Abstract
As technology scales to smaller dimensions, increasing process variations and coupling induced delay variations make timing verification extremely challenging. In this paper, the authors establish a theoretical framework for statistical timing analysis with coupling. They prove the convergence of their proposed iterative approach and discuss implementation issues under the assumption of a Gaussian distribution for the parameters of variation. A statistical timer based on their proposed approach is developed and experimental results are presented for the International Symposium on Circuits and Systems benchmarks. They juxtapose their timer with a single pass, noniterative statistical timer that does not consider the mutual dependence of coupling with timing, and another statistical timer that handles coupling deterministically. Monte Carlo simulations reveal a distinct gain (up to 24%) in accuracy by their approach in comparison to the others mentioned.
Original language | English (US) |
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Pages (from-to) | 2965-2974 |
Number of pages | 10 |
Journal | IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems |
Volume | 25 |
Issue number | 12 |
DOIs | |
State | Published - Dec 2006 |
Funding
Dr. Zhou served on the technical program committees of many conferences on very large scale integrated circuits and computer-aided design. He is a recipient of the CAREER Award from the National Science Foundation in 2003. Manuscript received July 20, 2005; revised January 10, 2006. This work was supported by the National Science Foundation under Grant CCR-0238484. This paper was presented in part at the International Conference on Computer-Aided Design, 2005 [1]. This paper was recommended by Associate Editor F. N. Najm.
Keywords
- Coupling
- Fixpoint computation
- Statistical timing analysis
- Variability
- Very large scale integration (VLSI)
ASJC Scopus subject areas
- Software
- Computer Graphics and Computer-Aided Design
- Electrical and Electronic Engineering