Statistical Modeling with the Virtual Source MOSFET Model
A statistical extension of the ultra-compact Virtual Source (VS) MOSFET model is developed here for the first time. The characterization uses a statistical extraction technique based on the backward propagation of variance (BPV) with variability parameters derived directly from the nominal VS model....
| Main Authors: | , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2014
|
| Online Access: | http://hdl.handle.net/1721.1/92428 https://orcid.org/0000-0002-4836-6525 https://orcid.org/0000-0002-0417-445X |
| _version_ | 1826199787369660416 |
|---|---|
| author | Yu, Li Wei, Lan Elfadel, Ibrahim M. Antoniadis, Dimitri A. Boning, Duane S. |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Yu, Li Wei, Lan Elfadel, Ibrahim M. Antoniadis, Dimitri A. Boning, Duane S. |
| author_sort | Yu, Li |
| collection | MIT |
| description | A statistical extension of the ultra-compact Virtual Source (VS) MOSFET model is developed here for the first time. The characterization uses a statistical extraction technique based on the backward propagation of variance (BPV) with variability parameters derived directly from the nominal VS model. The resulting statistical VS model is extensively validated using Monte Carlo simulations, and the statistical distributions of several figures of merit for logic and memory cells are compared with those of a BSIM model from a 40-nm CMOS industrial design kit. The comparisons show almost identical distributions with distinct run time advantages for the statistical VS model. Additional simulations show that the statistical VS model accurately captures non-Gaussian features that are important for low-power designs. |
| first_indexed | 2024-09-23T11:25:46Z |
| format | Article |
| id | mit-1721.1/92428 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:25:46Z |
| publishDate | 2014 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/924282022-09-27T19:26:57Z Statistical Modeling with the Virtual Source MOSFET Model Yu, Li Wei, Lan Elfadel, Ibrahim M. Antoniadis, Dimitri A. Boning, Duane S. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Microsystems Technology Laboratories Boning, Duane S. Yu, Li Wei, Lan Antoniadis, Dimitri A. Boning, Duane S. A statistical extension of the ultra-compact Virtual Source (VS) MOSFET model is developed here for the first time. The characterization uses a statistical extraction technique based on the backward propagation of variance (BPV) with variability parameters derived directly from the nominal VS model. The resulting statistical VS model is extensively validated using Monte Carlo simulations, and the statistical distributions of several figures of merit for logic and memory cells are compared with those of a BSIM model from a 40-nm CMOS industrial design kit. The comparisons show almost identical distributions with distinct run time advantages for the statistical VS model. Additional simulations show that the statistical VS model accurately captures non-Gaussian features that are important for low-power designs. Masdar Institute of Science and Technology 2014-12-22T14:56:47Z 2014-12-22T14:56:47Z 2013-03 Article http://purl.org/eprint/type/ConferencePaper 9781467350716 1530-1591 http://hdl.handle.net/1721.1/92428 Yu, Li, Lan Wei, Dimitri Antoniadis, Ibrahim Elfadel, and Duane Boning. “Statistical Modeling with the Virtual Source MOSFET Model.” Design, Automation & Test in Europe Conference & Exhibition (DATE), 2013 (2013). https://orcid.org/0000-0002-4836-6525 https://orcid.org/0000-0002-0417-445X en_US http://dx.doi.org/10.7873/DATE.2013.296 Proceedings of the Design, Automation & Test in Europe Conference & Exhibition (DATE), 2013 Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) Boning |
| spellingShingle | Yu, Li Wei, Lan Elfadel, Ibrahim M. Antoniadis, Dimitri A. Boning, Duane S. Statistical Modeling with the Virtual Source MOSFET Model |
| title | Statistical Modeling with the Virtual Source MOSFET Model |
| title_full | Statistical Modeling with the Virtual Source MOSFET Model |
| title_fullStr | Statistical Modeling with the Virtual Source MOSFET Model |
| title_full_unstemmed | Statistical Modeling with the Virtual Source MOSFET Model |
| title_short | Statistical Modeling with the Virtual Source MOSFET Model |
| title_sort | statistical modeling with the virtual source mosfet model |
| url | http://hdl.handle.net/1721.1/92428 https://orcid.org/0000-0002-4836-6525 https://orcid.org/0000-0002-0417-445X |
| work_keys_str_mv | AT yuli statisticalmodelingwiththevirtualsourcemosfetmodel AT weilan statisticalmodelingwiththevirtualsourcemosfetmodel AT elfadelibrahimm statisticalmodelingwiththevirtualsourcemosfetmodel AT antoniadisdimitria statisticalmodelingwiththevirtualsourcemosfetmodel AT boningduanes statisticalmodelingwiththevirtualsourcemosfetmodel |