Associative Networks on a Massively Parallel Computer.

Abstract

A generalization of semantic networks, called an associative network is mapped onto a massively parallel processor which is currently under development. The results show: - The time required to process a query is dependent strictly on the pattern of the query, not on the size of the classes being processed. - The order of processing a query does not affect the speed. - Although we do not receive anywhere near an n-fold speedup by using n processors, we still receive significant performance benefits over a single processor. - The associative network may be used not just as a semantic network, for example, it also allows some problems involving numerical minimizations to be solved efficiently. The primary result of this work is that a large number of simple processors, each responsible for a small piece of information, can work in unison to answer queries significantly faster than a single, highly complex processor can.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1985
Accession Number
ADA162234

Entities

People

  • Gary Jackoway

Organizations

  • Duke University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Automobiles
  • Birds
  • Computations
  • Computer Science
  • Computers
  • Databases
  • Language
  • Natural Languages
  • New York
  • Parallel Computing
  • Parallel Processing
  • Parallel Processors
  • Simulators
  • Standards
  • United States
  • Very Large Scale Integration

Fields of Study

  • Computer science

Readers

  • Calculus or Mathematical Analysis
  • Database Systems and Applications
  • Neural Network Machine Learning.