The CAOS System.

Abstract

The CAOS system is a framework designed to facilitate the development of highly concurrent real-time signal interpretation applications. It explores the potential of multiprocessor architectures to improve the performance of expert systems in the domain of signal interpretation. CAOS is implemented in LISP on a (simulated) collection of processor-memory sites, linked by a high- speed communications subsystem. The virtual machine on which it depends provides remote evaluation and packet-based message exchange between processes, using virtual circuits known as streams. To this presentation layer, CAOS adds (1) a flexible process scheduler, and (2) an object-centered notion of agents, dynamically-instantiable entities which model interpreted signal features. This report documents the principal ideas, programming model, and implementation of CAOS. A model of real-time signal interpretation, based on replicated abstraction pipelines, is presented. For some applications, this model offers a means by large numbers of processors may be utilized without introducing synchronization-necessitated software bottlenecks. The report concludes with a description of the performance of a large CAOS application over various sizes of multiprocessor configurations. Lessons about problem decomposition grain size, global problem solving control strategy, and appropriate services provided to CAOS by the underlying architecture are discussed. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1986
Accession Number
ADA174178

Entities

People

  • Eric Schoen

Organizations

  • Stanford University

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Application Software
  • Classification
  • Clocks
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Data Rate
  • Expert Systems
  • Hash Tables
  • Instrumentation
  • Lisp Programming Language
  • Operating Systems
  • Scheduling (Production)
  • Simulations
  • Simulators

Fields of Study

  • Computer science
  • Engineering

Readers

  • Military Logistics and Supply Chain Management
  • Parallel and Distributed Computing.
  • Systems Analysis and Design