Parallel Processing and Parallel Algorithms

1. Front Matter

   Pages i-xix

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2. Computer Architecture

   • Seyed H. Roosta

   Pages 1-56

3. Components of Parallel Computers

   • Seyed H. Roosta

   Pages 57-108

4. Principles of Parallel Programming

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   Pages 109-136

5. Parallel Programming Approaches

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   Pages 137-216

6. Principles of Parallel Algorithm Design

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   Pages 217-258

7. Parallel Graph Algorithms

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   Pages 259-318

8. Parallel Search Algorithms

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   Pages 319-353

9. Parallel Computational Algorithms

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   Pages 355-410

10. Data Flow and Functional Programming

    • Seyed H. Roosta

    Pages 411-437

11. Asynchronous Parallel Programming

    • Seyed H. Roosta

    Pages 439-476

12. Data Parallel Programming

    • Seyed H. Roosta

    Pages 477-499

13. Artificial Intelligence and Parallel Processing

    • Seyed H. Roosta

    Pages 501-534

14. Back Matter

    Pages 535-566

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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
• algorithm analysis and problem complexity

• Department of Computer Science, State University of New York, Oswego, USA

  Seyed H. Roosta

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