Structured Parallel Programming offers the simplest way for developers to learn patterns for high-performance parallel programming. Written by parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders, this book explains how to design and implement maintainable and efficient parallel algorithms using a composable, structured, scalable, and machine-independent approach to parallel computing. It presents both theory and practice, and provides detailed concrete examples using multiple programming models. The examples in this book are presented using two of the most popular and cutting edge programming models for parallel programming: Threading Building Blocks, and Cilk Plus. These architecture-independent models enable easy integration into existing applications, preserve investments in existing code, and speed the development of parallel applications. Examples from realistic contexts illustrate patterns and themes in parallel algorithm design that are widely applicable regardless of implementation technology. Software developers, computer programmers, and software architects will find this book extremely helpful. The patterns-based approach offers structure and insight that developers can apply to a variety of parallel programming models Develops a composable, structured, scalable, and machine-independent approach to parallel computing Includes detailed examples in both Cilk Plus and the latest Threading Building Blocks, which support a wide variety of computers
Bisseling explains how to use the bulk synchronous parallel (BSP) model and the freely available BSPlib communication library in parallel algorithm design and parallel programming.
The emphasis lies on parallel programming techniques needed for different architectures. For this second edition, all chapters have been carefully revised.
This book offers an overview of some of the most prominent parallel programming models used in high-performance computing and supercomputing systems today.
hood: coprocessor. specifications. We want to get on the road right away, but like most with a new car, we will at least take a quick glance under the hood at our “engine.” Similar to other Intel processing products, like the Intels ...
Mathematics of Computing -- Parallelism.
[FJL+88] G.Fox, M.Johnson, G.Lyzenga, S.Otto, J.Salmon, and D.Walker. Solving Problems on Concurrent Processors, Volume I: General Techniques and Regular Problems. Prentice Hall, 1988. [FK03] IanFoster and CarlKesselman.
Takes a tutorial approach, starting with small programming examples and building progressively to more challenging examples Explains how to develop parallel programs using MPI, Pthreads and OpenMP programming models A robust package of ...
In: Proceedings of the fourth SIAM conference on parallel processing for scientific computing. SIAM, Philadelphia, pp 237-244 Cote SI (1991) Solving partial differential equations on a MIMD hypercube: fast Poisson solvers and the ...
Optimize code for multi-core processors with Intel Parallel Studio XE Serving as a stand-alone, teach-yourself tutorial, this book walks you through the steps for adding parallel programming to your skill set.
Each chapter in this edited work includes detailed explanations of the programming techniques used, while showing high performance results on both Intel Xeon Phi coprocessors and multicore processors.