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Hierarchical and adaptive finite-element reduction-recovery method for large-scale power and signal integrity analysis of high-speed IC and packaging structures

机译:用于大型功率和高速IC和包装结构的大规模功率和信号完整性分析的分层和自适应有限元缩减方法

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This paper proposes a hierarchical and adaptive finite-element reduction-recovery method for power and signal integrity analysis of high-speed IC and packaging structures. This method rigorously reduces the matrix of a multilayer system of O(N) to that of a single-cell one of O(1) regardless of the original problem size. More important, the matrix reduction is achieved analytically, and hence the CPU and memory overheads are minimal. In addition, the reduction preserves the sparsity of the original matrix. As a result, the matrix factorization cost of the proposed method is reduced to a constant. The CPU cost at each time step scales linearly with the number of unknowns to be recovered. Furthermore, an adaptive reductionrecovery scheme is developed to perform reduction and recovery in the active layers only, and hence further reducing the complexity of the proposed method. Numerical and experimental results demonstrate its performance.
机译:本文提出了高速IC和包装结构的功率和信号完整性分析的分层和自适应有限元缩减方法。该方法严格地将O(n)的多层系统的矩阵减少到O(1)中的单个小区的多层系统的矩阵,而不管原始问题大小如何。更重要的是,矩阵减少是在分析上实现的,因此CPU和存储器开销是最小的。此外,减少保留了原始矩阵的稀疏性。结果,所提出的方法的矩阵分解成本降低到常数。每个时间步长的CPU成本与要恢复的未知数的数量线性缩放。此外,开发了一种自适应还原脱离方案以仅在有源层中进行减少和恢复,因此进一步降低了所提出的方法的复杂性。数值和实验结果表明其性能。

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