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Title: A model for an intelligent operating system for executing image understanding tasks on a reconfigurable parallel architecture

Abstract

Parallel processing is one approach to achieving the large computational processing capabilities required by many real-time computing tasks. One of the problems that must be addressed in the use of reconfigurable multiprocessor systems is matching the architecture configuration to the algorithms to be executed. This paper presents a conceptual model that explores the potential of artificial intelligence tools, specifically expert systems, to design an Intelligent Operating System for multiprocessor systems. The target task is the implementation of image understanding systems on multiprocessor architectures. PASM is used as an example multiprocessor. The Intelligent Operating System concepts developed here could also be used to address other problems requiring real-time processing. An example image understanding task is presented to illustrate the concept of intelligent scheduling by the Intelligent Operating System. Also considered is the use of the conceptual model when developing an image understanding system in order to test different strategies for choosing algorithms, imposing execution, order constraints, and integrating results from various algorithms.

Authors:
 [1]; ; ; ;  [2];  [3]
  1. University of Southwestern Louisiana, Lafayette, LA (USA)
  2. Purdue Univ., Lafayette, IN (USA). School of Electrical Engineering
  3. Texas Univ., Austin, TX (USA). Graduate School of Business
Publication Date:
OSTI Identifier:
5347749
Resource Type:
Journal Article
Journal Name:
Journal of Parallel and Distributed Computing; (USA)
Additional Journal Information:
Journal Volume: 6:3; Journal ID: ISSN 0743-7315
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; ARRAY PROCESSORS; PARALLEL PROCESSING; COMPUTER ARCHITECTURE; ARTIFICIAL INTELLIGENCE; ALGORITHMS; CONSTRAINTS; EXPERT SYSTEMS; IMAGE PROCESSING; REAL TIME SYSTEMS; MATHEMATICAL LOGIC; PROCESSING; PROGRAMMING; 990200* - Mathematics & Computers

Citation Formats

Chu, C H, Delp, E J, Jamieson, L H, Siegel, H J, Weil, F J, and Whinston, A B. A model for an intelligent operating system for executing image understanding tasks on a reconfigurable parallel architecture. United States: N. p., 1989. Web.
Chu, C H, Delp, E J, Jamieson, L H, Siegel, H J, Weil, F J, & Whinston, A B. A model for an intelligent operating system for executing image understanding tasks on a reconfigurable parallel architecture. United States.
Chu, C H, Delp, E J, Jamieson, L H, Siegel, H J, Weil, F J, and Whinston, A B. 1989. "A model for an intelligent operating system for executing image understanding tasks on a reconfigurable parallel architecture". United States.
@article{osti_5347749,
title = {A model for an intelligent operating system for executing image understanding tasks on a reconfigurable parallel architecture},
author = {Chu, C H and Delp, E J and Jamieson, L H and Siegel, H J and Weil, F J and Whinston, A B},
abstractNote = {Parallel processing is one approach to achieving the large computational processing capabilities required by many real-time computing tasks. One of the problems that must be addressed in the use of reconfigurable multiprocessor systems is matching the architecture configuration to the algorithms to be executed. This paper presents a conceptual model that explores the potential of artificial intelligence tools, specifically expert systems, to design an Intelligent Operating System for multiprocessor systems. The target task is the implementation of image understanding systems on multiprocessor architectures. PASM is used as an example multiprocessor. The Intelligent Operating System concepts developed here could also be used to address other problems requiring real-time processing. An example image understanding task is presented to illustrate the concept of intelligent scheduling by the Intelligent Operating System. Also considered is the use of the conceptual model when developing an image understanding system in order to test different strategies for choosing algorithms, imposing execution, order constraints, and integrating results from various algorithms.},
doi = {},
url = {https://www.osti.gov/biblio/5347749}, journal = {Journal of Parallel and Distributed Computing; (USA)},
issn = {0743-7315},
number = ,
volume = 6:3,
place = {United States},
year = {Thu Jun 01 00:00:00 EDT 1989},
month = {Thu Jun 01 00:00:00 EDT 1989}
}