An Enhanced Genetic Solution for Scheduling, Module Allocation, and Binding in VLSI Design

  • Authors:
  • Gary William Grewal;Thomas Charles Wilson

  • Affiliations:
  • -;-

  • Venue:
  • VLSID '97 Proceedings of the Tenth International Conference on VLSI Design: VLSI in Multimedia Applications
  • Year:
  • 1997

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Abstract

This paper presents a novel approach to the high-level synthesis problems of scheduling, module allocation, and module binding for behavioral descriptions. A very general version of this problem is considered where modules may perform different numbers of operations in different numbers of control steps. These inherently interdependent problems are solved using an Enhanced Genetic Algorithm (EGA) which is both more robust and more efficient than the simple GA.