PLAFST Programmable Logic Array from State Table.

Abstract

Programmable Logic Array From State Table (PLAFST) is a computer aided design tool that takes a symbolic state table as input and produces a very large scale integrated (VLSI) circuit implementation of the symbolic state table. The state table is first reduced symbolically using equivalence partitioning. A near optimal binary state assignment is made based on the Story, Harrison, and Reinhard procedure as modified by Noe and Ryhne. Distinct state assignment variables are sorted based on cost estimates obtained by increasing the number of adjacencies in the state transition table. Once sorted, the actual costs of valid state assignments made from the state variables are calculated. Since state assignments with the lowest cost estimates are investigated first, and optimal solution is found with a small number of iterations. This binary state assignment is demonstratably less costly than either simple or gray code assignments of the state variables. The VLSI circuit consists of a programmable logic array and clocked buffers. The state buffers are properly interconnected. The final outputs are Chip Layout Language and Caltech Intermediate Format descriptions of the integrated circuit. PLAFST also plots the final integrated circuit. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1983
Accession Number
ADA138466

Entities

People

  • D. C. Pelan

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Buffers
  • Circuits
  • Computer Programming
  • Computer Programs
  • Computer-Aided Design
  • Computers
  • Cost Estimates
  • Debugging
  • Electrical Engineering
  • Engineering
  • Gray (Color)
  • Integrated Circuits
  • Language
  • Operating Systems
  • Shell Scripts
  • Transitions
  • Very Large Scale Integration

Readers

  • Integrated Circuit Design and Technology.
  • International Relations and European Studies
  • Regression Analysis.