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

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2 Author(s)
Funabikiy, N. ; Dept. of Inf. & Comput. Sci., Osaka Univ., Japan ; Nishikawa, S.

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 two-terminal nets by a neural network model so as to minimize the number of unassigned nets, and 3) embedding one via for each unassigned net by Marek-Sadowska's algorithm. The neural network model is composed of N×M processing elements to assign N two-terminal nets in an M-layer switchbox. The performance 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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Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on  (Volume:15 ,  Issue: 8 )