Variability in process parameters is making accurate timing analysis of nano-scale integrated circuits an extremely challenging task. In this paper, we propose a new algorithm for...
Statistical static timing analysis (SSTA) is emerging as a solution for predicting the timing characteristics of digital circuits under process variability. For computing the stat...
Kaviraj Chopra, Bo Zhai, David Blaauw, Dennis Sylv...
Recently, a novel Log-Euclidean Riemannian metric [28] is proposed for statistics on symmetric positive definite (SPD) matrices. Under this metric, distances and Riemannian means ...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
Current source based cell models are becoming a necessity for accurate timing and noise analysis at 65nm and below. Voltage waveform shapes are increasingly more difficult to repr...
We propose a scalable and efficient parameterized block-based statistical static timing analysis algorithm incorporating both Gaussian and non-Gaussian parameter distributions, ca...