A Maze Routing-Based Methodology With Bounded Exploration and Path-Assessed Retracing for Constrained Multilayer Obstacle-Avoiding Rectilinear Steiner Tree Construction

Abstract

Owing to existing intellectual properties, prerouted nets, and power/ground wires, the routing of a system on chip design demands to detour around multilayer obstacles. Traditional approaches for the multilayer obstacle-avoiding rectilinear Steiner tree (ML-OARST) problem are thus nonmaze routing-based approaches for runtime issues, yet they cannot be directly applied to deal with additional constraints such as variant edge weights on a routing layer. In this article, we propose the maze routing-based methodology with bounded exploration and path-assessed retracing to reduce runtime and routing cost for the constrained ML-OARST construction problem. The exploration of maze routing is bounded to reduce the runtime; the costs of connecting pins are computed to select Steiner points in the retracing phase. To further reduce the routing cost, we develop a Steiner point-based ripping-up and rebuilding scheme for altering tree topology. Experimental results on industrial and randomly generated benchmarks demonstrate that the proposed methodology can provide a solution with good quality in terms of routing cost and has a significant speedup compared to traditional maze routing. A commercial tool is also used to show the effectiveness of the proposed methodology.