Recursive statistical blockade: An enhanced technique for rare event simulation with application to SRAM circuit design

Amith Singhee, Jiajing Wang, Benton H. Calhoun, Rob A. Rutenbar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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. The authors of [1] proposed Statistical Blockade as a Monte Carlo technique that allows us to efficiently filter-to block-unwanted samples insufficiently rare in the tail distributions we seek. However, there are significant practical problems with the technique. In this work, we show common scenarios in SRAM design where these problems render Statistical Blockade ineffective. We then propose significant extensions to make Statistical Blockade practically usable in these common scenarios. We show speedups of 102+ over standard Statistical Blockade and 104+ over standard Monte Carlo, for an SRAM cell in an industrial 90nm technology.

Original languageEnglish (US)
Title of host publicationProceedings - 21st International Conference on VLSI Design, VLSI DESIGN 2008
Pages131-136
Number of pages6
DOIs
StatePublished - 2008
Externally publishedYes
Event21st International Conference on VLSI Design, VLSI DESIGN 2008 - Hyderabad, India
Duration: Jan 4 2008Jan 8 2008

Publication series

NameProceedings of the IEEE International Frequency Control Symposium and Exposition

Other

Other21st International Conference on VLSI Design, VLSI DESIGN 2008
Country/TerritoryIndia
CityHyderabad
Period1/4/081/8/08

ASJC Scopus subject areas

  • General Engineering

Fingerprint

Dive into the research topics of 'Recursive statistical blockade: An enhanced technique for rare event simulation with application to SRAM circuit design'. Together they form a unique fingerprint.

Cite this