Enes Eken, Yaojun Zhang, et al.
DAC 2014
A number of researchers described a mixture importance sampling (MixIS) methodology to enable yield-driven design and extends its application beyond memories to peripheral circuits and logic blocks. The sampling methodology was developed by researchers as a fast Monte Carlo technique developed for memory analysis. The MixIS was a comprehensive and computationally efficient method of estimating low failure probabilities of SRAM designs. This method relied on distorting the Monte Carlo sampling function to produce more samples in the important regions and rare-failure-event critical regions. The MixIS methodology was universal and its efficiency was independent of the underlying technology or application. The methodology was also used to compare two different local bit-select circuits in 45-nm technology.
Enes Eken, Yaojun Zhang, et al.
DAC 2014
Rajiv Joshi, Keunwoo Kim, et al.
VLSID/Embedded 2010
Rajiv Joshi, Rouwaida Kanj
ICICDT 2009
Rouwaida Kanj, Rajiv Joshi, et al.
ISQED 2007