An efficient nonlinear circuit simulation technique

This paper proposes a new and efficient approach for the analysis and simulation of circuits subject to input signals with widely separated rates of variation. Such signals arise in communication circuits when an RF carrier is modulated by a low-frequency information signal. The proposed technique initially involves converting the ordinary differential equation system, that describes the nonlinear circuit, to a partial differential equation system. The resultant system is then semidiscretised using a multiresolution collocation scheme, involving cubic spline wavelet decomposition. A reduced equation system is subsequently formed, using a nonlinear model reduction strategy. This enables an efficient solution process using trapezoidal numerical integration. Results highlight the efficacy of the proposed approach

An efficient wavelet-based nonlinear circuit simulation technique with model order reduction

This paper proposes further improvement to a novel method for the analysis and simulation of ICs recently proposed by the authors. The circuits are assumed to be subjected to input signals that have widely separated rates of variation, e.g. in communication systems an RF carrier modulated by a low-frequency information signal. The previously proposed technique enables the reuse of the results obtained using a lower-order accuracy model to calculate a response of higher-order accuracy model. In this paper, the efficiency of this method is further improved by using a nonlinear model order reduction technique. Results highlight the efficiency of the proposed approach

An efficient steady-state analysis of the eddy current problem using a parallel-in-time algorithm

This paper introduces a parallel-in-time algorithm for efficient steady-state solution of the eddy current problem. Its main idea is based on the application of the well-known multi-harmonic (or harmonic balance) approach as the coarse solver within the periodic parallel-in-time framework. A frequency domain representation allows for the separate calculation of each harmonic component in parallel and therefore accelerates the solution of the time-periodic system. The presented approach is verified for a nonlinear coaxial cable model

A novel envelope simulation technique for high-frequency nonlinear circuits

The paper proposes a new approach for the analysis and simulation of circuits subject to input signals with widely separated rates of variation. Such signals arise in communication circuits when an RF carrier is modulated by a low-frequency information signal. The approach will involve converting the ordinary differential equation system that describes the circuit to a partial differential equation system and subsequently solving the resultant system using a multiresolution collocation approach involving a cubic spline wavelet-based decomposition

An efficient nonlinear circuit simulation technique

This paper proposes a novel method for the analysis and simulation of integrated circuits (ICs) with the potential to greatly shorten the IC design cycle. The circuits are assumed to be subjected to input signals that have widely separated rates of variation, e.g., in communication systems, an RF carrier modulated by a low-frequency information signal. The proposed technique involves two stages. Initially, a particular order result for the circuit response is obtained using a multiresolution collocation scheme involving cubic spline wavelet decomposition. A more accurate solution is then obtained by adding another layer to the wavelet series approximation. However, the novel technique presented here enables the reuse of results acquired in the first stage to obtain the second-stage result. Therefore, vast gains in efficiency are obtained. Furthermore, a nonlinear model-order reduction technique can readily be used in both stages making the calculations even more efficient. Results will highlight the efficacy of the proposed approac

Tensor Computation: A New Framework for High-Dimensional Problems in EDA

Many critical EDA problems suffer from the curse of dimensionality, i.e. the very fast-scaling computational burden produced by large number of parameters and/or unknown variables. This phenomenon may be caused by multiple spatial or temporal factors (e.g. 3-D field solvers discretizations and multi-rate circuit simulation), nonlinearity of devices and circuits, large number of design or optimization parameters (e.g. full-chip routing/placement and circuit sizing), or extensive process variations (e.g. variability/reliability analysis and design for manufacturability). The computational challenges generated by such high dimensional problems are generally hard to handle efficiently with traditional EDA core algorithms that are based on matrix and vector computation. This paper presents "tensor computation" as an alternative general framework for the development of efficient EDA algorithms and tools. A tensor is a high-dimensional generalization of a matrix and a vector, and is a natural choice for both storing and solving efficiently high-dimensional EDA problems. This paper gives a basic tutorial on tensors, demonstrates some recent examples of EDA applications (e.g., nonlinear circuit modeling and high-dimensional uncertainty quantification), and suggests further open EDA problems where the use of tensor computation could be of advantage.Comment: 14 figures. Accepted by IEEE Trans. CAD of Integrated Circuits and System