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An algorithmic framework for efficient large-scale circuit simulation using exponential integrators

机译:使用指数积分器进行高效大规模电路仿真的算法框架

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摘要

We propose an efficient algorithmic framework for time-domain circuit simulation using exponential integrators. This work addresses several critical issues exposed by previous matrix exponential based circuit simulation research, and makes it capable of simulating stiff nonlinear circuit system at a large scale. In this framework, the system's nonlinearity is treated with exponential Rosenbrock-Euler formulation. The matrix exponential and vector product is computed using invert Krylov subspace method. Our proposed method has several distinguished advantages over conventional formulations (e.g., the well-known backward Euler with Newton-Raphson method). The matrix factorization is performed only for the conductance/resistance matrix G, without being performed for the combinations of the capacitance/inductance matrix C and matrix G, which are used in traditional implicit formulations. Furthermore, due to the explicit nature of our formulation, we do not need to repeat LU decompositions when adjusting the length of time steps for error controls. Our algorithm is better suited to solving tightly coupled post-layout circuits in the pursuit for full-chip simulation. Our experimental results validate the advantages of our framework.
机译:我们为使用指数积分器的时域电路仿真提出了一种有效的算法框架。这项工作解决了以前基于矩阵指数的电路仿真研究所暴露的几个关键问题,并使之能够大规模仿真刚性非线性电路系统。在此框架中,系统采用指数Rosenbrock-Euler公式处理非线性。矩阵指数和矢量积是使用反Krylov子空间方法计算的。我们提出的方法相对于常规配方(例如,著名的反向牛顿法和牛顿-拉夫森法)具有几个显着的优势。矩阵分解仅对电导/电阻矩阵G执行,而对电容/电感矩阵C和矩阵G的组合不执行,而传统的隐式公式中使用了电容/电感矩阵C和矩阵G的组合。此外,由于我们公式的明确性质,在调整错误控制的时间步长时,我们不需要重复LU分解。我们的算法更适合解决紧密耦合的布局后电路,以进行全芯片仿真。我们的实验结果验证了我们框架的优势。

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