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Accelerating relaxation algorithms for circuit simulation using waveform-Newton and step-size refinement

机译:使用波形牛顿和步长细化的电路仿真加速松弛算法

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A new relaxation algorithm for circuit simulation that combines the advantages of iterated timing analysis (ITA) and waveform relaxation (WR) is described. The method is based on using an iterative stepsize refinement strategy with a waveform-relaxation-newton (WRN) algorithm. All three relaxation techniques, ITA, WR, and WRN, are compared, and experimental results that indicate the strengths and weaknesses of the methods are presented. In addition, a new convergence proof for the waveform-Newton (WN) method for systems with nonlinear capacitors is provided. Finally, it is shown that the step-refined WRN algorithm can be implemented on a parallel processor in such a way that different subsystems can be processed in parallel and the solution at different timepoints of the same subsystem can also be computed in parallel.
机译:描述了一种新的电路仿真松弛算法,该算法结合了迭代时序分析(ITA)和波形松弛(WR)的优点。该方法基于使用具有波形松弛牛顿(WRN)算法的迭代逐步调整细化策略。比较了ITA,WR和WRN这三种松弛技术,并给出了表明该方法的优缺点的实验结果。此外,为具有非线性电容器的系统的波形牛顿(WN)方法提供了新的收敛证明。最后,示出了可以在并行处理器上以这样的方式来实现逐步完善的WRN算法:不同的子系统可以并行处理,并且同一子系统在不同时间点的解决方案也可以并行计算。

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