|Statement||by Ruijing Shen, Sheldon X.-D. Tan, Hao Yu|
|Contributions||Tan, Sheldon X. D., Yu, Hao, SpringerLink (Online service)|
|The Physical Object|
|Format||[electronic resource] /|
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. Add tags for "Statistical Performance Analysis and Modeling Techniques for Nanometer VLSI Designs". Be the first. Part V of this book focuses on the performance bound and statistical analysis of nanometer analog/mixed-signal circuits and the yield analysis and optimization based on statistical performance analysis and modeling. Chapter 14 presents per-formance bound analysis technique in s-domain for linearized analog circuits using. Statistical Yield Analysis and Design for Nanometer VLSI by Javid Jaffari A thesis Reliable and efﬁcient statistical analysis The proposed sampling-based yield analysis methods beneﬁt from the very appealing feature of the MC method, that is, the capability to consider any complex circuit model.
The proposed sampling-based yield analysis methods benefit from the very appealing feature of the MC method, that is, the capability to consider any complex circuit model. However, through the use and engineering of advanced variance reduction and sampling methods, ultra-fast yield estimation solutions are provided for different types of VLSI. This paper explores performance estimation of VLSI design using simple RC delay model based an Elmore Delay Method. In this paper Pre-layout & Post-layout VLSI design flow for delay convergence is. plex VLSI circuits. It has therefore become imperative to model, analyze and optimize the effects of uncertainty for reliable operation to avoid the large costs associated with guard-banding VLSI circuits. In this chapter, we give a brief overview of the sources, taxonomy and impact of variability on performance analysis with emphasis on timing. Design and Modeling of Low Power VLSI Systems analyzes various traditional and modern low power techniques for integrated circuit design in addition to the limiting factors of existing techniques and methods for optimization. Through a research-based discussion of the technicalities involved in the VLSI hardware development process cycle, this.
The intrinsic variability of nanoscale VLSI technology must be taken into account when analyzing circuit designs to predict likely yield. Monte-Carlo- (MC-) and quasi-MC- (QMC-) based statistical techniques do this by analysing many randomised or quasirandomised copies of circuits. The randomisation must model forms of variability that occur in nano-CMOS technology, including atomistic Author: Zheng Xie, Doug Edwards. This book provides readers with an up-to-date account of the use of machine learning frameworks, methodologies, algorithms and techniques in the context of computer-aided design (CAD) for very-large-scale integrated circuits (VLSI). Introduction This book provides comprehensive coverage of the recent advances in symbolic analysis techniques for design automation of nanometer VLSI systems. The presentation is organized in parts of fundamentals, basic implementation methods and applications for VLSI design. springer, This book provides comprehensive coverage of the recent advances in symbolic analysis techniques for design automation of nanometer VLSI systems. The presentation is organized in parts of fundamentals, basic implementation methods and applications for VLSI design. Topics emphasized include statistical timing and crosstalk analysis, statistical and parallel analysis, performance .