A compressed BiCGStab algorithm for power and ground network analysis

Haohang Su, Yimen Zhang, Yuming Zhang, Jincai Man
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引用次数: 3

Abstract

An effective method is proposed based on compressed BiCGStab approaches to perform static and transient simulations for large-scale power and ground network circuits and a good result is obtained. Extensive experimental results on large-scale power and ground network show that presented method is over two orders faster than HSPICE in transient simulations. Furthermore, our algorithm reduces over 95% of memory usage than HSPICE and 75% of memory usage than ICCG while the accuracy is not compromised.
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一种用于电力和地网分析的压缩bicstab算法
提出了一种基于压缩BiCGStab方法对大型电网和地网电路进行静态和暂态仿真的有效方法,并取得了良好的效果。在大型电网和地网上的大量实验结果表明,该方法在瞬态仿真中比HSPICE快两个数量级以上。此外,我们的算法比HSPICE减少了95%以上的内存使用,比ICCG减少了75%的内存使用,而准确性没有受到影响。
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