Analog circuit simulation using range arithmetics

Grabowski,; Olbrich,; Barke,

doi:10.1109/aspdac.2008.4484053

Cited by 32 publications

(18 citation statements)

References 12 publications

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“…Beside system level analog circuits can also be simulated on lower level like transistor level. For this purpose, a semisymbolic circuit simulator has been developed [37]. Circuit simulation is performed in two steps.…”

Section: Semisymbolic Simulation On System and Circuit Levelmentioning

confidence: 99%

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Verification of Mixed-Signal Systems with Affine Arithmetic Assertions

et al. 2013

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Embedded systems include an increasing share of analog/mixed-signal components that are tightly interwoven with functionality of digital HW/SW systems. A challenge for verification is that even small deviations in analog components can lead to significant changes in system properties. In this paper we propose the combination of range-based, semisymbolic simulation with assertion checking. We show that this approach combines advantages, but as well some limitations, of multirun simulations with formal techniques. The efficiency of the proposed method is demonstrated by several examples.

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Section: Semisymbolic Simulation On System and Circuit Levelmentioning

confidence: 99%

“…(2) The equation system is passed through a numerical equation solver which performs DC, AC, and Transient Analysis [37]. The solver uses numerical methods as forward, backward Euler or trapezoidal methods to solve the equations.…”

Section: Semisymbolic Simulation On System and Circuit Levelmentioning

confidence: 99%

Verification of Mixed-Signal Systems with Affine Arithmetic Assertions

et al. 2013

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“…An algorithm to solve implicit equations with uncertain parameters using affine arithmetic was described in [3,4]. In Fig.…”

Section: Preliminariesmentioning

confidence: 99%

“…With decreasing structure sizes in microelectronics the influence of parameter deviations on the behaviour of analog circuits increases. An algorithm to solve implicit equations using affine arithmetic was proposed in [3,4]. This method is limited in its convergence range.…”

Section: Introductionmentioning

confidence: 99%

Split and Merge Strategies for Solving Uncertain Equations Using Affine Arithmetic

Scharf¹,

Olbrich²,

Barke³

2015

Proceedings of the Eighth EAI International Conference on Simulation Tools and Techniques

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The behaviour of systems is determined by various parameters. Due to several reasons like e. g. manufacturing tolerances these parameters can have some uncertainties. Corner Case and Monte Carlo simulations are well known approaches to handle uncertain systems. They sample the corners and random points of the parameter space, respectively. Both require many runs and do not guarantee the inclusion of the worst case. As alternatives, range based approaches can be used. They model parameter uncertainties as ranges. The simulation outputs are ranges which include all possible results created by the parameter uncertainties. One type of range arithmetic is the affine arithmetic, which allows to maintain linear correlations to avoid over-approximation. An equation solver based on affine arithmetic has been proposed earlier. Unlike many other range based approaches it can solve implicit non-linear equations. This is necessary for analog circuit simulation. For large uncertainties the solver suffers from convergence problems. To overcome these problems it is possible to split the parameter ranges, calculate the solutions separately and merge them again. For higher dimensional systems this leads to excessive runtimes as each parameter is split. To minimize the additional runtime several split and merge strategies are proposed and compared using two analog circuit examples.

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“…Simulations based on range arithmetic promise reduced simulation time at the expense of pessimistic results. This approach (2) presents a new field entered by the application of affine arithmetic in circuit simulation [7]- [9]. Design aids for integrated circuits based on probabilistic affine forms have already been presented in [10], [11].…”

Section: Transistor Level Simulation With Parameter Uncertaintiesmentioning

confidence: 99%

Formal approaches to analog circuit verification

Barke

Grabowski

Graeb

et al. 2009

2009 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition

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Abstract-For a speed-up of analog design cycles to keep up with the continuously decreasing time to market, iterative design refinement and redesigns are more than ever regarded as showstoppers. To deal with this issue, referred to as design and verification gap, the development of a continuous and consistent verification is mandatory. In digital design, formal verification methods are considered as a key technology for efficient design flows. However, industrial availability of formal methods for analog circuit verification is still negligible despite a growing need. In recent years, research institutions have made considerable advances in the area of formal verification of analog circuits. This paper presents a selection of four recent approaches in analog verification that cover a broad scope of verification philosophies.

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Analog circuit simulation using range arithmetics

Cited by 32 publications

References 12 publications

Verification of Mixed-Signal Systems with Affine Arithmetic Assertions

Verification of Mixed-Signal Systems with Affine Arithmetic Assertions

Split and Merge Strategies for Solving Uncertain Equations Using Affine Arithmetic

Formal approaches to analog circuit verification

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