Passive Model Order Reduction Research Articles

Krylov subspace method for passive reduced‐order modelling of electrical networks

This study presents a two-stage method to compute the passive reduced-order models of multi-input multi-output electrical networks containing distributed-parameter transmission lines (TLs). The method is based on the discretised TL models and a Krylov subspace model-order reduction method called passive reduced-order interconnect macromodelling algorithm. The section numbers of the TLs are adaptively determined using an innovative and fast algorithm. In stage 1, the high-order cascaded Π circuit models of the TLs are reduced and synthesised into low-order RLC two ports; stage 2 further reduces the entire lumped network. System passivity is preserved during the reduction. Useful postprocesses and a practical passivity test technique are given. Numerical tests confirm the superiority of the proposed method in reliable passivity preservation with decent accuracy and efficiency.

Passivity-Preserving Parameterized Model Order Reduction Using Singular Values and Matrix Interpolation

We present a parameterized model order reduction method based on singular values and matrix interpolation. First, a fast technique using grammians is utilized to estimate the reduced order, and then common projection matrices are used to build parameterized reduced order models (ROMs). The design space is divided into cells, and a Krylov subspace is computed for each cell vertex model. The truncation of the singular values of the merged Krylov subspaces from the models located at the vertices of each cell yields a common projection matrix per design space cell. Finally, the reduced system matrices are interpolated using positive interpolation schemes to obtain a guaranteed passive parameterized ROM. Pertinent numerical results validate the proposed technique.

Decentralized and Passive Model Order Reduction of Linear Networks With Massive Ports

It is well known that model order reduction for circuits with many terminals remains a challenging problem. One reason is that existing approaches are based on a centralized framework, in which each input-output pair is implicitly assumed to be equally interacted and the matrix-valued transfer function is assumed to be fully populated. In this paper, we attempt to address this long-standing problem using a decentralized model order reduction scheme, in which a multi-input multi-output system is decoupled into a number of subsystems and each subsystem corresponds to one output and several dominant inputs. The decoupling process is based on the relative gain array, which measures the degree of interaction of each input-output pair. For each decoupled subsystem, passive reduction can be easily achieved using existing reduction techniques. The proposed method is suitable for resistance-dominant interconnects such as on-chip power grids, substrate planes where extremely compact models can be obtained. Simulation results demonstrate the advantage of the proposed method compared to the existing approaches.

Circuit-Based Analysis of Electromagnetic Field Coupling With Nonuniform Transmission Lines

This paper presents a new algorithm for simulating electromagnetic (EM) field coupling with nonuniform multiconductor transmission lines in a circuit simulation environment. The proposed algorithm is based on the concept of passive model-order reduction, whereby an algorithmically developed passive reduced-order model, coupled with a set of equivalent sources representing the incident filed, are shown to accurately capture the behavior of the transmission line under EM excitation. The reduced-order model is developed independently from the particular shape of the incident field pulse, in the sense that, in constructing the model, one does not need prior knowledge about the waveform of the incident pulse of the EM field. In addition, it is also shown that the model developed can be used to simulate the transmission line in the absence of the EM field. The derived equivalent sources, representing the field coupling, are given directly in the time domain, thereby making simulation under nonlinear circuit terminations an easy task. Although the proposed work is aimed mainly at simulating nonuniform transmission lines, it can be applied to uniform lines as a special case. The proposed algorithm has been validated numerically with several examples.

TermMerg: An Efficient Terminal-Reduction Method for Interconnect Circuits

In this paper, a novel method to efficiently reduce the terminal number of general linear-interconnect circuits with a large number of input or output terminals considering delay uncertainty is proposed. Our new algorithm is motivated by the fact that terminal reduction can lead to a more compact order-reduced model and the observation that very large-scale integration interconnect circuits have many similar terminals in terms of their timing and delay metrics due to their closeness in structure or due to the mathematical discretization using meshing in finite-difference or finite-element scheme during the extraction process. The new method, called TermMerg ( Proc. ICCAD, p. 821, 2005), is based on the moments of the circuits as the metrics for the timing or delay. It then employs a singular-value-decomposition (SVD) method to determine the best number of clusters based on the low-rank approximation. After this, the -means clustering algorithm is used to cluster the moments of the terminals into the different clusters. The proposed method can work with any passive-model order reduction and ensure the passive models. In contrast, we show that singular value decomposition model order reduction (SVDMOR) does not generate passive models in general. Passivity enforcement in SVDMOR will significantly hamper the terminal-reduction effectiveness. Experimental results on a number of real industry interconnect circuits demonstrate the effectiveness of the proposed method and show also that the proposed method is more accurate than SVDMOR when the used moment matrix does not give good terminal correlations.

Identification of broadband passive macromodels for electromagnetic structures

PurposeThe paper aims to present an overview of techniques for the identification in the frequency domain of reduced order models for distributed passive electromagnetic structures.Design/methodology/approachMost known approaches proposed in different application contexts are described within a unified framework.FindingsA passive reduced order model of an unshielded twisted pair is fully developed with the combination of vector fitting algorithm and the passivity enforcement via Hamiltonian perturbation.Originality/valueA state‐of‐the‐art picture of the frequency domain identification and passivity enforcement techniques is given, and a test case of actual interest fully analysed.

Nonlinear semidefinite programming: sensitivity, convergence, and an application in passive reduced-order modeling

We consider the solution of nonlinear programs with nonlinear semidefiniteness constraints. The need for an efficient exploitation of the cone of positive semidefinite matrices makes the solution of such nonlinear semidefinite programs more complicated than the solution of standard nonlinear programs. This paper studies a sequential semidefinite programming (SSP) method, which is a generalization of the well-known sequential quadratic programming method for standard nonlinear programs. We present a sensitivity result for nonlinear semidefinite programs, and then based on this result, we give a self-contained proof of local quadratic convergence of the SSP method. We also describe a class of nonlinear semidefinite programs that arise in passive reduced-order modeling, and we report results of some numerical experiments with the SSP method applied to problems in that class.

Wideband passive multiport model order reduction and realization of RLCM circuits

This paper presents a novel compact passive modeling technique for high-performance RF passive and interconnect circuits modeled as high-order resistor-inductor-capacitor-mutual inductance circuits. The new method is based on a recently proposed general s-domain hierarchical modeling and analysis method and vector potential equivalent circuit model for self and mutual inductances. Theoretically, this paper shows that s-domain hierarchical reduction is equivalent to implicit moment matching at around s=0 and that the existing hierarchical reduction method by one-point expansion is numerically stable for general tree-structured circuits. It is also shown that hierarchical reduction preserves the reciprocity of passive circuit matrices. Practically, a hierarchical multipoint reduction scheme to obtain accurate-order reduced admittance matrices of general passive circuits is proposed. A novel explicit waveform-matching algorithm is proposed for searching dominant poles and residues from different expansion points based on the unique hierarchical reduction framework. To enforce passivity, state-space-based optimization is applied to the model order reduced admittance matrix. Then, a general multiport network realization method to realize the passivity-enforced reduced admittance based on the relaxed one-port network synthesis technique using Foster's canonical form is proposed. The resulting modeling algorithm can generate the multiport passive SPICE-compatible model for any linear passive network with easily controlled model accuracy and complexity. Experimental results on an RF spiral inductor and a number of high-speed transmission line circuits are presented. In comparison with other approaches, the proposed reduction is as accurate as passive reduced-order interconnect macromodeling algorithm in the high-frequency domain due to the enhanced multipoint expansion, but leads to smaller realized circuit models. In addition, under the same reduction ratio, realized models by the new method have less error compared with reduced circuits by time-constant-based reduction techniques in time domain.

HiPRIME: hierarchical and passivity preserved interconnect macromodeling engine for RLKC power delivery

This paper proposes a general hierarchical analysis methodology, HiPRIME, to efficiently analyze RLKC power delivery systems. After partitioning the circuits into blocks, we develop and apply the IEKS (Improved Extended Krylov Subspace) method to build the multiport Norton equivalent circuits which transform all the internal sources to Norton current sources at ports. Since there are no active elements inside the Norton circuits, passive or realizable model order reduction techniques such as PRIMA can be applied. The significant speed improvement, 700 times faster than Spice with less than 0.2% error and 7 times faster than a state-of-the-art solver, InductWise, is observed. To further reduce the top-level hierarchy runtime, we develop a second-level model reduction algorithm and prove its passivity.

Simulation and sensitivity analysis of nonuniform transmission lines using integrated congruence transform

This paper presents a new algorithm for computing sensitivity information of nonuniform multiconductor transmission lines with respect to arbitrary physical parameters. The proposed algorithm provides sensitivity information through a reduced-order system that has a simple representation in the time-domain. This feature enables computing sensitivity in the presence of nonlinear terminations. The proposed algorithm is based on the concept of passive model-order reduction using integrated congruence transform. It also addresses the problem of sensitivity analysis for nonuniform multiconductor transmission lines without having to resort to any discretization techniques

Generating Compact, Guaranteed Passive Reduced-Order Models of 3-D RLC Interconnects

As very large scale integration (VLSI) circuit speeds and density continue to increase, the need to accurately model the effects of three-dimensional (3-D) interconnects has become essential for reliable chip and system design and verification. Since such models are commonly used inside standard circuit simulators for time or frequency domain computations, it is imperative that they be kept compact without compromising accuracy, and also retain relevant physical properties of the original system, such as passivity. In this paper, we describe an approach to generate accurate, compact, and guaranteed passive models of RLC interconnects and packaging structures. The procedure is based on a partial element equivalent circuit (PEEC)-like approach to modeling the impedance of interconnect structures accounting for both the charge accumulation on the surface of conductors and the current traveling in their interior. The resulting formulation, based on nodal or mixed nodal and mesh analysis, enables the application of existing model order reduction techniques. Compactness and passivity of the model are then ensured with a two-step reduction procedure where Krylov-subspace moment-matching methods are followed by a recently proposed, nearly optimal, passive truncated balanced realization-like algorithm. The proposed approach was used for extracting passive models for several industrial examples, whose accuracy was validated both in the frequency domain as well as against measured time-domain data.

Passive Reduction Algorithm for RLC Interconnect Circuits With Embedded State-Space Systems (PRESS)

With the increasing operating frequencies and functionality in modern designs, the resulting size of circuit equations of high-frequency interconnect and microwave subnetworks are becoming large. Model-order reduction-based algorithms were recently suggested to handle the solution complexity of such circuits. The major objectives in state-of-the-art model-reduction algorithms are: 1) achieving accurate and compact models; 2) numerically stable and efficient generation of models; and 3) preservation of system properties such as passivity. Algorithms such as PRIMA generate guaranteed passive reduced-order models for large interconnect circuits described by RLC type of circuits. However, with the diverse technologies and complex geometries, it is becoming prevalent to describe some of the embedded linear modules in terms of state-space equations. In this paper, we show how to extend the scope of PRIMA-type first-level reduction algorithms for simultaneous reduction of combined circuits containing both RLC interconnects and embedded modules described by general passive state-space equations, while preserving the passivity of the resulting reduced-order model. Necessary formulation, proof of macromodel passivity, and validation examples are given.

Finite element‐based model order reduction of electromagnetic devices

AbstractIn this paper an efficient algorithm is presented for the development of compact and passive macro‐models of electromagnetic devices through the systematic reduction of the order of discrete models for these devices obtained through the use of finite elements. The proposed methodology is founded on a new finite element formulation that casts Maxwell's curl equations in a state‐space form. Such state‐space representations are very compatible with a class of robust model order reduction techniques based on Krylov subspaces. However, the advantage of this compatibility appears to be hindered by the fact that the state matrix of the discretized Maxwellian system is of dimension almost twice that obtained from the finite element approximation of the electromagnetic vector wave equation. It is shown in this paper that the apparent penalty in both memory and computation efficiency can be avoided by a proper selection of the finite element expansion functions used for the discretization of the electromagnetic fields. More specifically, it is shown that the proper selection of expansion functions renders the state‐space form of the Maxwellian system equivalent to the discrete problem obtained from the approximation of the vector wave equation using tangentially continuous vector finite elements. This equivalence is then used to effect Krylov‐based model order reduction directly from the finite element approximation of the vector wave equation. In particular, a passive model order reduction algorithm is used for this purpose. The proposed reduced order macro‐modelling algorithm is demonstrated through its application to a variety of microwave passive components. Copyright © 2002 John Wiley & Sons, Ltd.

MOMCO: method of moment components for passive model order reduction of RLCG interconnects

We introduce a new concept called moment components and a new method based on it to obtain passive reduced-order models of interconnect networks. In this method, the impedance matrix moments of the interconnect network are partitioned into their inductive, capacitive and mixed inductive/capacitive moment components. The method of moment components is described in a formal manner using analysis and synthesis equalities. Two significant contributions of the method of moment components are: 1) new decomposition of moments into parts which reflect passivity in all moments of passive networks; and 2) the analysis equalities impart a regular pattern in terms of the moment components, thus simplifying the moment generation for our method. None of these features is observable in conventional complete moment terms. Two new methods for obtaining passive reduced-order models based on the method of moment components are introduced. The passive reduced-order models are obtained by matching their impedance moment components to those of the original interconnect network through the synthesis equalities. Due to nonnegative definiteness of the moment components, the match in the moment components preserves the passivity of the original interconnect in the reduced-order model. The method of moment components does not have the instability problem of general moment matching techniques. The reduced-order model is specifically targeted for fast timing simulators so that interconnect effects can be simulated efficiently.

A coordinate-transformed Arnoldi algorithm for generating guaranteed stable reduced-order models of RLC circuits

Since the first papers on asymptotic waveform evaluation (AWE), Padé-based reduced order models have become standard for improving coupled circuit-interconnect simulation efficiency. Such models can be accurately computed using bi-orthogonalization algorithms like Padé via Lanczos (PVL), but the resulting Padé approximates can still be unstable even when generated from stable RLC circuits. For certain classes of RC circuits it has been shown that congruence transforms, like the Arnoldi algorithm, can generate guaranteed stable and passive reduced-order models. In this paper we present a computationally efficient model-order reduction technique, the coordinate-transformed Arnoldi algorithm, and show that this method generates arbitrarily accurate and guaranteed stable reduced-order models for RLC circuits. Examples are presented which demonstrates the enhanced stability and efficiency of the new method.

Passive reduced-order modeling of electromagnetic systems

Rapid electromagnetic field simulation is now being recognized as a critical component of next-generation computer-aided design frameworks that will be used for performance evaluation and design of the information processing and communication systems of the 21st century. Except for very simple systems, computer simulation of electromagnetic interactions is hindered by the very large number of degrees of freedom involved in the discrete model. One potentially useful approach to overcoming this computational bottleneck is model order reduction, where parts of the electromagnetic model are replaced by models of substantially lower order, yet capable of capturing the electromagnetic behavior of the original subsystems with sufficient engineering accuracy. Possible approaches to the development of such model order reduction techniques are the subject of this paper. The potential applications and the benefits from such electromagnetic model order reduction are discussed. The important issue of passivity of the generated reduced model is considered, and a set of constraints on the state representation of the discrete electromagnetic boundary-value problem are identified for the reduced order model to be passive. The paper concludes with a presentation of several numerical examples from the application of model order reduction techniques to the analysis of electromagnetic waveguides and antennas.

A new discrete transmission line model for passive model order reduction and macromodeling of high-speed interconnections

A new, computationally efficient, discrete model is presented for passive model order reduction of high-speed interconnections. The proposed discrete model is based on the use of the theory of compact finite differences for the development of the discrete approximation to the transmission line equations that govern wave propagation on the interconnections. Thus result in a discrete model that utilizes only a few unknowns per wavelength and yet provides highly accurate waveform resolution. In addition to improved computational efficiency, the generated discrete model is passive, and compatible with the passive reduced-order interconnect modeling algorithm (PRIMA). Thus, it is suitable for the development of passive reduced-order models of interconnection networks of high complexity. Numerical experiments from the simulation and model order reduction of coupled interconnections are used to illustrate the validity and efficiency of the proposed model.

Passive multipoint moment matching model order reduction algorithm on multiport distributed interconnect networks

In this paper, we introduce a general method of interconnect simulation based on distributed circuits. The algorithm is very efficient and consists of two main steps. In the first step, each distributed line is modeled by a finite order system with passivity preservation and multipoint moment matching of its input admittance/impedance matrix. In the second step, an Arnoldi-based congruence transform is applied to the network to form its reduced order model. The main feature of the algorithm is in its first step, where a passive multipoint moment matching model of a distributed line can be generated without any discretization of the line. We provide an integrated-congruence transform which can be directly applied to the partial differential equations of a distributed line and generate a passive finite order system as its model. We also provide an algorithm based on the L/sup 2/ Hilbert space theory so that exact moment matching at multiple points can be obtained, We demonstrate the accuracy of our method with examples and show the advantage of ours over conventional ones based on lumped circuit models.

PRIMA: passive reduced-order interconnect macromodeling algorithm

This paper describes an algorithm for generating provably passive reduced-order N-port models for RLC interconnect circuits. It is demonstrated that, in addition to macromodel stability, macromodel passivity is needed to guarantee the overall circuit stability once the active and passive driver/load models are connected. The approach proposed here, PRIMA, is a general method for obtaining passive reduced-order macromodels for linear RLC systems. In this paper, PRIMA is demonstrated in terms of a simple implementation which extends the block Arnoldi technique to include guaranteed passivity while providing superior accuracy. While the same passivity extension is not possible for MPVL, comparable accuracy in the frequency domain for all examples is observed.