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  • Textbook
  • © 2010

Parallel Programming

for Multicore and Cluster Systems

  • Broad coverage of all aspects of parallel programming

  • Special emphasis on runtime efficiency and memory organization

  • Presented material has been used in courses for many years

  • Complemented by many examples and an additional website with teaching material

  • Includes supplementary material: sn.pub/extras

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-x
  2. Introduction

    • Thomas Rauber, Gudula Rünger
    Pages 1-6
  3. Parallel Computer Architecture

    • Thomas Rauber, Gudula Rünger
    Pages 7-91
  4. Parallel Programming Models

    • Thomas Rauber, Gudula Rünger
    Pages 93-149
  5. Performance Analysis of Parallel Programs

    • Thomas Rauber, Gudula Rünger
    Pages 151-196
  6. Message-Passing Programming

    • Thomas Rauber, Gudula Rünger
    Pages 197-256
  7. Thread Programming

    • Thomas Rauber, Gudula Rünger
    Pages 257-357
  8. Algorithms for Systems of Linear Equations

    • Thomas Rauber, Gudula Rünger
    Pages 359-440
  9. Back Matter

    Pages 441-455

About this book

Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing.

Rauber and Rünger take up these recent developments in processor architecture by giving detailed descriptions of parallel programming techniques that are necessary for developing efficient programs for multicore processors as well as for parallel cluster systems and supercomputers. Their book is structured in three main parts, covering all areas of parallel computing: the architecture of parallel systems, parallel programming models and environments, and the implementation of efficient application algorithms. The emphasis lies on parallel programming techniques needed for different architectures.

The main goal of the book is to present parallel programming techniques that can be used in many situations for many application areas and which enable the reader to develop correct and efficient parallel programs. Many examples and exercises are provided to show how to apply the techniques. The book can be used as both a textbook for students and a reference book for professionals. The presented material has been used for courses in parallel programming at different universities for many years.

Reviews

"[...] The end-ofchapter exercises are stimulating, there are adequate references for further study, and the index, though short, is quite helpful. [...] This book introduces the basics of parallel programming on multicore and cluster systems. Adequate sample programs illustrate the key concepts of parallel programming. [...]" ACM Computing Reviews, S. V. Nagaraj, February 2011

Authors and Affiliations

  • LS für Angewandte Informatik II, Universität Bayreuth, Bayreuth, Germany

    Thomas Rauber

  • Fak. Informatik, TU Chemnitz, Chemnitz, Germany

    Gudula Rünger

About the authors

Thomas Rauber has been professor for parallel and distributed systems at the University of Bayreuth since 2002. His research is focusing on algorithms and systems for distributed and parallel programming, on which he published more than 80 papers in journals or conference proceedings.

Gudula Rünger has been professor at the Chemnitz University of Technology since 2000. Her main research interests are parallel and distributed programming both in theory and applications, and she published more than 80 conference and journal papers on these topics.

Bibliographic Information

Buy it now

Buying options

eBook USD 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Other ways to access