324 research outputs found

    Obstacle-Avoiding Rectilinear Steiner Minimal Tree Construction

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    Obstacle-avoiding rectilinear Steiner minimal tree (OARSMT) construction is becoming one of the most sought after problems in modern design flow. In this thesis we present an algorithm to route a multi-terminal net in the presence of obstacles. Ours is a top down approach which includes partitioning the initial solution into subproblems and using obstacle aware version of Fast Lookup Table based Wirelength Estimation (OA-FLUTE) at a lower level to generate an OAST followed by recombining them with some backend refinement. To construct an initial connectivity graph we use a novel obstacle-avoiding spanning graph (OASG) algorithm which is a generalization of Zhou\u27s spanning graph algorithm without obstacle presented in ASPDAC 2001. The runtime complexity of our algorithm is O(n log n)

    Routing for analog chip designs at NXP Semiconductors

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    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

    NN-Steiner: A Mixed Neural-algorithmic Approach for the Rectilinear Steiner Minimum Tree Problem

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    Recent years have witnessed rapid advances in the use of neural networks to solve combinatorial optimization problems. Nevertheless, designing the "right" neural model that can effectively handle a given optimization problem can be challenging, and often there is no theoretical understanding or justification of the resulting neural model. In this paper, we focus on the rectilinear Steiner minimum tree (RSMT) problem, which is of critical importance in IC layout design and as a result has attracted numerous heuristic approaches in the VLSI literature. Our contributions are two-fold. On the methodology front, we propose NN-Steiner, which is a novel mixed neural-algorithmic framework for computing RSMTs that leverages the celebrated PTAS algorithmic framework of Arora to solve this problem (and other geometric optimization problems). Our NN-Steiner replaces key algorithmic components within Arora's PTAS by suitable neural components. In particular, NN-Steiner only needs four neural network (NN) components that are called repeatedly within an algorithmic framework. Crucially, each of the four NN components is only of bounded size independent of input size, and thus easy to train. Furthermore, as the NN component is learning a generic algorithmic step, once learned, the resulting mixed neural-algorithmic framework generalizes to much larger instances not seen in training. Our NN-Steiner, to our best knowledge, is the first neural architecture of bounded size that has capacity to approximately solve RSMT (and variants). On the empirical front, we show how NN-Steiner can be implemented and demonstrate the effectiveness of our resulting approach, especially in terms of generalization, by comparing with state-of-the-art methods (both neural and non-neural based).Comment: This paper is the complete version with appendix of the paper accepted in AAAI'24 with the same titl

    Multi-objective optimal design of obstacle-avoiding two-dimensional Steiner trees with application to ascent assembly engineering.

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    We present an effective optimization strategy that is capable of discovering high-quality cost-optimal solution for two-dimensional (2D) path network layouts (i.e., groups of obstacle-avoiding Euclidean Steiner trees) that, among other applications, can serve as templates for complete ascent assembly structures (CAA-structures). The main innovative aspect of our approach is that our aim is not restricted to simply synthesizing optimal assembly designs with regard to a given goal, but we also strive to discover the best trade-offs between geometric and domain-dependent optimal designs. As such, the proposed approach is centred on a variably constrained multi-objective formulation of the optimal design task and on an efficient co-evolutionary solver. The results we obtained on both artificial problems and realistic design scenarios based on an industrial test case empirically support the value of our contribution to the fields of optimal obstacle-avoiding path generation in particular and design automation in general

    Optimal Flood Control

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    A mathematical model for optimal control of the water levels in a chain of reservoirs is studied. Some remarks regarding sensitivity with respect to the time horizon, terminal cost and forecast of inflow are made

    On the construction of rectilinear Steiner minimum trees among obstacles.

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    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
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