Spatial-correlation-aware soft error rate analysis using quasi-importance sampling

Xin Tian Wu*, Kai Hua Hsu, Lynn C.L. Chang, Charles H.P. Wen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Since statistical methods are important to accurately estimate the soft error rate (SER) of circuits with process variations, we incorporate the spatial correlation into SSER analysis to provide better accuracy. Moreover, the SSER analysis based on quasi-Monte Carlo comes into the difficulty of sampling points on a non-uniform distribution or unbounded distribution. Therefore, in this paper, we employ the quasi-importance sampling into Monte-Carlo simulation to overcome such sampling issue. Experimental results show that the quasi-importance sampling Monte-Carlo SSER analysis framework is capable of more precisely estimating circuit SSERs and reaches 3.72X speedups when compared to the baseline Monte-Carlo simulation

Original languageEnglish
Title of host publication2012 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2012 - Proceedings of Technical Papers
DOIs
StatePublished - 25 Jul 2012
Event2012 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2012 - Hsinchu, Taiwan
Duration: 23 Apr 201225 Apr 2012

Publication series

Name2012 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2012 - Proceedings of Technical Papers

Conference

Conference2012 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2012
CountryTaiwan
CityHsinchu
Period23/04/1225/04/12

Keywords

  • importance sampling
  • quasi-monte carlo
  • spatial correlations
  • statistical soft error rate

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