Doctor of Philosophy

dissertationRecent breakthroughs in silicon photonics technology are enabling the integration of optical devices into silicon-based semiconductor processes. Photonics technology enables high-speed, high-bandwidth, and high-fidelity communications on the chip-scale-an important development in an increasingly communications-oriented semiconductor world. Significant developments in silicon photonic manufacturing and integration are also enabling investigations into applications beyond that of traditional telecom: sensing, filtering, signal processing, quantum technology-and even optical computing. In effect, we are now seeing a convergence of communications and computation, where the traditional roles of optics and microelectronics are becoming blurred. As the applications for opto-electronic integrated circuits (OEICs) are developed, and manufacturing capabilities expand, design support is necessary to fully exploit the potential of this optics technology. Such design support for moving beyond custom-design to automated synthesis and optimization is not well developed. Scalability requires abstractions, which in turn enables and requires the use of optimization algorithms and design methodology flows. Design automation represents an opportunity to take OEIC design to a larger scale, facilitating design-space exploration, and laying the foundation for current and future optical applications-thus fully realizing the potential of this technology. This dissertation proposes design automation for integrated optic system design. Using a buildingblock model for optical devices, we provide an EDA-inspired design flow and methodologies for optical design automation. Underlying these flows and methodologies are new supporting techniques in behavioral and physical synthesis, as well as device-resynthesis techniques for thermal-aware system integration. We also provide modeling for optical devices and determine optimization and constraint parameters that guide the automation techniques. Our techniques and methodologies are then applied to the design and optimization of optical circuits and devices. Experimental results are analyzed to evaluate their efficacy. We conclude with discussions on the contributions and limitations of the approaches in the context of optical design automation, and describe the tremendous opportunities for future research in design automation for integrated optics

Lower and Upper-Bounds for the General Junction Routing Problem

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryNational Science Foundation / ECS 84-10902Semiconductor Research Corporatio

Switchbox Routing in VLSI Design: Closing the Complexity Gap

The design of integrated circuits has achieved a great deal of attention in the last decade. In the routing phase, there have survived two open layout problems which are important from both the theoretical and the practical point of view. Up to now, switchbox routing has been known to be solvable in polynomial time when there are only 2-terminal nets, and to be NP}-complete in case there exist nets involving at least five terminals. Our main result is that this problem is NP}-complete even if no net has more that three terminals. Hence, from the theoretical perspective, the SRP is completely settled. The NP–completeness proof is based on a reduction from a special kind of the satisfiability problem. It is also possible to adopt our construction to channel routing which shows that this problem is NP–complete, even if each net does not consist of more than five terminals. This improves upon a result of Sarrafzadeh who proved the NP–completeness in case of nets with no more than six terminals

Channel routing: Efficient solutions using neural networks

Neural network architectures are effectively applied to solve the channel routing problem. Algorithms for both two-layer and multilayer channel-width minimization, and constrained via minimization are proposed and implemented. Experimental results show that the proposed channel-width minimization algorithms are much superior in all respects compared to existing algorithms. The optimal two-layer solutions to most of the benchmark problems, not previously obtained, are obtained for the first time, including an optimal solution to the famous Deutch\u27s difficult problem. The optimal solution in four-layers for one of the be lchmark problems, not previously obtained, is obtained for the first time. Both convergence rate and the speed with which the simulations are executed are outstanding. A neural network solution to the constrained via minimization problem is also presented. In addition, a fast and simple linear-time algorithm is presented, possibly for the first time, for coloring of vertices of an interval graph, provided the line intervals are given

A Density-Based General Greedy Channel Routing Algorithm in VLSI Design Automation.

One of the most important forms of routing strategies is called channel routing . This approach allows us to reduce the extremely difficult VLSI layout problem to a collection of simpler subproblems. For channel routing problems, most frequently mentioned heuristic algorithms use parameters derived from experiments to approach the routing solution without carefully considering the effect of each selected wire segment to the final routing solution. In this dissertation, we propose a new channel routing algorithm in the two-layer restricted-Manhattan routing model (2-RM) in detail. There are three phases involved in developing the new routing algorithm. In the first phase, we distinguish one type of wire from the others using some optimality criteria, which makes the selection of a set of best horizontal wire segments for a track more effective so that good performance of the generated routing solutions can be achieved. In the second phase, we develop a theoretical framework related to two major data structures, column density and vertical constraint graph, which effectively improves search efficiency and routing performance. Finally in the third phase, we develop an efficient powerful heuristic channel routing algorithm based on the concepts shown in phase one and the theoretical framework proposed in phase two. We highlight the application of our algorithm to the channel routing problems in the three-layer restricted-Manhattan overlap (3-RM-O) and three-layer Manhattan overlay (3-M-O) routing models. On many tests we have conducted on the examples known in the literature, our algorithm has performed as well or better than the existing algorithms in both 2-RM and 3-M-O routing models. Our experiments show that our approach has the potential to outperform other algorithms in other routing models

A Router for Symmetrical FPGAs based on Exact Routing Density Evaluation

Abstract This paper presents a new performance and routability driven routing algorithm for symmetrical array based field-programmable gate arrays (FPGAs). A key contribution of our work is to overcome one essential limitation of the previous routing algorithms: inaccurate estimations of routing density which were too general for symmetrical FPGAs. To this end, we derive an exact routing density calculation that is based on a precise analysis of the structure (switch block) of symmetrical FPGAs, and utilize it consistently in global and detailed routings. With an introduction of the proposed accurate routing metrics, we design a new routing algorithm called a cost-effective net-decomposition based routing which is fast, and yet produces remarkable routing results in terms of both routability and path/net delays. We performed an extensive experiment to show the effectiveness of our algorithm based on the proposed cost metrics

Parallel Processing for VLSI CAD Applications a Tutorial

Coordinated Science Laboratory was formerly known as Control Systems LaboratorySemiconductor Research CorporationAuthor's name appears in front matter as Prithviraj Banerje