An Extension of Workload Capacity Space for Systems With More Than Two Channels

Abstract

We provide the n-channel extension of the unified workload capacity space bounds for standard parallel processing models with minimumtime, maximum-time, and single-target self-terminating stopping rules. This extension enables powerful generalizations of this approach to multiple stopping rules and any number of channels of interest. Mapping the bounds onto the unified capacity space enables a single plot to be used to compare the capacity coefficient values to the upper and lower bounds on standard parallel processing in order to make direct inferences about extreme workload capacity.

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Document Details

Document Type
Technical Report
Publication Date
Apr 05, 2015
Accession Number
ADA624787

Entities

People

  • Joseph W. Houpt
  • Leslie M. Blaha

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Autism
  • Channel Models
  • Coefficients
  • Distribution Functions
  • Inequalities
  • Information Processing
  • Military Research
  • Notation
  • Parallel Computing
  • Parallel Processing
  • Psychology
  • Standards
  • United States
  • Workload

Fields of Study

  • Computer science

Readers

  • Parallel and Distributed Computing.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Space
  • Space - Space Objects