Design Issues in Parallel Architectures for Artificial Intelligence.

Abstract

Development of highly intelligent computers requires a conceptual foundation that will overcome the limitations of the von Neumann architecture. Architectures for such a foundation should meet the following design goals: Address the fundamental organizational issues of large-scale parallelism and sharing in a fully integrated way. This means attention to organizational principles, as well as hardware and software. Serve as an experimental apparatus for testing large-scale artificial intelligence systems. Explore the feasibility of an architecture based on abstractions, which serve as natural computational primitives for parallel processing. Such abstractions should be logically independent of their software and hardware host implementations. In this paper we lay out some of the fundamental design issues in parallel architecture for Artificial Intelligence, delineate limitations of previous parallel architectures, and outline a new approach that we are pursuing. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1983
Accession Number
ADA142482

Entities

People

  • C. Hewitt
  • H. Lieberman

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Boundaries
  • Computations
  • Computer Languages
  • Computer Programming
  • Computers
  • Department Of Defense
  • Information Processing
  • Information Systems
  • Instruction Set Architecture
  • Language
  • Massachusetts
  • Military Research
  • Parallel Computing
  • Parallel Processing
  • Programming Languages
  • Simulators

Fields of Study

  • Computer science
  • Engineering

Readers

  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy