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Des. Autom. Electron. Syst."],"published-print":{"date-parts":[[2018,5,31]]},"abstract":"<jats:p>\n            Yield\n            <jats:sup>1<\/jats:sup>\n            analysis of SRAM is a challenging issue, because the failure rates of SRAM cells are extremely small. In this article, an efficient non-Gaussian sampling method of cross entropy optimization is proposed for estimating the high sigma SRAM yield. Instead of sampling with the Gaussian distribution in existing methods, a non-Gaussian distribution, i.e., a joint one-dimensional generalized Pareto distribution and (\n            <jats:italic>n<\/jats:italic>\n            -1)-dimensional Gaussian distribution, is taken as the function family of practical distribution, which is proved to be more suitable to fit the ideal distribution in the view of extreme failure event. To minimize the cross entropy between practical and ideal distributions, a sequential quadratic programing solver with multiple starting points strategy is applied for calculating the optimal parameters of practical distributions. Experimental results show that the proposed non-Gaussian sampling is a 2.2--4.1\u00d7 speedup over the Gaussian sampling, on the whole, it is about a 1.6--2.3\u00d7 speedup over state-of-the-art methods with low- and high-dimensional cases without loss of accuracy\n          <\/jats:p>","DOI":"10.1145\/3174866","type":"journal-article","created":{"date-parts":[[2018,3,16]],"date-time":"2018-03-16T12:49:41Z","timestamp":1521204581000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["An Efficient Non-Gaussian Sampling Method for High Sigma SRAM Yield Analysis"],"prefix":"10.1145","volume":"23","author":[{"given":"Jinyuan","family":"Zhai","sequence":"first","affiliation":[{"name":"Fudan University, Shanghai, China"}]},{"given":"Changhao","family":"Yan","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}]},{"given":"Sheng-Guo","family":"Wang","sequence":"additional","affiliation":[{"name":"University of North Carolina at Charlotte, North Carolina"}]},{"given":"Dian","family":"Zhou","sequence":"additional","affiliation":[{"name":"Fudan University and University of Texas at Dallas, Richardson, Texas"}]},{"given":"Hai","family":"Zhou","sequence":"additional","affiliation":[{"name":"Fudan University and Northwestern University, Evanston, IL"}]},{"given":"Xuan","family":"Zeng","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}]}],"member":"320","published-online":{"date-parts":[[2018,3,16]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2024724.2024769"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1146909.1146930"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.5555\/1509456.1509533"},{"key":"e_1_2_1_4_1","volume-title":"Proceedings of the Conference on Design, Automation and Test in Europe. 801--806","author":"Masood Qazi","year":"2010","unstructured":"Qazi Masood , Tikekar Mehul , Dolecek Lara , Shah Devavrat , Chandrakasan and Anantha . 2010 . 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