dc.contributor.author | Elfadel, Ibrahim M. | |
dc.contributor.author | Zhang, Zheng | |
dc.contributor.author | El Moselhy, Tarek Ali | |
dc.contributor.author | Daniel, Luca | |
dc.date.accessioned | 2017-04-25T19:05:25Z | |
dc.date.available | 2017-04-25T19:05:25Z | |
dc.date.issued | 2013-09 | |
dc.identifier.issn | 0278-0070 | |
dc.identifier.issn | 1937-4151 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/108401 | |
dc.description.abstract | Uncertainties have become a major concern in integrated circuit design. In order to avoid the huge number of repeated simulations in conventional Monte Carlo flows, this paper presents an intrusive spectral simulator for statistical circuit analysis. Our simulator employs the recently developed generalized polynomial chaos expansion to perform uncertainty quantification of nonlinear transistor circuits with both Gaussian and non-Gaussian random parameters. We modify the nonintrusive stochastic collocation (SC) method and develop an intrusive variant called stochastic testing (ST) method. Compared with the popular intrusive stochastic Galerkin (SG) method, the coupled deterministic equations resulting from our proposed ST method can be solved in a decoupled manner at each time point. At the same time, ST requires fewer samples and allows more flexible time step size controls than directly using a nonintrusive SC solver. These two properties make ST more efficient than SG and than existing SC methods, and more suitable for time-domain circuit simulation. Simulation results of several digital, analog and RF circuits are reported. Since our algorithm is based on generic mathematical models, the proposed ST algorithm can be applied to many other engineering problems. | en_US |
dc.language.iso | en_US | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/TCAD.2013.2263039 | en_US |
dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
dc.source | Prof. Daniel via Phoebe Ayers | en_US |
dc.title | Stochastic Testing Method for Transistor-Level Uncertainty Quantification Based on Generalized Polynomial Chaos | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Zhang, Zheng; El-Moselhy, Tarek A.; Elfadel, Ibrahim M. and Daniel, Luca. "Stochastic Testing Method for Transistor-Level Uncertainty Quantification Based on Generalized Polynomial Chaos." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 32, no. 10 (October 2013): 1533-1545. © 2013 Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
dc.contributor.approver | Daniel, Luca | en_US |
dc.contributor.mitauthor | Zhang, Zheng | |
dc.contributor.mitauthor | El Moselhy, Tarek Ali | |
dc.contributor.mitauthor | Daniel, Luca | |
dc.relation.journal | IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dspace.orderedauthors | Zhang, Zheng; El-Moselhy, Tarek A.; Elfadel, Ibrahim M.; Daniel, Luca | en_US |
dspace.embargo.terms | N | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-5880-3151 | |
mit.license | OPEN_ACCESS_POLICY | en_US |