Publication Date
5-1996
Abstract
An important stage in circuit design is placement, where components are assigned to physical locations on a chip. A popular contemporary approach for placement is the use of simulated annealing. While this approach has been shown to produce good placement solutions, recent work in genetic algorithms has produced promising results. The purpose of this study is to determine which approach will result in better placement solutions.
A simplified model of the placement problem, circuit partitioning, was tested on three circuits with both a genetic algorithm and a simulated annealing algorithm. When compared with simulated annealing, the genetic algorithm was found to produce similar results for one circuit, and better results for the other two circuits. Based on these results, genetic algorithms may also yield better results than simulated annealing when applied to the placement problem.
Document Type
Technical Report
Keywords
Genetic algorithm, simulated annealing, partitioning, chip design, placement
Disciplines
Digital Circuits | Electrical and Electronics | Hardware Systems | VLSI and Circuits, Embedded and Hardware Systems
Extent
16 pages
Format
Language
English
Recommended Citation
Manikas, Theodore W. and Cain, James T., "Genetic Algorithms vs. Simulated Annealing: A Comparison of Approaches for Solving the Circuit Partitioning Problem" (1996). Computer Science and Engineering Research. 1.
https://scholar.smu.edu/engineering_compsci_research/1
Included in
Digital Circuits Commons, Electrical and Electronics Commons, Hardware Systems Commons, VLSI and Circuits, Embedded and Hardware Systems Commons
