Title :
From Finance to Flip Flops: A Study of Fast Quasi-Monte Carlo Methods from Computational Finance Applied to Statistical Circuit Analysis
Author :
Singhee, Amith ; Rutenbar, Rob A.
Author_Institution :
Dept. of ECE, Carnegie Mellon Univ., Pittsburgh, PA
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
Keywords :
Monte Carlo methods; circuit analysis computing; sampling methods; 45 nm; 90 nm; QMC analysis; analog circuits; computational finance; digital circuits; flip flops; parametric yield estimation; pseudo-random Monte Carlo sampling; quasi-Monte Carlo methods; statistical circuit analysis; Analytical models; Circuit analysis; Circuit analysis computing; Computational modeling; Convergence; Finance; Instruments; Monte Carlo methods; Pricing; Security;
Conference_Titel :
Quality Electronic Design, 2007. ISQED '07. 8th International Symposium on
Conference_Location :
San Jose, CA
Print_ISBN :
0-7695-2795-7
DOI :
10.1109/ISQED.2007.79
