Abstract
Importance Sampling allows for efficient Monte Carlo sampling that also properly covers tails of distributions. From Large Deviation Theory we derive an optimal upper bound for the number of samples to efficiently sample for an accurate fail probability P fail = 10- 10. We apply this to accurately and efficiently minimize the access time of Static Random Access Memory (SRAM), while guaranteeing a statistical constraint on the yield target.
Original language | English |
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Title of host publication | Scientific Computing in Electrical Engineering SCEE 2010 |
Editors | B. Michielsen, J.R. Poirier |
Place of Publication | Berlin |
Publisher | Springer |
Pages | 39-47 |
ISBN (Print) | 978-3-642-22452-2 |
DOIs | |
Publication status | Published - 2012 |
Event | Scientific Computing in Electrical Engineering, SCEE 2010 - Toulouse, France Duration: 19 Sep 2010 → 24 Sep 2010 https://scee-conferences.org/ |
Publication series
Name | Mathematics in Industry |
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Volume | 16 |
ISSN (Print) | 1612-3956 |
Conference
Conference | Scientific Computing in Electrical Engineering, SCEE 2010 |
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Country/Territory | France |
City | Toulouse |
Period | 19/09/10 → 24/09/10 |
Other | SCEE 2010 |
Internet address |