Generalized nonlinear timing/phase macromodeling: Theory, numerical methods and applications

Gu, Chenjie; Roychowdhury, Jaijeet

doi:10.1109/iccad.2010.5654174

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…Efforts such as [32,21,33,34] have been made to advance the modeling techniques. In this work, we focus on the techniques that consider parasitic effects.…”

Section: Related Prior Researchmentioning

confidence: 99%

iVAMS 1.0: Polynomial-Metamodel-Integrated Intelligent Verilog-AMS for Fast, Accurate Mixed-Signal Design Optimization

Mohanty,

Kougianos

2019

Preprint

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Electronic circuit behavioral models built with hardware description/modeling languages such as Verilog-AMS for system-level simulations are typically functional models. They do not capture the physical design (layout) information of the target design. Thus, their applications are limited to early design feasibility studies and/or pre-layout functional verification. Numerous iterations of post-layout design adjustments are usually required to ensure that design specifications are met with the presence of layout parasitics. In this paper a paradigm shift of the current trend is presented that integrates layout-level information (with full parasitics) in Verilog-AMS through metamodels such that systemlevel simulation of a mixed-signal circuit/system is realistic and as accurate as true parasitic netlist simulation. The simulations performed with these parasitic-aware models can be used to estimate system performance without layout iterations. We call this new form of Verilog-AMS as iVAMS (i.e. Intelligent Verilog-AMS). We call this iVAMS 1.0 as it is simple polynomial-metamodel integrated Intelligent Verilog-AMS. As a specific case study, a voltage-controlled oscillator (VCO) Verilog-AMS behavioral model and design flow are proposed to assist fast PLL design space exploration. The PLL simulation employing quadratic metamodels achieves approximately 10× speedup compared to that employing the layout extracted, parasitic netlist. The simulations using this behavioral model attain high accuracy. The observed error for the simulated lock time and average power dissipation are 0.7 % and 3 %, respectively. This behavioral metamodel approach bridges the gap between layout-accurate but fast simulation and design space exploration. The proposed method also allows much shorter design verification and optimization to meet stringent time-to-market requirements. In the PLL optimization case study, 46 % PLL power reduction was achieved using a differential evolution algorithm and the proposed layout-accurate behavioral model. Compared to the optimization using the layout netlist, the runtime using the behavioral model is reduced by 88.9 %. To the best of the authors' knowledge this is the first approach that brings layout-level accuracy to system-level design exploration and is applied towards mixed-signal design exploration.

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“…Efforts such as [32,21,33,34] have been made to advance the modeling techniques. In this work, we focus on the techniques that consider parasitic effects.…”

Section: Related Prior Researchmentioning

confidence: 99%

iVAMS 1.0: Polynomial-Metamodel-Integrated Intelligent Verilog-AMS for Fast, Accurate Mixed-Signal Design Optimization

Mohanty,

Kougianos

2019

Preprint

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“…Macromodeling has been extensively applied in circuit timing analysis [1,2], power analysis and estimation [3], process variation analysis, etc. This paper proposes a statistically optimal macromodeling framework and applies it to the design, analysis, and verification of MicroElectroMechanical System (MEMS) devices.…”

Section: Introductionmentioning

confidence: 99%

A statistically optimal macromodeling framework with application in process variation analysis of MEMS devices

2012

10th IEEE International NEWCAS Conference

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Macromodels are used extensively in circuit and process analysis for higher computation efficiency, and better insight into system behaviors. A statistically optimal and elegant framework for macromodeling is proposed in this paper, which can successfully handle the modeling challenges created by the highly customized fabrication/design paradigm of MEMS devices. Without requirements for a priori knowledge and experience of fast emerging and highly diversified MEMS fabrication and design style, the proposed framework can adapt to arbitrary distribution and correlation by optimally scaling the order and dimension of the process variation models for trade-off between accuracy and efficiency. The effectiveness of the proposed framework is demonstrated by process variation modeling and analysis of MEMS devices.

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Algorithmic nonlinear macromodeling: Challenges, solutions and applications in Analog/Mixed-Signal validation

2013

Proceedings of the IEEE 2013 Custom Integrated Circuits Conference

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Generalized nonlinear timing/phase macromodeling: Theory, numerical methods and applications

Cited by 3 publications

References 13 publications

iVAMS 1.0: Polynomial-Metamodel-Integrated Intelligent Verilog-AMS for Fast, Accurate Mixed-Signal Design Optimization

iVAMS 1.0: Polynomial-Metamodel-Integrated Intelligent Verilog-AMS for Fast, Accurate Mixed-Signal Design Optimization

A statistically optimal macromodeling framework with application in process variation analysis of MEMS devices

Algorithmic nonlinear macromodeling: Challenges, solutions and applications in Analog/Mixed-Signal validation

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