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This monograph represents a summary of our work in the last two years in applying the method of simulated annealing to the solution of problems that arise in the physical design of VLSI circuits. Our study is experimental in nature, in that we are con cerned with issues such as solution representations, neighborhood structures, cost functions, approximation schemes, and so on, in order to obtain good design results in a reasonable amount of com putation time. We hope that our experiences with the techniques we employed, some of which indeed bear certain similarities for different problems, could be useful as hints and guides for other researchers in applying the method to the solution of other prob lems. Work reported in this monograph was partially supported by the National Science Foundation under grant MIP 87-03273, by the Semiconductor Research Corporation under contract 87-DP- 109, by a grant from the General Electric Company, and by a grant from the Sandia Laboratories.
From my B.E.E degree at the University of Minnesota and right through my S.M. degree at M.I.T., I had specialized in solid state devices and microelectronics. I made the decision to switch to computer-aided design (CAD) in 1981, only a year or so prior to the introduction of the simulated annealing algorithm by Scott Kirkpatrick, Dan Gelatt, and Mario Vecchi of the IBM Thomas 1. Watson Research Center. Because Prof. Alberto Sangiovanni-Vincentelli, my UC Berkeley advisor, had been a consultant at IBM, I re ceived a copy of the original IBM internal report on simulated annealing approximately the day of its release. Given my background in statistical mechanics and solid state physics, I was immediately impressed by this new combinatorial optimization technique. As Prof. Sangiovanni-Vincentelli had suggested I work in the areas of placement and routing, it was in these realms that I sought to explore this new algorithm. My flJ'St implementation of simulated annealing was for an island-style gate array placement problem. This work is presented in the Appendix of this book. I was quite struck by the effect of a nonzero temperature on what otherwise appears to be a random in terchange algorithm.
The Best of ICCAD marks the 20th anniversary of the International Conference on Computer Aided Design. This book presents a selection of papers from among the best contributions presented in ICCAD based on their impact on research and applications. The Best of ICCAD contains overview articles solicited from leading EDA researchers that comment on the historical context of the selected papers and outline their impact on follow up work. Nine leading companies including Cadence, Synopsys, Fujitsu, IBM and Magma offer "Industry Viewpoints" outlining the impact of ICCAD on their businesses. The Best of ICCAD provides an insightful reminder on how much progress has been made in EDA in the past twenty years and will be a useful tool for professionals in the field and students in the pursuit to crack the next wave of emerging EDA problems.
Introduction The exponential scaling of feature sizes in semiconductor technologies has side-effects on layout optimization, related to effects such as inter connect delay, noise and crosstalk, signal integrity, parasitics effects, and power dissipation, that invalidate the assumptions that form the basis of previous design methodologies and tools. This book is intended to sample the most important, contemporary, and advanced layout opti mization problems emerging with the advent of very deep submicron technologies in semiconductor processing. We hope that it will stimulate more people to perform research that leads to advances in the design and development of more efficient, effective, and elegant algorithms and design tools. Organization of the Book The book is organized as follows. A multi-stage simulated annealing algorithm that integrates floorplanning and interconnect planning is pre sented in Chapter 1. To reduce the run time, different interconnect plan ning approaches are applied in different ranges of temperatures. Chapter 2 introduces a new design methodology - the interconnect-centric design methodology and its centerpiece, interconnect planning, which consists of physical hierarchy generation, floorplanning with interconnect planning, and interconnect architecture planning. Chapter 3 investigates a net-cut minimization based placement tool, Dragon, which integrates the state of the art partitioning and placement techniques.
Design and optimization of integrated circuits are essential to the creation of new semiconductor chips, and physical optimizations are becoming more prominent as a result of semiconductor scaling. Modern chip design has become so complex that it is largely performed by specialized software, which is frequently updated to address advances in semiconductor technologies and increased problem complexities. A user of such software needs a high-level understanding of the underlying mathematical models and algorithms. On the other hand, a developer of such software must have a keen understanding of computer science aspects, including algorithmic performance bottlenecks and how various algorithms operate and interact. "VLSI Physical Design: From Graph Partitioning to Timing Closure" introduces and compares algorithms that are used during the physical design phase of integrated-circuit design, wherein a geometric chip layout is produced starting from an abstract circuit design. The emphasis is on essential and fundamental techniques, ranging from hypergraph partitioning and circuit placement to timing closure.
This book presents state of the art contributes to Simulated Annealing (SA) that is a well-known probabilistic meta-heuristic. It is used to solve discrete and continuous optimization problems. The significant advantage of SA over other solution methods has made it a practical solution method for solving complex optimization problems. Book is consisted of 13 chapters, classified in single and multiple objectives applications and it provides the reader with the knowledge of SA and several applications. We encourage readers to explore SA in their work, mainly because it is simple and can determine extremely very good results.
The physical design flow of any project depends upon the size of the design, the technology, the number of designers, the clock frequency, and the time to do the design. As technology advances and design-styles change, physical design flows are constantly reinvented as traditional phases are removed and new ones are added to accommodate changes in technology. Handbook of Algorithms for Physical Design Automation provides a detailed overview of VLSI physical design automation, emphasizing state-of-the-art techniques, trends and improvements that have emerged during the previous decade. After a brief introduction to the modern physical design problem, basic algorithmic techniques, and partitioning, the book discusses significant advances in floorplanning representations and describes recent formulations of the floorplanning problem. The text also addresses issues of placement, net layout and optimization, routing multiple signal nets, manufacturability, physical synthesis, special nets, and designing for specialized technologies. It includes a personal perspective from Ralph Otten as he looks back on the major technical milestones in the history of physical design automation. Although several books on this topic are currently available, most are either too broad or out of date. Alternatively, proceedings and journal articles are valuable resources for researchers in this area, but the material is widely dispersed in the literature. This handbook pulls together a broad variety of perspectives on the most challenging problems in the field, and focuses on emerging problems and research results.
Proceedings of the NATO Advanced Study Institute, L'Aquila, Italy, July 7-18, 1986
One of the keys to success in the IC industry is getting a new product to market in a timely fashion and being able to produce that product with sufficient yield to be profitable. There are two ways to increase yield: by improving the control of the manufacturing process and by designing the process and the circuits in such a way as to minimize the effect of the inherent variations of the process on performance. The latter is typically referred to as "design for manufacture" or "statistical design". As device sizes continue to shrink, the effects of the inherent fluctuations in the IC fabrication process will have an even more obvious effect on circuit performance. And design for manufacture will increase in importance. We have been working in the area of statistically based computer aided design for more than 13 years. During the last decade we have been working with each other, and individually with our students, to develop methods and CAD tools that can be used to improve yield during the design and manufacturing phases of IC realization. This effort has resulted in a large number of publications that have appeared in a variety of journals and conference proceedings. Thus our motivation in writing this book is to put, in one place, a description of our approach to IC yield enhancement. While the work that is contained in this book has appeared in the open literature, we have attempted to use a consistent notation throughout this book.
The goal of the research out of which this monograph grew, was to make annealing as much as possible a general purpose optimization routine. At first glance this may seem a straight-forward task, for the formulation of its concept suggests applicability to any combinatorial optimization problem. All that is needed to run annealing on such a problem is a unique representation for each configuration, a procedure for measuring its quality, and a neighbor relation. Much more is needed however for obtaining acceptable results consistently in a reasonably short time. It is even doubtful whether the problem can be formulated such that annealing becomes an adequate approach for all instances of an optimization problem. Questions such as what is the best formulation for a given instance, and how should the process be controlled, have to be answered. Although much progress has been made in the years after the introduction of the concept into the field of combinatorial optimization in 1981, some important questions still do not have a definitive answer. In this book the reader will find the foundations of annealing in a self-contained and consistent presentation. Although the physical analogue from which the con cept emanated is mentioned in the first chapter, all theory is developed within the framework of markov chains. To achieve a high degree of instance independence adaptive strategies are introduced.