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 language | English |
|---|---|
| Pages (from-to) | 1012-1020 |
| Number of pages | 9 |
| Journal | IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems |
| Volume | 15 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 1996 |
| Externally published | Yes |
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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 journal › Article
}
TY - JOUR
T1 - A neural network model for multilayer topological via minimization in a switchbox
AU - Funabiki, Nobuo
AU - Nishikawa, Seishi
PY - 1996
Y1 - 1996
N2 - 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.
AB - 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.
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U2 - 10.1109/43.511580
DO - 10.1109/43.511580
M3 - Article
VL - 15
SP - 1012
EP - 1020
JO - IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
JF - IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
SN - 0278-0070
IS - 8
ER -