A neural network model for multilayer topological via minimization in a switchbox

Nobuo Funabiki, Seishi Nishikawa

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

This paper presents a new approach using a neural network model for the multilayer topological via minimization problem in a switchbox. Our algorithm consists of three steps: 1) dividing multiterminal nets into two-terminal nets, 2) finding a layer-assignment of the twoterminal nets by a neural network model so as to minimize the number of unassigned nets, and 3) embedding one via for each imassigned net by Marek-Sadowska's algorithm. The neural network model is composed of N x M processing elements to assign N two-terminal nets in an M -layer switchbox. The performante of our algorithm is verified by 15 benchmark problems where it can find optimum or near-optimum solutions. In the two-layer Burstein's switchbox, our algorithm finds a 15-via solution while the best known solution requires 20 vias.

Original languageEnglish
Pages (from-to)1012-1020
Number of pages9
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Volume15
Issue number8
DOIs
Publication statusPublished - 1996
Externally publishedYes

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Electric switchgear
Multilayers
Neural networks
Processing

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Hardware and Architecture
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

A neural network model for multilayer topological via minimization in a switchbox. / Funabiki, Nobuo; Nishikawa, Seishi.

In: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Vol. 15, No. 8, 1996, p. 1012-1020.

Research output: Contribution to journalArticle

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