Abstract
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 x10-x100 over standard Monte Carlo.
Original language | English (US) |
---|---|
Title of host publication | Design, Automation, and Test in Europe |
Subtitle of host publication | The Most Influential Papers of 10 Years Date |
Publisher | Springer |
Pages | 235-251 |
Number of pages | 17 |
ISBN (Print) | 9781402064876 |
DOIs | |
State | Published - Dec 1 2008 |
ASJC Scopus subject areas
- Engineering(all)