Emerging Trends in Database and Knowledge Based Machines: The Application of Parallel Architectures to Smart Information Systems / Edition 1

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Overview

This book illustrates important ways in which new parallel hardware is being used to improve the speed and usefulness of a variety of information systems. It contains thirteen original papers that survey the latest trends in performance enhancing architectures for smart information systems.

The machines featured in the text have been designed to support information systems ranging from relational databases to semantic networks and other artificial intelligence paradigms. In addition, many of the projects illustrated in the book contain generic architectural ideas that support higher-level requirements by using semantics-free hardware designs.

The case studies describe add-on machines and performance-enhancing units that employ parallel hardware to speed up database operations. Other case studies show how high-performance computers support database and related software, even though some platforms were originally designed for scientific or numeric applications. The last three chapters give examples of machines that are deliberately designed to speed up a particular knowledge representation formalism or a particular AI problem solving paradigm. The information presented throughout this book will help all those engaged in the design or use of high-performance architectures for nonnumeric (i.e., symbolic) applications.

Illustrating interesting ways in which new parallel hardware is being used to improve performance and increase functionality for a variety of information systems, this book, containing 13 original papers, surveys the latest trends in performance enhancing architectures for smart information systems. It will appeal to anyone engaged in the design or use of high-performance architectures for non-numeric applications.

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Editorial Reviews

Booknews
Illustrates some of the ways new parallel computer hardware is being used to improve the performance and increase the functionality for a variety of information systems such as relational databases, semantic networks, and other artificial intelligence paradigms. The 13 original papers survey the latest trends and contain generic architecture ideas that support higher-level requirements and are based on semantics-free hardware designs. For designers or users of high-performance architecture for non-numeric applications. No index. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780818665523
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 4/13/1995
  • Series: Practitioners Series , #54
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 312
  • Product dimensions: 7.32 (w) x 10.20 (h) x 0.90 (d)

Table of Contents

1. Introduction: Parallel Database and Knowledge-Base Systems (M. Abdelguerfi & S. Lavington).

DATABASE MACHINES.

2. IDIOMS: A Multitransputer Database Machine (J. Kerridge).

3. From DBC to MDBS—A Progression in Database Machine Research (D. Hsiao & W. Wang).

4. Rinda: A Relational Database Processor for Large Databases (T. Satoh & U. Inoue).

5. A Paginated Set-Associate Architecture for Databases (P. Faudemay).

6. Parallel Multi-Wavefront Algorithms for Pattern-Based Processing of Object-Oriented Databases (S. Su, et al.).

7. The Datacycle Architecture: A Database Broadcast System (T. Bowen, et al.).

USING MASSIVELY-PARALLEL GENERAL COMPUTING PLATFORMS FOR DBMS.

8. Industrial Database Supercomputer Exegesis: The DBC/1012, The NCR 3700, The Ynet, and The Bynet (F. Cariño, et al.).

9. A Massively Parallel Indexing Engine Using DAP (N. Bond & S. Reddaway).

KNOWLEDGE-BASE MACHINES.

10. The IFS/2: Add-on Support for Knowledge-Base Systems (S. Lavington).

11. EDS: An Advanced Parallel Database Server (L. Borrmann, et al.).

12. A Parallel and Distributed Environment for Database Rule Processing: Open Problems and Future Directions (S. Stolfo, et al.).

ARTIFICIAL INTELLIGENCE MACHINES.

13. IXM2: A Parallel Associative Processor for Knowledge Processing (T. Higuchi).

14. An Overview of the Knowledge Crunching Machine (J Noyé).

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