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An Introduction To Parallel Programming

Author: Peter Pacheco
Publisher: Elsevier
ISBN: 9780080921440
Size: 21.43 MB
Format: PDF, ePub, Mobi
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An Introduction to Parallel Programming is the first undergraduate text to directly address compiling and running parallel programs on the new multi-core and cluster architecture. It explains how to design, debug, and evaluate the performance of distributed and shared-memory programs. The author Peter Pacheco uses a tutorial approach to show students how to develop effective parallel programs with MPI, Pthreads, and OpenMP, starting with small programming examples and building progressively to more challenging ones. The text is written for students in undergraduate parallel programming or parallel computing courses designed for the computer science major or as a service course to other departments; professionals with no background in parallel computing. Takes a tutorial approach, starting with small programming examples and building progressively to more challenging examples Focuses on designing, debugging and evaluating the performance of distributed and shared-memory programs Explains how to develop parallel programs using MPI, Pthreads, and OpenMP programming models

Mpi Eine Einf Hrung

Author: William Gropp
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3486841009
Size: 43.55 MB
Format: PDF, ePub, Docs
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Message Passing Interface (MPI) ist ein Protokoll, das parallel Berechnungen auf verteilten, heterogenen, lose-gekoppelten Computersystemen ermöglicht.

Parallel Programming

Author: T. Bräunl
ISBN: 9780133368277
Size: 67.36 MB
Format: PDF
View: 1920
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This introduction to parallel programming explores the fundamentals of parallelism, parallel system architecture (MIMD and SIMD), and parallel programming languages, and presents methods for designing parallel algorithms, for writing efficient parallel programs, and for computing performance data and judging it.

Introduction To Parallel Computing

Author: Ananth Grama
Publisher: Pearson Education
ISBN: 9780201648652
Size: 15.54 MB
Format: PDF, Kindle
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A complete source of information on almost all aspects of parallel computing from introduction, to architectures, to programming paradigms, to algorithms, to programming standards. It covers traditional Computer Science algorithms, scientific computing algorithms and data intensive algorithms.

An Introduction To Parallel Programming

Author: Scott L. Hamilton
ISBN: 1304761576
Size: 35.36 MB
Format: PDF, Docs
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An introduction to parallel programming with openmpi using C. It is written so that someone with even a basic understanding of programming can begin to write mpi based parallel programs.

Introduction To Parallel Computing A Practical Guide With Examples In C

Author: Wesley Petersen
Publisher: OUP Oxford
ISBN: 9780191513619
Size: 31.42 MB
Format: PDF, ePub, Docs
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In the last few years, courses on parallel computation have been developed and offered in many institutions in the UK, Europe and US as a recognition of the growing significance of this topic in mathematics and computer science. There is a clear need for texts that meet the needs of students and lecturers and this book, based on the author's lecture at ETH Zurich, is an ideal practical student guide to scientific computing on parallel computers working up from a hardware instruction level, to shared memory machines, and finally to distributed memory machines. Aimed at advanced undergraduate and graduate students in applied mathematics, computer science, and engineering, subjects covered include linear algebra, fast Fourier transform, and Monte-Carlo simulations, including examples in C and, in some cases, Fortran. This book is also ideal for practitioners and programmers.

Introduction To Parallel Processing

Author: M. Sasikumar
Publisher: PHI Learning Pvt. Ltd.
ISBN: 8120350316
Size: 65.17 MB
Format: PDF
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Written with a straightforward and student-centred approach, this extensively revised, updated and enlarged edition presents a thorough coverage of the various aspects of parallel processing including parallel processing architectures, programmability issues, data dependency analysis, shared memory programming, thread-based implementation, distributed computing, algorithms, parallel programming languages, debugging, parallelism paradigms, distributed databases as well as distributed operating systems. The book, now in its second edition, not only provides sufficient practical exposure to the programming issues but also enables its readers to make realistic attempts at writing parallel programs using easily available software tools. With all the latest information incorporated and several key pedagogical attributes included, this textbook is an invaluable learning tool for the undergraduate and postgraduate students of computer science and engineering. It also caters to the students pursuing master of computer application. What’s New to the Second Edition • A new chapter named Using Parallelism Effectively has been added covering a case study of parallelising a sorting program, and introducing commonly used parallelism models. • Sections describing the map-reduce model, initiative, Indian efforts in supercomputing, OpenMP system for shared memory programming, etc. have been added. • Numerous sections have been updated with current information. • Several questions have been incorporated in the chapter-end exercises to guide students from examination and practice points of view.

An Introduction To Parallel And Vector Scientific Computation

Author: Ronald W. Shonkwiler
Publisher: Cambridge University Press
ISBN: 113945899X
Size: 35.19 MB
Format: PDF, Mobi
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In this text, students of applied mathematics, science and engineering are introduced to fundamental ways of thinking about the broad context of parallelism. The authors begin by giving the reader a deeper understanding of the issues through a general examination of timing, data dependencies, and communication. These ideas are implemented with respect to shared memory, parallel and vector processing, and distributed memory cluster computing. Threads, OpenMP, and MPI are covered, along with code examples in Fortran, C, and Java. The principles of parallel computation are applied throughout as the authors cover traditional topics in a first course in scientific computing. Building on the fundamentals of floating point representation and numerical error, a thorough treatment of numerical linear algebra and eigenvector/eigenvalue problems is provided. By studying how these algorithms parallelize, the reader is able to explore parallelism inherent in other computations, such as Monte Carlo methods.