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Content Provider | IEEE Xplore Digital Library |
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Author | Liu, F. |
Copyright Year | 2007 |
Description | Author affiliation: IBM Austin Res. Lab, Austin (Liu, F.) |
Abstract | The dynamic behavior of a VLSI circuit can be described by a system of differential-algebraic equations. When some circuit elements are affected by process variations, the dynamic behavior of the circuit will deviate from its nominal trajectory. Monte-Carlo-type random sampling methods are widely used to estimate the trajectory deviation. However they can be quite time-consuming when the dimension of the parameter space is large. This paper offers an alternative solution by casting the problem into the theoretic frame work of non-linear non-Gaussian filtering. To estimate the mean and variance of the time-dependent circuit trajectory, we develop a method based on unscented transformation, which is an efficient Bayesian analysis sampling technique. Theoretically the method has linear runtime complexity. Experimental results show that compared to traditional Monte-Carlo methods, the new method can achieve over 10times speedup with less than 2% error. |
Starting Page | 719 |
Ending Page | 724 |
File Size | 878982 |
Page Count | 6 |
File Format | |
ISBN | 9781424413812 |
ISSN | 10923152 |
DOI | 10.1109/ICCAD.2007.4397350 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2007-11-04 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Circuit simulation Sampling methods Circuit optimization Bayesian methods SPICE Statistics Differential equations Casting Runtime Voltage |
Content Type | Text |
Resource Type | Article |
Subject | Computer Graphics and Computer-Aided Design Computer Science Applications Software |
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