基于压缩式双共轭梯度算法对大规模电源/地线网络的快速分析
A Fast Analysis of Large-Scale Power and Ground Networks Based on Compressed BCG Algorithm
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摘要: 采用压缩式双共轭梯度算法分析大规模电源/地线网络.首先以稀疏存储结构对大规模的系数矩阵进行压缩处理,然后采用双共轭梯度算法对网络进行模拟.双共轭梯度算法采用2组共轭向量组作为搜索方向,收敛速度快.实验数据表明:在保证精度的情况下,该算法在加快电路网络分析求解效率的同时,大幅度地节省了计算所占用的内存,它适用于分析超大规模的电源/地线网络.Abstract: An improved method is proposed based on compressed b-i conjugate gradient (BCG) algorithm to perform efficient static and transient simulations for large-scale power and ground networks circuits.A more efficient compressed storage strategy is used to save the memory,and BCG algorithm is used to analysis the large-scale power and ground networks. Extensive experimental results show that the compressed BCG algorithm gain the significant memory and run-time advantages over the traditional approach and has more powerful capability to deal with the increasing size of power and ground networks.
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