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Full-Text Articles in Physical Sciences and Mathematics
Packet Routing In Networks With Long Wires, Ronald I. Greenberg, Hyeong-Cheol Oh
Packet Routing In Networks With Long Wires, Ronald I. Greenberg, Hyeong-Cheol Oh
Computer Science: Faculty Publications and Other Works
In this paper, we examine the packet routing problem for networks with wires of differing length. We consider this problem in a network independent context, in which routing time is expressed in terms of "congestion" and "dilation" measures for a set of packet paths. We give, for any constant ϵ > 0, a randomized on-line algorithm for routing any set of Npackets in O((C lgϵ(Nd) + D lg(Nd))/lg lg(Nd)) time, where C is the maximum congestion and D is the length of the longest path, both taking wire delays into …
Finding Connected Components On A Scan Line Array Processor, Ronald I. Greenberg
Finding Connected Components On A Scan Line Array Processor, Ronald I. Greenberg
Computer Science: Faculty Publications and Other Works
This paper provides a new approach to labeling the connected components of an n x n image on a scan line array processor (comprised of n processing elements). Variations of this approach yield an algorithm guaranteed to complete in o(n lg n) time as well as algorithms likely to approach O(n) time for all or most images. The best previous solutions require using a more complicated architecture or require Omega(n lg n) time. We also show that on a restricted version of the architecture, any algorithm requires Omega(n lg n) time in the worst case.
Feasible Offset And Optimal Offset For General Single-Layer Channel Routing, Ronald I. Greenberg, Jau-Der Shih
Feasible Offset And Optimal Offset For General Single-Layer Channel Routing, Ronald I. Greenberg, Jau-Der Shih
Computer Science: Faculty Publications and Other Works
This paper provides an efficient method to find all feasible offsets for a given separation in a very large-scale integration (VLSI) channel-routing problem in one layer. The previous literature considers this task only for problems with no single-sided nets. When single-sided nets are included, the worst-case solution time increases from $\Theta ( n )$ to $\Omega ( n^2 )$, where n is the number of nets. But if the number of columns c is $O( n )$, the problem can be solved in time $O( n^{1.5} \lg n )$, which improves upon a “naive” $O( cn )$ approach. As a …