NHAR: A non‐homogeneous Arnoldi method for fast simulation of RCL circuits with a large number of ports
NHAR: A non‐homogeneous Arnoldi method for fast simulation of RCL circuits with a large number of ports
复制标题
NHAR：一种用于快速仿真具有大量端口的 RCL 电路的非齐次 Arnoldi 方法
DOI：
10.1002/cta.611
复制
发表时间：
2010
影响因子：
2.3
通讯作者：
W. Cai
中科院分区：
文献类型：
--
作者：
Xuan Zeng;Fan Yang;Yangfeng Su;W. Cai
具有大量端口的大规模RCL电路已被广泛用于建模互连电路，例如VLSI中的电源/接地网络，时钟分配网络和大型数据总线。输入相关矩匹配技术在构造降阶系统的投影矩阵时考虑了输入激励，已被提出来模拟这种类型的电路。现有的依赖输入的矩匹配方法要么存在扩展Krylov子空间（EKS）和改进的扩展Krylov子空间（IEKS）方法的数值不稳定性，要么存在扩展线性化（EXPLIN）方法难以承受的内存消耗和CPU开销。本文提出了一种非齐次ARnoldi（NHAR）过程来生成标准正交投影矩阵，该过程由节省内存且计算高效的线性化方案和数值稳定的部分正交化Arnoldi方法组成。通过应用所得到的投影矩阵来生成降阶模型，我们推导出了用于具有大量端口的大规模RCL电路的模型降阶的NHAR方法。所提出的NHAR方法可以保证矩匹配、数值稳定性和无源性保持。与EXPLIN方法相比，NHAR方法可以显著减小线性化系统的规模，从而在几乎相同的精度下，大大节省了内存消耗和计算成本。此外，与EKS和IEKS方法相比，NHAR具有数值稳定性，可以在几乎相同的计算成本下获得更高的准确度。版权所有© 2009约翰威利父子有限公司。
Large‐scale RCL circuits with a large number of ports have been widely employed to model interconnect circuits, such as the power/ground networks, clock distribution networks and large data buses in VLSI. The input‐dependent moment‐matching technique, which takes the input excitations into account when constructing the projection matrices for the reduced‐order systems, has been proposed to simulate this type of circuits. The existing input‐dependent moment‐matching methods suffer from either numerical instability in the case of extended Krylov subspace (EKS) and improved extended Krylov subspace (IEKS) methods, or unbearable memory consumption and CPU cost for the EXPanded LINearization (EXPLIN) method. In this paper, a Non‐Homogeneous ARnoldi (NHAR) process, which consists of a memory‐saving and computation‐efficient linearization scheme and a numerical stable partial orthogonalization Arnoldi method, is proposed for the generation of the orthonormal projection matrix. By applying the obtained projection matrix to generate the reduced‐order model, we derive the NHAR method for the model‐order reduction of large‐scale RCL circuits with a large number of ports. The proposed NHAR method can guarantee moment matching, numerical stability and passivity preserving. Compared with the EXPLIN method, NHAR can remarkably reduce the size of the linearized system and therefore can greatly save the memory consumption and computational cost with almost the same accuracy. Moreover, NHAR is numerically stable and can achieve higher accuracy with approximately the same computational cost compared with the EKS and IEKS methods. Copyright © 2009 John Wiley & Sons, Ltd.
复频域大规模 RCG 互连 LSI 缩减技术
DOI：
--
发表时间：
2004
期刊：
International Journal of Circuit Theory and Applications vol.32
影响因子：
--
作者：
Y.Yamagami;Y.Tanji;A.Hattori;Y.Nishio;A.Ushida
通讯作者：
A.Ushida