Statistical Analysis And Design Of Nanoscale Vlsi Circuits Under Parameter Variations

Knowledge exists: you only have to ?nd it VLSI design has come to an important in?ection point with the appearance of large manufacturing variations as semiconductor technology has moved to 45 nm feature sizes and below. If we ignore the random variations in the manufacturing process, simulation-based design essentially becomes useless, since its predictions will be far from the reality of manufactured ICs. On the other hand, using design margins based on some traditional notion of worst-case scenarios can force us to sacri?ce too much in terms of power consumption or manufacturing cost, to the extent of making the design goals even infeasible. We absolutely need to explicitly account for the statistics of this random variability, to have design margins that are accurate so that we can ?nd the optimum balance between yield loss and design cost. This discontinuity in design processes has led many researchers to develop effective methods of statistical design, where the designer can simulate not just the behavior of the nominal design, but the expected statistics of the behavior in manufactured ICs. Memory circuits tend to be the hardest hit by the problem of these random variations because of their high replication count on any single chip, which demands a very high statistical quality from the product. Requirements of 5–6s (0.

Since process variation and chip performance uncertainties have become more pronounced as technologies scale down into the nanometer regime, accurate and efficient modeling or characterization of variations from the device to the architecture level have become imperative for the successful design of VLSI chips. This book provides readers with tools for variation-aware design methodologies and computer-aided design (CAD) of VLSI systems, in the presence of process variations at the nanometer scale. It presents the latest developments for modeling and analysis, with a focus on statistical interconnect modeling, statistical parasitic extractions, statistical full-chip leakage and dynamic power analysis considering spatial correlations, statistical analysis and modeling for large global interconnects and analog/mixed-signal circuits. Provides readers with timely, systematic and comprehensive treatments of statistical modeling and analysis of VLSI systems with a focus on interconnects, on-chip power grids and clock networks, and analog/mixed-signal circuits; Helps chip designers understand the potential and limitations of their design tools, improving their design productivity; Presents analysis of each algorithm with practical applications in the context of real circuit design; Includes numerical examples for the quantitative analysis and evaluation of algorithms presented. Provides readers with timely, systematic and comprehensive treatments of statistical modeling and analysis of VLSI systems with a focus on interconnects, on-chip power grids and clock networks, and analog/mixed-signal circuits; Helps chip designers understand the potential and limitations of their design tools, improving their design productivity; Presents analysis of each algorithm with practical applications in the context of real circuit design; Includes numerical examples for the quantitative analysis and evaluation of algorithms presented.

Design considerations for low-power operations and robustness with respect to variations typically impose contradictory requirements. Low-power design techniques such as voltage scaling, dual-threshold assignment and gate sizing can have large negative impact on parametric yield under process variations. This book focuses on circuit/architectural design techniques for achieving low power operation under parameter variations. We consider both logic and memory design aspects and cover modeling and analysis, as well as design methodology to achieve simultaneously low power and variation tolerance, while minimizing design overhead. This book will discuss current industrial practices and emerging challenges at future technology nodes.

This volume is the first complete overview of VLSI design methods that use statistical techniques for dealing with the random phenomena that are inherent in all VLSI manufacturing processes. VLSI design today cannot be performed without taking into account economic-related issues such as yield, cost and performance oriented tradeoffs. The book includes practical methods relevant to real life applications. It contains edited papers by top industrial and academic specialists in the field. These papers describe all three categories of CAD tools employed for statistical design: IC performance optimization tools, process simulation tools and tools for characterization of process fluctuations. In each category both practical approaches and more theoretical approaches are presented.

This monograph is motivated by the challenges faced in designing reliable VLSI systems in modern VLSI processes. The reliable operation of integrated circuits (ICs) has become increasingly dif?cult to achieve in the deep submicron (DSM) era. With continuouslydecreasing device feature sizes, combinedwith lower supply voltages and higher operating frequencies, the noise immunity of VLSI circuits is decreasing alarmingly. Thus, VLSI circuits are becoming more vulnerable to noise effects such as crosstalk, power supply variations, and radiation-inducedsoft errors. Among these noise sources, soft errors(or error caused by radiation particle strikes) have become an increasingly troublesome issue for memory arrays as well as c- binational logic circuits. Also, in the DSM era, process variations are increasing at a signi?cant rate, making it more dif?cult to design reliable VLSI circuits. Hence, it is important to ef?ciently design robust VLSI circuits that are resilient to radiation particle strikes and process variations. The work presented in this research mo- graph presents several analysis and design techniques with the goal of realizing VLSI circuits, which are radiation and process variation tolerant.

Covers the statistical analysis and optimization issues arising due to increased process variations in current technologies. Comprises a valuable reference for statistical analysis and optimization techniques in current and future VLSI design for CAD-Tool developers and for researchers interested in starting work in this very active area of research. Written by author who lead much research in this area who provide novel ideas and approaches to handle the addressed issues

This book describes methodologies in the design of VLSI devices, circuits and their applications at nanoscale levels. The book begins with the discussion on the dominant role of power dissipation in highly scaled devices.The 15 Chapters of the book are classified under four sections that cover design, modeling, and simulation of electronic, magnetic and compound semiconductors for their applications in VLSI devices, circuits, and systems. This comprehensive volume eloquently presents the design methodologies for ultra–low power VLSI design, potential post–CMOS devices, and their applications from the architectural and system perspectives. The book shall serve as an invaluable reference book for the graduate students, Ph.D./ M.S./ M.Tech. Scholars, researchers, and practicing engineers working in the frontier areas of nanoscale VLSI design.

As MOS devices are scaled to meet increasingly demanding circuit specifications, process variations have a greater effect on the reliability of circuit performance. For this reason, statistical techniques are required to design integrated circuits with maximum yield. Statistical Modeling for Computer-Aided Design of MOS VLSI Circuits describes a statistical circuit simulation and optimization environment for VLSI circuit designers. The first step toward accomplishing statistical circuit design and optimization is the development of an accurate CAD tool capable of performing statistical simulation. This tool must be based on a statistical model which comprehends the effect of device and circuit characteristics, such as device size, bias, and circuit layout, which are under the control of the circuit designer on the variability of circuit performance. The distinctive feature of the CAD tool described in this book is its ability to accurately model and simulate the effect in both intra- and inter-die process variability on analog/digital circuits, accounting for the effects of the aforementioned device and circuit characteristics. Statistical Modeling for Computer-Aided Design of MOS VLSI Circuits serves as an excellent reference for those working in the field, and may be used as the text for an advanced course on the subject.

"The last couple of years have been very busy for the semiconductor industry and researchers. The rapid speed of production channel length reduction has brought lithographic challenges to semiconductor modeling. These include stress optimization, transisto"