This book presents a new methodology with reduced time impact to address the problem of analog integrated circuit (IC) yield estimation by means of Monte Carlo (MC) analysis, inside an optimization loop of a population-based algorithm. The low time impact on the overall optimization processes enables IC designers to perform yield optimization with the most accurate yield estimation method, MC simulations using foundry statistical device models considering local and global variations. The methodology described by the authors delivers on average a reduction of 89% in the total number of MC simulations, when compared to the exhaustive MC analysis over the full population. In addition to describing a newly developed yield estimation technique, the authors also provide detailed background on automatic analog IC sizing and optimization.
| Autorius: | António Manuel Lourenço Canelas, Nuno Cavaco Gomes Horta, Jorge Manuel Correia Guilherme, |
| Leidėjas: | Springer Nature Switzerland |
| Išleidimo metai: | 2021 |
| Knygos puslapių skaičius: | 264 |
| ISBN-10: | 3030415384 |
| ISBN-13: | 9783030415389 |
| Formatas: | 235 x 155 x 15 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Yield-Aware Analog IC Design and Optimization in Nanometer-scale Technologies“
