Xingsheng Wang, D. Reid, Liping Wang, A. Burenkov, C. Millar, B. Cheng, André Lange, J. Lorenz, E. Baer, A. Asenov
{"title":"Variability-aware compact model strategy for 20-nm bulk MOSFETs","authors":"Xingsheng Wang, D. Reid, Liping Wang, A. Burenkov, C. Millar, B. Cheng, André Lange, J. Lorenz, E. Baer, A. Asenov","doi":"10.1109/SISPAD.2014.6931621","DOIUrl":null,"url":null,"abstract":"In this paper a variability-aware compact modeling strategy is presented for 20-nm bulk planar technology, taking into account the critical dimension long-range process variation and local statistical variability. Process and device simulations and statistical simulations for a wide range of combinations of L and W are carefully carried out using a design of experiments approach. The variability aware compact model strategy features a comprehensively extracted nominal model and two groups of selected parameters for extractions of the long-range process variation and statistical variability. The unified variability compact modeling method can provide a simulation frame for variability aware technology circuit co-optimization.","PeriodicalId":101858,"journal":{"name":"2014 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SISPAD.2014.6931621","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper a variability-aware compact modeling strategy is presented for 20-nm bulk planar technology, taking into account the critical dimension long-range process variation and local statistical variability. Process and device simulations and statistical simulations for a wide range of combinations of L and W are carefully carried out using a design of experiments approach. The variability aware compact model strategy features a comprehensively extracted nominal model and two groups of selected parameters for extractions of the long-range process variation and statistical variability. The unified variability compact modeling method can provide a simulation frame for variability aware technology circuit co-optimization.