: Take a tutorial approach, beginning with examples of programming a small and progressive development of more challenging examples Focus on designing, debugging and evaluating program performance distributed shared-memory and Describes how to develop parallel programs using MPI, pthreads, OpenMP programming model.

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Parallel Programming

In just a few years, many standard software products will be based on the concept of parallel programming is implemented in hardware, and various applications will be far more extensive than scientific computing, until now the main application area for parallel computing. Rauber and RR takes the latest developments in processor architecture by providing a detailed description of parallel programming techniques needed to develop efficient programs for multicore processors as well as for parallel cluster systems and supercomputers. their book is organized into three main sections, covering all areas of parallel computing: a parallel system architecture, parallel programming models and environments, and efficient implementation of the algorithm application. The emphasis lies in parallel programming techniques needed for a different architecture. The main purpose of this book is to present a parallel programming techniques that can be used in many situations to the many applications that allow readers to develop programs that correct and efficient parallel. 

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Parallel Programming in OpenMP

Aimed at researchers who work or scientific C / C + + or Fortran programmers, Parallel Programming in OpenMP two standards describe what and how to use them to create software that takes full advantage of parallel computing. At its core, OpenMP is very simple. Techniques explored include how to tweak the default direction paralleled to a certain situation, how to use the parallel region (beyond simple loop), and the dos and don'ts of effective synchronization (with critical sections and barriers). The book is completed with some advice very good for how to work with the current system cache mechanism OpenMP-compliant. Overall, Parallel Programming in OpenMP introduce appropriate research programmer for a new vocabulary of idioms and techniques for parallelizing software using OpenMP -. Richard Dragan Topics covered: Overview of OpenMP programming standard for shared-memory multiprocessors Description OpenMP directives for Fortran OpenMP parallel hardware and pragmas for C / C + + Parallelizing simple do-loop parallel / parallel to the direction of shared and private scoping for variable reduction surgery thread data dependence and how to remove them OpenMP performance problems (work fairly, balancing the load in the loop, the scheduling option) Parallel mode area parallelize arbitrary blocks of code (master and slave threads, and paragraph copyin threadprivate direction) parallel work queue task number Divide by sharing thread Restrictions on work-sharing Noniterative Orphaning work Nested parallel regions in OpenMP parallelism control, including controlling the number of threads, dynamic threads, and OpenMP library calls for synchronization of data OpenMP threads Avoiding Critical race landing part (nested critical sections and atomic directive name and OpenMP Runtime library lock routines Event synchronization (barrier landing and part ordered) Custom synchronization, including the directive flush Programming tips for the performance of synchronization problems with the Act load balancing's Amdahl OpenMP for manual code parallelized to write code paralleled that matches the processor cache Avoiding false synchronization instructions Performance sharing problem for bus-based and Non-Uniform Memory Access (NUMA) machine quick reference OpenMP.

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Parallel Programming in C with MPI and OpenMP

The era of practical parallel programming has arrived, marked by the popularity of the MPI and OpenMP software standards and the emergence of commodity clusters as the hardware platform of choice for an increasing number of organizations. This exciting new book, "Parallel Programming in C with MPI and OpenMP" addresses the needs of students and professionals who want to learn how to design, analyze, implement, and benchmark parallel programs in C using MPI and/or OpenMP. It introduces a rock-solid design methodology with coverage of the most important MPI functions and OpenMP directives. It also demonstrates, through a wide range of examples, how to develop parallel programs that will execute efficiently on today's parallel platforms. 

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Using OpenMP

Kuck, Intel Software, Fellow and Solutions Group, and Director, Parallel and Distributed Solutions, Intel Corporation OpenMP, a portable programming interface for shared memory parallel computers, has been adopted as an informal standard in 1997 by computer scientists who want a single model on which the program to the shared memory system. Using OpenMP offers a comprehensive introduction to parallel programming concepts and detailed overview of OpenMP. Using OpenMP discusses hardware developments, describes where OpenMP applicable, and compares OpenMP to other programming interfaces parallel and distributed shared memory architecture. Finally, Using OpenMP considers trends likely to influence OpenMP development, offering a glimpse of the possibility of a future OpenMP 3.0 from the viewpoint of the current OpenMP 2.5. With multicore computer use increasing, the need for a comprehensive introduction and overview of the standard interface that clearly provides. Using OpenMP important reference not only for students both at undergraduate and postgraduate level, but also for professionals who intend to parallelize existing codes or develop The new parallel programs for shared memory computer architecture. 

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Examples from book : http://openmp.org/examples/Using-OpenMP-Examples-Distr.zip

Parallel and Distributed Programming Using C++

Many companies and government agencies have large investments in applications developed using C++ language. This book helps software developers and programmers who need to add the technique of parallel and distributed programming to existing applications. parallel programming using multiple computers, or computers with multiple internal processors, to solve problems with greater computational speed than using a single computer.

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