Parallel Computing in Science and Engineering

4th International DFVLR Seminar on Foundations of Engineering Sciences Bonn, Federal Republic of Germany, June 25/26, 1987

  • Editors
  • Rüdiger Dierstein
  • Dieter Müller-Wichards
  • Hans-Martin Wacker

Part of the Lecture Notes in Computer Science book series (LNCS, volume 295)

Table of contents

  1. Front Matter
  2. Hans-Martin Wacker
    Pages 1-11
  3. Howard Jay Siegel, William Tsun-yuk Hsu, Menkae Jeng, Wayne G. Nation
    Pages 35-60
  4. Arvind, Robert A. Iannucci
    Pages 61-88
  5. David Callahan, Keith D. Cooper, Robert T. Hood, Ken Kennedy, Linda M. Torczon, Scott K. Warren
    Pages 89-106
  6. Constantine D. Polychronopoulos
    Pages 107-130
  7. Garry Rodrigue, A. Louise Perkins
    Pages 131-143
  8. Karl Solchenbach, Ulrich Trottenberg
    Pages 145-158
  9. Dieter Müller-Wichards
    Pages 159-185

About these proceedings

Introduction

It was the aim of the conference to present issues in parallel computing to a community of potential engineering/scientific users. An overview of the state-of-the-art in several important research areas is given by leading scientists in their field. The classification question is taken up at various points, ranging from parametric characterizations, communication structure, and memory distribution to control and execution schemes. Central issues in multiprocessing hardware and operation, such as scalability, techniques of overcoming memory latency and synchronization overhead, as well as fault tolerance of communication networks are discussed. The problem of designing and debugging parallel programs in a user-friendly environment is addressed and a number of program transformations for enhancing vectorization and parallelization in a variety of program situations are described. Two different algorithmic techniques for the solution of certain classes of partial differential equations are discussed. The properties of domain-decomposition algorithms and their mapping onto a CRAY-XMP-type architecture are investigated and an overview is given of the merit of various approaches to exploiting the acceleration potential of multigrid methods. Finally, an abstract performance modeling technique for the behavior of applications on parallel and vector architectures is described.

Keywords

Debugging Potential Scala Transformation algorithm algorithms communication modeling parallel programming programming

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-18923-8
  • Copyright Information Springer-Verlag 1988
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-18923-7
  • Online ISBN 978-3-540-38848-7
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book
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