A Neural Network Approach to Topological Via-Minimization Problems

Nobuo Funabiki; Yoshiyasu Takefuji

doi:10.1109/43.229751

A Neural Network Approach to Topological Via-Minimization Problems

Nobuo Funabiki, Yoshiyasu Takefuji

Research output: Contribution to journal › Article › peer-review

12 Citations (Scopus)

Abstract

Toooloeical via-minimization (TVM) algorithms in two-layer channels based on the artificial neural network model are presented in this paper. TVM problems require not only assigning wires or nets between terminals without an intersection to one of two layers, but also a minimization of the number of vias, which are the single contacts of nets between two layers. The goal of our algorithms is to embed the maximum number of nets without an intersection. Two types of TVM problems are examined: split rectangular TVM (RTVM) problems and split circular TVM (CTVM) problems. Our algorithms require 3n processing elements for the n-net split RTVM problems, and 5n processing elements for the n-net split CTVM problems. The algorithms were verified by solving seven problems with 20 to 80 nets. The algorithms can be easily extended for more-than-two-layer problems.

Original language	English
Pages (from-to)	770-779
Number of pages	10
Journal	IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Volume	12
Issue number	6
DOIs	https://doi.org/10.1109/43.229751
Publication status	Published - 1993 Jun
Externally published	Yes

ASJC Scopus subject areas

Software
Computer Graphics and Computer-Aided Design
Electrical and Electronic Engineering

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abstract = "Toooloeical via-minimization (TVM) algorithms in two-layer channels based on the artificial neural network model are presented in this paper. TVM problems require not only assigning wires or nets between terminals without an intersection to one of two layers, but also a minimization of the number of vias, which are the single contacts of nets between two layers. The goal of our algorithms is to embed the maximum number of nets without an intersection. Two types of TVM problems are examined: split rectangular TVM (RTVM) problems and split circular TVM (CTVM) problems. Our algorithms require 3n processing elements for the n-net split RTVM problems, and 5n processing elements for the n-net split CTVM problems. The algorithms were verified by solving seven problems with 20 to 80 nets. The algorithms can be easily extended for more-than-two-layer problems.",

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A Neural Network Approach to Topological Via-Minimization Problems

Abstract

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