Stochastic behavioral modeling and analysis for analog/mixed-signal circuits
It has become increasingly challenging to model the stochastic behavior of analog/mixed-signal (AMS) circuits under large-scale process variations. In this paper, a novel moment-matching based method has been proposed to accurately extract the probabilistic behavioral distributions of AMS circuits....
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| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/95295 http://hdl.handle.net/10220/9241 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | It has become increasingly challenging to model the stochastic behavior of analog/mixed-signal (AMS) circuits under large-scale process variations. In this paper, a novel moment-matching based method has been proposed to accurately extract the probabilistic behavioral distributions of AMS circuits. This method first utilizes Latin Hypercube Sampling (LHS) coupling with a correlation control technique to generate a few samples (e.g., sample-size is in linear with number of variable parameters) and further analytically evaluate the high-order moments of the circuit behavior with high accuracy. In this way, the “arbitrary” probabilistic distributions of the circuit behavior can be extracted using moment-matching method. More importantly, the proposed method has been successfully applied to high-dimensional prob-lems with linear complexity. The experiments demonstrate that the proposed method can provide up to 1666X speedup over crude Monte Carlo method for the same accuracy. |
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