Name
Title | ||
|---|---|---|
High-Dimensional and Multiple-Failure-Region Importance Sampling for SRAM Yield Analysis. |
Abstract | ||
|---|---|---|
The failure rate of static RAM (SRAM) cells is restricted to be extremely low to ensure sufficient high yield for the entire chip. In addition, multiple performances of interest and influences from peripherals make SRAM failure rate estimation a high-dimensional multiple-failure-region problem. This paper proposes a new method featuring a multistart-point sequential quadratic programming (SQP) fra... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TVLSI.2016.2601606 | IEEE Transactions on Very Large Scale Integration (VLSI) Systems |
Keywords | Field | DocType |
Random access memory,Computational modeling,Adaptation models,Monte Carlo methods,Probability density function,Random variables,Estimation | Importance sampling,Computer science,Algorithm,Failure rate,Electronic engineering,Curse of dimensionality,Static random-access memory,Gaussian,Sampling (statistics),Process variation,Sequential quadratic programming | Journal |
Volume | Issue | ISSN |
25 | 3 | 1063-8210 |
Citations | PageRank | References |
4 | 0.44 | 18 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mengshuo Wang | 1 | 21 | 2.23 |
| Changhao Yan | 2 | 27 | 6.64 |
| Xin Li | 3 | 530 | 60.02 |
| Dian Zhou | 4 | 260 | 56.14 |
| Xuan Zeng | 5 | 408 | 75.96 |