Advanced Field-Solver Techniques for RC Extraction of Integrated Circuits

Yu, Wenjian; Wang, Xiren

doi:10.1007/978-3-642-54298-5

Cited by 54 publications

(14 citation statements)

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“…We then consider an example about extracting the capacitance of conductors in an electrostatic system, which is an important problem in modern IC design for addressing the parasitic effects of interconnects . The problem is stated in Figure .…”

Section: Numerical Examplesmentioning

confidence: 99%

Three‐dimensional space variable–separated PGD in electrostatic field problems: A comparison between two implementations

Yan

Zong

et al. 2019

Int J Numerical Modelling

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Proper generalized decomposition (PGD) is a promising model order reduction (MOR) technique to solve partial differential equations (PDEs). It usually bases on an explicit variable-separated formulation of the problems to be solved. However, it can be expensive to derive the separated formulations. Also, the PGD process can become inefficient because of the massive separated terms.Another way of implementing PGD is based on direct integration. In this work, we illustrate this kind of implementation algebraically by introducing tensors to represent the operator and right-hand side of the problem. The separated formulation-based PGD and tensor-based PGD are compared in computational complexity and accuracy. The pros and cons of both approaches are discussed.The methods are applied in three-dimensional (3D) electrostatic field problems.

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Section: Numerical Examplesmentioning

confidence: 99%

Three‐dimensional space variable–separated PGD in electrostatic field problems: A comparison between two implementations

Yan

Zong

et al. 2019

Int J Numerical Modelling

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“…Known resistance extraction approaches are usually classified as either "exact" or heuristic [1] [4]. The first ones numerically solve the electromagnetic field equations (finite difference, finite element, boundary element, Monte Carlo methods) [5]. The resulting extraction is highly accurate but requires fine meshing of complex shaped interconnects, leading to heavy computations and increased memory consumption, and thus is impractical for fast analysis of large circuits.…”

Section: Introductionmentioning

confidence: 99%

A Parasitic Resistance Extraction Method for Early Analysis of Complex Shaped Power Delivery Networks

Malinauskas

2019

MES

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*-This work presents a novel method of resistances extraction from arbitrary shaped 2D polygonal interconnects. It includes a new approach to resistor network construction based on medial axis transform and a simple set of analytical formulas for resistances estimation. The extracted circuits are compact enough while naturally mappable onto the original complex layout. These properties are useful in early design stage power delivery modeling with voltage drop or equivalent resistance maps visualization. The method is implemented within the industrial power integrity analysis system and demonstrated high efficiency while keeping enough accuracy.

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“…This simple solution approach was further developed by many investigators in subsequent years. Apart from the standard RW, in which both step size and move directions are fixed and preassigned, two main random walk types were derived, namely semi floating random walk (step size is fixed, though the move direction is not limited, [47,52]) and full floating random walk (step size is not preassigned and changes at each step, whereas the move direction is not limited, [8,42,47,52]). Moreover, a continuous random walk procedure, minimizing the solution error has been proposed [17] along with the self-adaptive, grid-free algorithm, with improved solution smoothness and its application to diffusion equations [20].…”

Section: Introductionmentioning

confidence: 99%

A Matlab software for approximate solution of 2D elliptic problems by means of the meshless Monte Carlo random walk method

Milewski

2019

Numer Algor

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This paper is devoted to the development of an innovative Matlab software, dedicated to the numerical analysis of two-dimensional elliptic problems, by means of the probabilistic approach. This approach combines features of the Monte Carlo random walk method with discretization and approximation techniques, typical for meshless methods. It allows for determination of an approximate solution of elliptic equations at the specified point (or group of points), without a necessity to generate large system of equations for the entire problem domain. While the procedure is simple and fast, the final solution may suffer from both stochastic and discretization errors. The attached Matlab software is based on several original author's concepts. It permits the use of arbitrarily irregular clouds of nodes, non-homogeneous right-hand side functions, mixed type of boundary conditions as well as variable material coefficients (of anisotropic materials). The paper is illustrated with results of analysis of selected elliptic problems, obtained by means of this software. Keywords Monte Carlo method • Random walk technique • Meshless methods • Elliptic problems • Finite difference method • Implementation in Matlab

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Advanced Field-Solver Techniques for RC Extraction of Integrated Circuits

Cited by 54 publications

References 0 publications

Three‐dimensional space variable–separated PGD in electrostatic field problems: A comparison between two implementations

Three‐dimensional space variable–separated PGD in electrostatic field problems: A comparison between two implementations

A Parasitic Resistance Extraction Method for Early Analysis of Complex Shaped Power Delivery Networks

A Matlab software for approximate solution of 2D elliptic problems by means of the meshless Monte Carlo random walk method

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