Statistical Blockade: A Novel Method for Very Fast Monte Carlo Simulation of Rare Circuit Events, and its Application

Circuit reliability under statistical process variation is an area of growing concern. For highly replicated circuits such as SRAMs and flip flops, a rare statistical event for one circuit may induce a not-so-rare system failure. Existing techniques perform poorly when tasked to generate both effici...

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Bibliographic Details
Published in2007 Design, Automation & Test in Europe Conference & Exhibition pp. 1 - 6
Main Authors Singhee, A., Rutenbar, R.A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2007
Subjects
Circuit simulation
Data mining
Filters
Measurement
Monte Carlo methods
Probability distribution
Random access memory
Statistical distributions
Statistics
Tail
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Summary:Circuit reliability under statistical process variation is an area of growing concern. For highly replicated circuits such as SRAMs and flip flops, a rare statistical event for one circuit may induce a not-so-rare system failure. Existing techniques perform poorly when tasked to generate both efficient sampling and sound statistics for these rare events. Statistical blockade is a novel Monte Carlo technique that allows us to efficiently filter - to block - unwanted samples insufficiently rare in the tail distributions we seek. The method synthesizes ideas from data mining and extreme value theory, and shows speed-ups of 10times - 100times over standard Monte Carlo
ISBN:3981080122
9783981080124
ISSN:1530-1591
1558-1101
DOI:10.1109/DATE.2007.364490