This book presents novel solutions to problems of efficient statistical analysis of circuits in the nanometer regime. It draws on theories from a wide variety of scientific fields and applies them to parallel problems in numerous other fields.

As VLSI technology moves to the nanometer scale for transistor feature sizes, the impact of manufacturing imperfections result in large variations in the circuit performance. Traditional CAD tools are not well-equipped to handle this scenario, since they do not model this statistical nature of the circuit parameters and performances, or if they do, the existing techniques tend to be over-simplified or intractably slow. Novel Algorithms for Fast Statistical Analysis of Scaled Circuits draws upon ideas for attacking parallel problems in other technical fields, such as computational finance, machine learning and actuarial risk, and synthesizes them with innovative attacks for the problem domain of integrated circuits. The result is a set of novel solutions to problems of efficient statistical analysis of circuits in the nanometer regime.

Presents flexible and general techniques for statistical analysis that can be applied to wide variety of circuit applications Applies theory from a wide variety of scientific fields (machine learning, computational finance, number theory, actuarial studies) Covers relevant theory in detail This is the first book to present these novel techniques Extensive experiments, illustrative examples and analysis Includes supplementary material: sn.pub/extras

Inhalt
SiLVR: Projection Pursuit for Response Surface Modeling.- Quasi-Monte Carlo for Fast Statistical Simulation of Circuits.- Statistical Blockade: Estimating Rare Event Statistics.- Concluding Observations.