Routing for analog chip designs at NXP Semiconductors

During the study week 2011 we worked on the question of how to automate certain aspects of the design of analog chips. Here we focused on the task of connecting different blocks with electrical wiring, which is particularly tedious to do by hand. For digital chips there is a wealth of research available for this, as in this situation the amount of blocks makes it hopeless to do the design by hand. Hence, we set our task to finding solutions that are based on the previous research, as well as being tailored to the specific setting given by NXP. This resulted in an heuristic approach, which we presented at the end of the week in the form of a protoype tool. In this report we give a detailed account of the ideas we used, and describe possibilities to extend the approach

Two-Level Rectilinear Steiner Trees

Given a set $P$ of terminals in the plane and a partition of $P$ into $k$ subsets $P_1, ..., P_k$, a two-level rectilinear Steiner tree consists of a rectilinear Steiner tree $T_i$ connecting the terminals in each set $P_i$ ($i=1,...,k$) and a top-level tree $T_{top}$ connecting the trees $T_1, ..., T_k$. The goal is to minimize the total length of all trees. This problem arises naturally in the design of low-power physical implementations of parity functions on a computer chip. For bounded $k$ we present a polynomial time approximation scheme (PTAS) that is based on Arora's PTAS for rectilinear Steiner trees after lifting each partition into an extra dimension. For the general case we propose an algorithm that predetermines a connection point for each $T_i$ and $T_{top}$ ($i=1,...,k$). Then, we apply any approximation algorithm for minimum rectilinear Steiner trees in the plane to compute each $T_i$ and $T_{top}$ independently. This gives us a $2.37$-factor approximation with a running time of $\mathcal{O}(|P|\log|P|)$ suitable for fast practical computations. The approximation factor reduces to $1.63$ by applying Arora's approximation scheme in the plane

Spanning trees short or small

We study the problem of finding small trees. Classical network design problems are considered with the additional constraint that only a specified number $k$ of nodes are required to be connected in the solution. A prototypical example is the $k$MST problem in which we require a tree of minimum weight spanning at least $k$ nodes in an edge-weighted graph. We show that the $k$MST problem is NP-hard even for points in the Euclidean plane. We provide approximation algorithms with performance ratio $2\sqrt{k}$ for the general edge-weighted case and $O(k^{1/4})$ for the case of points in the plane. Polynomial-time exact solutions are also presented for the class of decomposable graphs which includes trees, series-parallel graphs, and bounded bandwidth graphs, and for points on the boundary of a convex region in the Euclidean plane. We also investigate the problem of finding short trees, and more generally, that of finding networks with minimum diameter. A simple technique is used to provide a polynomial-time solution for finding $k$-trees of minimum diameter. We identify easy and hard problems arising in finding short networks using a framework due to T. C. Hu.Comment: 27 page

On the construction of rectilinear Steiner minimum trees among obstacles.

Rectilinear Steiner minimum tree (RSMT) problem asks for a shortest tree spanning a set of given terminals using only horizontal and vertical lines. Construction of RSMTs is an important problem in VLSI physical design. It is useful for both the detailed and global routing steps, and it is important for congestion, wire length and timing estimations during the floorplanning or placement step. The original RSMT problem assumes no obstacle in the routing region. However, in today’s designs, there can be many routing blockages, like macro cells, IP blocks and pre-routed nets. Therefore, the RSMT problem with blockages has become an important problem in practice and has received a lot of research attentions in the recent years. The RSMT problem has been shown to be NP-complete, and the introduction of obstacles has made this problem even more complicated.In the first part of this thesis, we propose an exact algorithm, called ObSteiner, for the construction of obstacle-avoiding RSMT (OARSMT) in the presence of complex rectilinear obstacles. Our work is developed based on the GeoSteiner approach in which full Steiner trees (FSTs) are first constructed and then combined into a RSMT. We modify and extend the algorithm to allow rectilinear obstacles in the routing region. We prove that by adding virtual terminals to each routing obstacle, the FSTs in the presence of obstacles will follow some very simple structures. A two-phase approach is then developed for the construction of OARSMTs. In the first phase, we generate a set of FSTs. In the second phase, the FSTs generated in the first phase are used to construct an OARSMT. Experimental results show that ObSteiner is able to handle problems with hundreds of terminals in the presence of up to two thousand obstacles, generating an optimal solution in a reasonable amount of time.In the second part of this thesis, we propose the OARSMT problem with slew constraints over obstacles. In modern VLSI designs, obstacles usually block a fraction of metal layers only making it possible to route over the obstacles. However, since buffers cannot be place on top of any obstacle, we should avoid routing long wires over obstacles. Therefore, we impose the slew constraints for the interconnects that are routed over obstacles. To deal with this problem, we analyze the optimal solutions and prove that the internal trees with signal direction over an obstacle will follow some simple structures. Based on this observation, we propose an exact algorithm, called ObSteiner with slew constraints, that is able to find an optimal solution in the extended Hanan grid. Experimental results show that the proposed algorithm is able to reduce nearly 5% routing resources on average in comparison with the OARSMT algorithm and is also very much faster.Huang, Tao.Thesis (Ph.D.)--Chinese University of Hong Kong, 2013.Includes bibliographical references (leaves [137]-144).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- The rectilinear Steiner minimum tree problem --- p.1Chapter 1.2 --- Applications --- p.3Chapter 1.3 --- Obstacle consideration --- p.5Chapter 1.4 --- Thesis outline --- p.6Chapter 1.5 --- Thesis contributions --- p.8Chapter 2 --- Background --- p.11Chapter 2.1 --- RSMT algorithms --- p.11Chapter 2.1.1 --- Heuristics --- p.11Chapter 2.1.2 --- Exact algorithms --- p.20Chapter 2.2 --- OARSMT algorithms --- p.30Chapter 2.2.1 --- Heuristics --- p.30Chapter 2.2.2 --- Exact algorithms --- p.33Chapter 3 --- ObSteiner - an exact OARSMT algorithm --- p.37Chapter 3.1 --- Introduction --- p.38Chapter 3.2 --- Preliminaries --- p.39Chapter 3.2.1 --- OARSMT problem formulation --- p.39Chapter 3.2.2 --- An exact RSMT algorithm --- p.40Chapter 3.3 --- OARSMT decomposition --- p.42Chapter 3.3.1 --- Full Steiner trees among complex obstacles --- p.42Chapter 3.3.2 --- More Theoretical results --- p.59Chapter 3.4 --- OARSMT construction --- p.62Chapter 3.4.1 --- FST generation --- p.62Chapter 3.4.2 --- Pruning of FSTs --- p.66Chapter 3.4.3 --- FST concatenation --- p.71Chapter 3.5 --- Incremental construction --- p.82Chapter 3.6 --- Experiments --- p.83Chapter 4 --- ObSteiner with slew constraints --- p.97Chapter 4.1 --- Introduction --- p.97Chapter 4.2 --- Problem Formulation --- p.100Chapter 4.3 --- Overview of our approach --- p.103Chapter 4.4 --- Internal tree structures in an optimal solution --- p.103Chapter 4.5 --- Algorithm --- p.126Chapter 4.5.1 --- EFST and SCIFST generation --- p.127Chapter 4.5.2 --- Concatenation --- p.129Chapter 4.5.3 --- Incremental construction --- p.131Chapter 4.6 --- Experiments --- p.131Chapter 5 --- Conclusion --- p.135Bibliography --- p.13