STAC: statistical timing analysis with correlation
Proceedings of the 41st annual Design Automation Conference
Statistical Timing Analysis Considering Spatial Correlations using a Single Pert-Like Traversal
Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design
Robust extraction of spatial correlation
Proceedings of the 2006 international symposium on Physical design
ICCAD '05 Proceedings of the 2005 IEEE/ACM International conference on Computer-aided design
Proceedings of the 46th Annual Design Automation Conference
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
On confidence in characterization and application of variation models
Proceedings of the 2010 Asia and South Pacific Design Automation Conference
Hybrid modeling of non-stationary process variations
Proceedings of the 48th Design Automation Conference
Design and Analysis of a Robust Carbon Nanotube-Based Asynchronous Primitive Circuit
ACM Journal on Emerging Technologies in Computing Systems (JETC)
| Hi-index | 0.00 |
With the significant advancement of statistical timing and yield analysis algorithms, there is a strong need for accurate and analytical spatial correlation models. In this paper, we propose a novel spatial correlation modeling method not only can capture the general spatial correlation relationship but also can generate highly accurate and analytical models. Our method, based on Singular Value Decomposition (SVD), can generate sequences of polynomial weighted by the singular values. Experimental results from foundry measurement data show that our proposed approach is 5X accuracy improvement over several distance based spatial correlation modeling methods.