Parallel Processing and Parallel Algorithms

Theory and Computation

  • Seyed H. Roosta

Table of contents

  1. Front Matter
    Pages i-xix
  2. Seyed H. Roosta
    Pages 1-56
  3. Seyed H. Roosta
    Pages 57-108
  4. Seyed H. Roosta
    Pages 109-136
  5. Seyed H. Roosta
    Pages 137-216
  6. Seyed H. Roosta
    Pages 217-258
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    Pages 259-318
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    Pages 319-353
  9. Seyed H. Roosta
    Pages 355-410
  10. Seyed H. Roosta
    Pages 411-437
  11. Seyed H. Roosta
    Pages 439-476
  12. Seyed H. Roosta
    Pages 477-499
  13. Seyed H. Roosta
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  14. Back Matter
    Pages 535-566

About this book


Motivation It is now possible to build powerful single-processor and multiprocessor systems and use them efficiently for data processing, which has seen an explosive ex­ pansion in many areas of computer science and engineering. One approach to meeting the performance requirements of the applications has been to utilize the most powerful single-processor system that is available. When such a system does not provide the performance requirements, pipelined and parallel process­ ing structures can be employed. The concept of parallel processing is a depar­ ture from sequential processing. In sequential computation one processor is in­ volved and performs one operation at a time. On the other hand, in parallel computation several processors cooperate to solve a problem, which reduces computing time because several operations can be carried out simultaneously. Using several processors that work together on a given computation illustrates a new paradigm in computer problem solving which is completely different from sequential processing. From the practical point of view, this provides sufficient justification to investigate the concept of parallel processing and related issues, such as parallel algorithms. Parallel processing involves utilizing several factors, such as parallel architectures, parallel algorithms, parallel programming lan­ guages and performance analysis, which are strongly interrelated. In general, four steps are involved in performing a computational problem in parallel. The first step is to understand the nature of computations in the specific application domain.


Algorithms Modula Occam Sage algorithm artificial intelligence concurrent programming functional programming linear optimization neural network parallel programming programming programming language

Authors and affiliations

  • Seyed H. Roosta
    • 1
  1. 1.Department of Computer ScienceState University of New YorkOswegoUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag New York, Inc. 2000
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4612-7048-5
  • Online ISBN 978-1-4612-1220-1
  • Buy this book on publisher's site