Novel algorithms for fast statistical analysis of scaled circuits
As VLSI technology moves to the nanometer scale for transistor feature sizes, the impact of manufacturing imperfections result in large variations in the circuit performance. Traditional CAD tools are not well-equipped to handle this scenario, since they do not model this statistical nature of the c...
Enregistré dans:
| Auteurs principaux: | , |
|---|---|
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
Dordrecht :
Springer Netherlands
2009.
Cham : Springer Nature |
| Collection: | Lecture Notes in Electrical Engineering
46 |
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Novel Algorithms for Fast Statistical Analysis of Scaled Circuits, Texte imprimé, 9789048130993 • Novel Algorithms for Fast Statistical Analysis of Scaled Circuits, Texte imprimé, 9789048131013 • Novel Algorithms for Fast Statistical Analysis of Scaled Circuits, Texte imprimé, 9789400736870 |
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| 100 | 1 | |a Singhee, Amith, |d 19..- | |
| 245 | 1 | 0 | |a Novel algorithms for fast statistical analysis of scaled circuits |c by Amith Singhee, Rob A. Rutenbar. |
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| 505 | 0 | |a SiLVR: Projection Pursuit for Response Surface Modeling -- Quasi-Monte Carlo for Fast Statistical Simulation of Circuits -- Statistical Blockade: Estimating Rare Event Statistics -- Concluding Observations. | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. chttps://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a As VLSI technology moves to the nanometer scale for transistor feature sizes, the impact of manufacturing imperfections result in large variations in the circuit performance. Traditional CAD tools are not well-equipped to handle this scenario, since they do not model this statistical nature of the circuit parameters and performances, or if they do, the existing techniques tend to be over-simplified or intractably slow. Novel Algorithms for Fast Statistical Analysis of Scaled Circuits draws upon ideas for attacking parallel problems in other technical fields, such as computational finance, machine learning and actuarial risk, and synthesizes them with innovative attacks for the problem domain of integrated circuits. The result is a set of novel solutions to problems of efficient statistical analysis of circuits in the nanometer regime. In particular, Novel Algorithms for Fast Statistical Analysis of Scaled Circuits makes three contributions: 1) SiLVR, a nonlinear response surface modeling and performance-driven dimensionality reduction strategy, that automatically captures the designer s insight into the circuit behavior, by extracting quantitative measures of relative global sensitivities and nonlinear correlation. 2) Fast Monte Carlo simulation of circuits using quasi-Monte Carlo, showing speedups of 2. to 50. over standard Monte Carlo. 3) Statistical blockade, an efficient method for sampling rare events and estimating their probability distribution using limit results from extreme value theory, applied to high replication circuits like SRAM cells. | ||
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| 776 | 0 | |t Novel Algorithms for Fast Statistical Analysis of Scaled Circuits |b Texte imprimé |z 9789400736870 | |
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