Thirty-Five Point Rectilinear Steiner Minimal Trees in a Day

Given a set of terminals in the plane, a rectilinear Steiner minimal tree is a shortest interconnection among these terminals using only horizontal and vertical edges. We present an algorithm that constructs a rectilinear Steiner minimal tree for any input terminal set. On a workstation, problems involving 20 input terminals can be solved in a few seconds, and problems involving 30 input terminals can be solved, on average, in 30 minutes. Previous algorithms could only solve 16 or 17 point problems within the 30 minute time bound. Problems involving 35 points can be solved, on average, within a day. Our experiments were run on uniformly distributed data on an integer grid. 1 Introduction Let V be a set of n terminals in the plane. A rectilinear Steiner minimal tree for V is a tree of shortest length containing V as its vertex set, where the distance between two vertices is measured in the rectilinear metric. Rectilinear Steiner minimal trees are useful in VLSI physical design, particu..

Obstacle-avoiding rectilinear Steiner tree.

Li, Liang.Thesis (M.Phil.)--Chinese University of Hong Kong, 2009.Includes bibliographical references (leaves 57-61).Abstract also in Chinese.Abstract --- p.iAcknowledgement --- p.ivChapter 1 --- Introduction --- p.1Chapter 1.1 --- Background --- p.1Chapter 1.1.1 --- Partitioning --- p.1Chapter 1.1.2 --- Floorplanning and Placement --- p.2Chapter 1.1.3 --- Routing --- p.2Chapter 1.1.4 --- Compaction --- p.3Chapter 1.2 --- Motivations --- p.3Chapter 1.3 --- Problem Formulation --- p.4Chapter 1.3.1 --- Properties of OARSMT --- p.4Chapter 1.4 --- Progress on the Problem --- p.4Chapter 1.5 --- Contributions --- p.5Chapter 1.6 --- Thesis Organization --- p.6Chapter 2 --- Literature Review on OARSMT --- p.8Chapter 2.1 --- Introduction --- p.8Chapter 2.2 --- Previous Methods --- p.9Chapter 2.2.1 --- OARSMT --- p.9Chapter 2.2.2 --- Shortest Path Problem with Blockages --- p.13Chapter 2.2.3 --- OARSMT with Delay Minimization --- p.14Chapter 2.2.4 --- OARSMT with Worst Negative Slack Maximization --- p.14Chapter 2.3 --- Comparison --- p.15Chapter 3 --- Heuristic Method --- p.17Chapter 3.1 --- Introduction --- p.17Chapter 3.2 --- Our Approach --- p.18Chapter 3.2.1 --- Handling of Multi-pin Nets --- p.18Chapter 3.2.2 --- Propagation --- p.20Chapter 3.2.3 --- Backtrack --- p.23Chapter 3.2.4 --- Finding MST --- p.26Chapter 3.2.5 --- Local Refinement Scheme --- p.26Chapter 3.3 --- Experimental Results --- p.28Chapter 3.4 --- Summary --- p.28Chapter 4 --- Exact Method --- p.32Chapter 4.1 --- Introduction --- p.32Chapter 4.2 --- Review on GeoSteiner --- p.33Chapter 4.3 --- Overview of our Approach --- p.33Chapter 4.4 --- FST with Virtual Pins --- p.34Chapter 4.4.1 --- Definition of FST --- p.34Chapter 4.4.2 --- Notations --- p.36Chapter 4.4.3 --- Properties of FST with Virtual Pins --- p.36Chapter 4.5 --- Generation of FST with Virtual Pins --- p.46Chapter 4.5.1 --- Generation of FST with Two Pins --- p.46Chapter 4.5.2 --- Generation of FST with 3 or More Pins --- p.48Chapter 4.6 --- Concatenation of FSTs with Virtual Pins --- p.50Chapter 4.7 --- Experimental Results --- p.52Chapter 4.8 --- Summary --- p.53Chapter 5 --- Conclusion --- p.55Bibliography --- p.6