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8th International Symposium on Quality Electronic Design (ISQED'07)
From Finance to Flip Flops: A Study of Fast Quasi-Monte Carlo Methods from Computational Finance Applied to Statistical Circuit Analysis
San Jose, California
March 26-March 28
ISBN: 0-7695-2795-7
ASCII Text
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Amith Singhee, Rob A. Rutenbar, "From Finance to Flip Flops: A Study of Fast Quasi-Monte Carlo Methods from Computational Finance Applied to Statistical Circuit Analysis," Quality Electronic Design, International Symposium on, pp. 685-692, 8th International Symposium on Quality Electronic Design (ISQED'07), 2007.
 
 
BibTex
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@article{ 10.1109/ISQED.2007.79,
author = {Amith Singhee and Rob A. Rutenbar},
title = {From Finance to Flip Flops: A Study of Fast Quasi-Monte Carlo Methods from Computational Finance Applied to Statistical Circuit Analysis},
journal ={Quality Electronic Design, International Symposium on},
volume = {0},
year = {2007},
isbn = {0-7695-2795-7},
pages = {685-692},
doi = {http://doi.ieeecomputersociety.org/10.1109/ISQED.2007.79},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Quality Electronic Design, International Symposium on
TI - From Finance to Flip Flops: A Study of Fast Quasi-Monte Carlo Methods from Computational Finance Applied to Statistical Circuit Analysis
SN - 0-7695-2795-7
SP685
EP692
A1 - Amith Singhee,
A1 - Rob A. Rutenbar,
PY - 2007
KW - null
VL - 0
JA - Quality Electronic Design, International Symposium on
ER -
 
Amith Singhee, Carnegie Mellon University, USA
Rob A. Rutenbar, Carnegie Mellon University, USA
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 2X to 50X.
Citation:
Amith Singhee, Rob A. Rutenbar, "From Finance to Flip Flops: A Study of Fast Quasi-Monte Carlo Methods from Computational Finance Applied to Statistical Circuit Analysis," isqed, pp.685-692, 8th International Symposium on Quality Electronic Design (ISQED'07), 2007
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