Paper Info
Title
From Finance to Flip Flops: A Study of Fast Quasi-Monte Carlo Methods from Computational Finance Applied to Statistical Circuit Analysis
Abstract
Problems in computational finance share many of the characteristics that challenge us in statistical circuit analysis: high dimensionality, profound nonlinearity, stringent accuracy requirements, and expensive sample simulation. We offer a detailed experimental study of how one celebrated technique from this domain - quasi-Monte Carlo (QMC) analysis - can be used for fast statistical circuit analysis. In contrast with traditional pseudo-random Monte Carlo sampling, QMC substitutes a (shorter) sequence of deterministically chosen sample points. Across a set of digital and analog circuits, in 90nm and 45nm technologies, varying in size from 30 to 400 devices, we obtain speedups in parametric yield estimation from 2times to 50times
Year
DOI
Venue
2007
10.1109/ISQED.2007.79
San Jose, CA
Keywords
Field
DocType
statistical circuit analysis,sample point,computational finance share,expensive sample simulation,quasi-monte carlo,celebrated technique,analog circuit,fast statistical circuit analysis,fast quasi-monte carlo methods,computational finance applied,qmc substitute,monte carlo sampling,flip flops,circuit analysis,digital circuits,computational modeling,convergence,quasi monte carlo method,finance,quasi monte carlo,pricing,security,analog circuits,monte carlo methods,computational finance,sampling methods
Digital electronics,Mathematical optimization,Monte Carlo method,Computational finance,Computer science,Algorithm,Quasi-Monte Carlo method,Electronic engineering,Curse of dimensionality,Parametric statistics,Sampling (statistics),Network analysis
Conference
ISBN
Citations 
PageRank 
0-7695-2795-7
37
2.38
References 
Authors
9
2
Name
Order
Citations
PageRank
Amith Singhee134722.94
Rob A. Rutenbar22283280.48