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Rectilinear Steiner minimal tree (RSMT) problem finds a minimum length tree that interconnects a given set of points by only horizontal and vertical line segments and by using extra points if necessary. In this paper, to speedup the RSMT construction, two recently developed successful heuristic algorithms, namely rectilinear steiner tree (RST) by Zhou and batched greedy algorithm (BGA) by Kahng et al., have been used as the basis. Following a slight modification on RST, which led to a nonrecursive and a considerably faster version, a partially parallelized and distributed form of this modified algorithm is proposed. Computational tests using large random data sets have shown the advantage of the modification on RST, and tests conducted on a cluster of workstations have proven the proposed distributed approach to be very promising particularly for large problem instances. [ABSTRACT FROM AUTHOR]

Given a set of pins and a set of obstacles on routing layers, a multilayer obstacle-avoiding rectilinear Steiner minimal tree (ML-OARSMT) connects these pins by rectilinear edges within layers and vias between layers and avoids running through any obstacle to construct a Steiner tree with a minimal total cost. The ML-OARSMT problem is very important for many very large scale integration designs with pins being located in multiple routing layers that contain numerous routing obstacles incurred from IP blocks, power networks, prerouted nets, etc. As a fundamental problem with extensive practical applications to routing and wirelength/congestion/timing estimations in early design stages, it is desired to develop an effective algorithm for the ML-OARSMT problem to facilitate the design flow. However, there is no existing work on this ML-OARSMT problem. In this paper, we first formulate the ML-OARSMT problem with rectangular obstacles and then identify key different properties of this problem from its single-layer counterpart. Based on the multilayer obstacle-avoiding spanning graph, we present the first algorithm to solve the ML-OARSMT problem. Our algorithm can guarantee an optimal solution for any two-pin net and many multiple-pin nets. Experiments show that our algorithm results in 33% smaller total costs on average than a construction-by-correction heuristic which is widely used for Steiner-tree construction in the recent literature. [ABSTRACT FROM AUTHOR]

Given a set of pins and a set of obstacles on a plane, an obstacle-avoiding rectilinear Steiner minimal tree (OARSMT) connects these pins, possibly through some additional points (called the Steiner points), and avoids running through any obstacle to construct a tree with a minimal total wirelength. The OARSMT problem becomes more important than ever for modern nanometer IC designs which need to consider numerous routing obstacles incurred from power networks, prerouted nets, IP blocks, feature patterns for manufacturability improvement, antenna jumpers for reliability enhancement, etc. Consequently, the OARSMT problem has received dramatically increasing attention recently. Nevertheless, considering obstacles significantly increases the problem complexity, and thus, most previous works suffer from either poor quality or expensive running time. Based on the obstacle-avoiding spanning graph, this paper presents an efficient algorithm with some theoretical optimality guarantees for the OARSMT construction. Unlike previous heuristics, our algorithm guarantees to find an optimal OARSMT for any two-pin net and many higher pin nets. Extensive experiments show that our algorithm results in significantly shorter wirelengths than all state-of-the-art works. [ABSTRACT FROM AUTHOR]