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Full-Text Articles in Physical Sciences and Mathematics

On The Difficulty Of Manhattan Channel Routing, Ronald I. Greenberg, Joseph Jaja, Sridhar Krishnamurthy Dec 1992

On The Difficulty Of Manhattan Channel Routing, Ronald I. Greenberg, Joseph Jaja, Sridhar Krishnamurthy

Computer Science: Faculty Publications and Other Works

We show that channel routing in the Manhattan model remains difficult even when all nets are single-sided. Given a set of n single-sided nets, we consider the problem of determining the minimum number of tracks required to obtain a dogleg-free routing. In addition to showing that the decision version of the problem isNP-complete, we show that there are problems requiring at least d+Omega(sqrt(n)) tracks, where d is the density. This existential lower bound does not follow from any of the known lower bounds in the literature.


Minimum Separation For Single-Layer Channel Routing, Ronald I. Greenberg, F. Miller Maley Sep 1992

Minimum Separation For Single-Layer Channel Routing, Ronald I. Greenberg, F. Miller Maley

Computer Science: Faculty Publications and Other Works

We present a linear-time algorithm for determining the minimum height of a single-layer routing channel. The algorithm handles single-sided connections and multiterminal nets. It yields a simple routability test for single-layer switchboxes, correcting an error in the literature.


Finding A Maximum-Density Planar Subset Of A Set Of Nets In A Channel, Ronald I. Greenberg, Jau-Der Shih Feb 1992

Finding A Maximum-Density Planar Subset Of A Set Of Nets In A Channel, Ronald I. Greenberg, Jau-Der Shih

Computer Science: Faculty Publications and Other Works

We present efficient algorithms to find a maximum-density planar subset of n 2-pin nets in a channel. The simplest approach is to make repeated usage of Supowit's dynamic programming algorithm for finding a maximum-size planar subset, which leads to O(n^3) time to find a maximum-density planar subset. But we also provide an algorithm whose running time is dependent on other problem parameters and is often more efficient. A simple bound on the running time of this algorithm is O(nlgn+n(t+1)w), where t is the number of two-sided nets, and w is the number of nets in the output. Though the worst-case …