What Is Parallel Programming
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Parallel Programming
Author: Mikhail S. Tarkov
language: en
Publisher: Nova Science Publishers
Release Date: 2014-01-11
Parallel programming is designed for the use of parallel computer systems for solving time-consuming problems that cannot be solved on a sequential computer in a reasonable time. These problems can be divided into two classes: 1. Processing large data arrays (including processing images and signals in real time); 2. Simulation of complex physical processes and chemical reactions For each of these classes, prospective methods are designed for solving problems. For data processing, one of the most promising technologies is the use of artificial neural networks. Particles-in-cell method and cellular automata are very useful for simulation. Problems of scalability of parallel algorithms and the transfer of existing parallel programs to future parallel computers are very acute now. An important task is to optimise the use of the equipment (including the CPU cache) of parallel computers. Along with parallelising information processing, it is essential to ensure the processing reliability by the relevant organisation of systems of concurrent interacting processes. From the perspective of creating qualitative parallel programs, it is important to develop advanced methods of learning parallel programming. The above reasons are the basis for the creation of this book, chapters of which are devoted to solving these problems. We hope this book will be of interest to researchers, students and all those working in the field of parallel programming and high performance computing.
An Introduction to Parallel Programming
An Introduction to Parallel Programming, Second Edition presents a tried-and-true tutorial approach that shows students how to develop effective parallel programs with MPI, Pthreads and OpenMP.As the first undergraduate text to directly address compiling and running parallel programs on multi-core and cluster architecture, this second edition carries forward its clear explanations for designing, debugging and evaluating the performance of distributed and shared-memory programs while adding coverage of accelerators via new content on GPU programming and heterogeneous programming. New and improved user-friendly exercises teach students how to compile, run and modify example programs. - 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 online ancillaries for instructors and students includes lecture slides, solutions manual, downloadable source code, and an image bank New to this edition: - New chapters on GPU programming and heterogeneous programming - New examples and exercises related to parallel algorithms
Parallel Programming
Parallel Programming: Concepts and Practice provides an upper level introduction to parallel programming. In addition to covering general parallelism concepts, this text teaches practical programming skills for both shared memory and distributed memory architectures. The authors' open-source system for automated code evaluation provides easy access to parallel computing resources, making the book particularly suitable for classroom settings. - Covers parallel programming approaches for single computer nodes and HPC clusters: OpenMP, multithreading, SIMD vectorization, MPI, UPC++ - Contains numerous practical parallel programming exercises - Includes access to an automated code evaluation tool that enables students the opportunity to program in a web browser and receive immediate feedback on the result validity of their program - Features an example-based teaching of concept to enhance learning outcomes