33 research outputs found

    Via Minimization in VLSI Chip Design - Application of a Planar Max-Cut Algorithm

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    The design of very large scale integrated (VLSI) chips is an exciting area of applied discrete mathematics.Due to the intractability of the majority of the problems, and also due to the huge instance sizes, the design process is decomposed into various sub-problems. In this paper, for a given detailed routing solution, we revisit the assignment of layers to net segments. For connected metalized nets, a layer change is accomplished by a vertical interconnection area (via). We seek to minimize the use of these vias as vias not only reduce the electrical reliability and performance of the chip, but also decrease the manufacturing yield substantially. In the general case, the via minimization problem is NP-hard. However, it is known that the two layer via minimization problem can be solved as a maximum cut problem on a planar graph which is a polynomial task.The focus of this paper is to use this approach for modern real-world chips. From the roughly two dozen wiring layers present, we take two adjacent ones for the via minimization. As a core-routine, we use a fast maximum cut algorithm on planar graphs. For being able to use the solutions in practice, we integrate practically relevant design rule constraints at the expense of potentially using further vias. Thus, our solution satisfies the additional constraints present in actual current designs. The computational results show that our implementation is fast on real-world instances as it usually computes a solution within a few minutes CPU time only. Moreover, often a considerable amount of vias can be saved

    Via Minimization in VLSI Chip Design - Application of a Planar Max-Cut Algorithm

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    The design of very large scale integrated (VLSI) chips is an exciting area of applied discrete mathematics.Due to the intractability of the majority of the problems, and also due to the huge instance sizes, the design process is decomposed into various sub-problems. In this paper, for a given detailed routing solution, we revisit the assignment of layers to net segments. For connected metalized nets, a layer change is accomplished by a vertical interconnection area (via). We seek to minimize the use of these vias as vias not only reduce the electrical reliability and performance of the chip, but also decrease the manufacturing yield substantially. In the general case, the via minimization problem is NP-hard. However, it is known that the two layer via minimization problem can be solved as a maximum cut problem on a planar graph which is a polynomial task.The focus of this paper is to use this approach for modern real-world chips. From the roughly two dozen wiring layers present, we take two adjacent ones for the via minimization. As a core-routine, we use a fast maximum cut algorithm on planar graphs. For being able to use the solutions in practice, we integrate practically relevant design rule constraints at the expense of potentially using further vias. Thus, our solution satisfies the additional constraints present in actual current designs. The computational results show that our implementation is fast on real-world instances as it usually computes a solution within a few minutes CPU time only. Moreover, often a considerable amount of vias can be saved

    An efficient approach to multilayer layer assignment with an application to via minimization

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    Intelligent approaches to VLSI routing

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    Very Large Scale Integrated-circuit (VLSI) routing involves many large-size and complex problems and most of them have been shown to be NP-hard or NP-complete. As a result, conventional approaches, which have been successfully used to handle relatively small-size routing problems, are not suitable to be used in tackling large-size routing problems because they lead to \u27combinatorial explosion\u27 in search space. Hence, there is a need for exploring more efficient routing approaches to be incorporated into today\u27s VLSI routing system. This thesis strives to use intelligent approaches, including symbolic intelligence and computational intelligence, to solve three VLSI routing problems: Three-Dimensional (3-D) Shortest Path Connection, Switchbox Routing and Constrained Via Minimization. The 3-D shortest path connection is a fundamental problem in VLSI routing. It aims to connect two terminals of a net that are distributed in a 3-D routing space subject to technological constraints and performance requirements. Aiming at increasing computation speed and decreasing storage space requirements, we present a new A* algorithm for the 3-D shortest path connection problem in this thesis. This new A*algorithm uses an economical representation and adopts a novel back- trace technique. It is shown that this algorithm can guarantee to find a path if one exists and the path found is the shortest one. In addition, its computation speed is fast, especially when routed nets are spare. The computational complexities of this A* algorithm at the best case and the worst case are O(Æ–) and 0(Æ–3), respectively, where Æ– is the shortest path length between the two terminals. Most importantly, this A\u27 algorithm is superior to other shortest path connection algorithms as it is economical in terms of storage space requirement, i.e., 1 bit/grid. The switchbox routing problem aims to connect terminals at regular intervals on the four sides of a rectangle routing region. From a computational point of view, the problem is NP-hard. Furthermore, it is extremely complicated and as the consequence no existing algorithm can guarantee to find a solution even if one exists no matter how high the complexity of the algorithm is. Previous approaches to the switch box routing problem can be divided into algorithmic approaches and knowledge-based approaches. The algorithmic approaches are efficient in computational time, but they are unsucessful at achieving high routing completion rate, especially for some dense and complicated switchbox routing problems. On the other hand, the knowledge-based approaches can achieve high routing completion rate, but they are not efficient in computation speed. In this thesis we present a hybrid approach to the switchbox routing problem. This hybrid approach is based on a new knowledge-based routing technique, namely synchronized routing, and combines some efficient algorithmic routing techniques. Experimental results show it can achieve the high routing completion rate of the knowledge-based approaches and the high efficiency of the algorithmic approaches. The constrained via minimization is an important optimization problem in VLSI routing. Its objective is to minimize the number of vias introduced in VLSI routing. From computational perspective, the constrained via minimization is NP-complete. Although for a special case where the number of wire segments splits at a via candidate is not more than three, elegant theoretical results have been obtained. For a general case in which there exist more than three wire segment splits at a via candidate few approaches have been proposed, and those approaches are only suitable for tackling some particular routing styles and are difficult or impossible to adjust to meet practical requirements. In this thesis we propose a new graph-theoretic model, namely switching graph model, for the constrained via minimization problem. The switching graph model can represent both grid-based and grid less routing problems, and allows arbitrary wire segments split at a via candidate. Then on the basis of the model, we present the first genetic algorithm for the constrained via minimization problem. This genetic algorithm can tackle various kinds of routing styles and be configured to meet practical constraints. Experimental results show that the genetic algorithm can find the optimal solutions for most cases in reasonable time

    The predictor-adaptor paradigm : automation of custom layout by flexible design

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    Analog layout design automation: ILP-based analog routers

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    The shrinking design window and high parasitic sensitivity in the advanced technology have imposed special challenges on the analog and radio frequency (RF) integrated circuit design. In this thesis, we propose a new methodology to address such a deficiency based on integer linear programming (ILP) but without compromising the capability of handling any special constraints for the analog routing problems. Distinct from the conventional methods, our algorithm utilizes adaptive resolutions for various routing regions. For a more congested region, a routing grid with higher resolution is employed, whereas a lower-resolution grid is adopted to a less crowded routing region. Moreover, we strengthen its speciality in handling interconnect width control so as to route the electrical nets based on analog constraints while considering proper interconnect width to address the acute interconnect parasitics, mismatch minimization, and electromigration effects simultaneously. In addition, to tackle the performance degradation due to layout dependent effects (LDEs) and take advantage of optical proximity correction (OPC) for resolution enhancement of subwavelength lithography, in this thesis we have also proposed an innovative LDE-aware analog layout migration scheme, which is equipped with our special routing methodology. The LDE constraints are first identified with aid of a special sensitivity analysis and then satisfied during the layout migration process. Afterwards the electrical nets are routed by an extended OPC-inclusive ILP-based analog router to improve the final layout image fidelity while the routability and analog constraints are respected in the meantime. The experimental results demonstrate the effectiveness and efficiency of our proposed methods in terms of both circuit performance and image quality compared to the previous works

    Incremental physical design

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    Using ant colony optimization for routing in microprocesors

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    Power consumption is an important constraint on VLSI systems. With the advancement in technology, it is now possible to pack a large range of functionalities into VLSI devices. Hence it is important to find out ways to utilize these functionalities with optimized power consumption. This work focuses on curbing power consumption at the design stage. This work emphasizes minimizing active power consumption by minimizing the load capacitance of the chip. Capacitance of wires and vias can be minimized using Ant Colony Optimization (ACO) algorithms. ACO provides a multi agent framework for combinatorial optimization problems and hence is used to handle multiple constraints of minimizing wire-length and vias to achieve the goal of minimizing capacitance and hence power consumption. The ACO developed here is able to achieve an 8% reduction of wire-length and 7% reduction in vias thereby providing a 7% reduction in total capacitance, compared to other state of the art routers
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