Emerging Trends in Database and Knowledge Based Machines: The Application of Parallel Architectures to 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.
Table of Contents
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).
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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