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- W1989036882 abstract "To improve the efficiency of direct solution methods in SPICE-accurate nonlinear circuit simulations, preconditioned iterative solution techniques have been widely studied in the past decades. However, it still has been an extremely challenging task to develop general-purpose preconditioning methods that can deal with various large-scale nonlinear circuit simulations. In this work, a novel circuit-oriented, general-purpose support-circuit preconditioning technique (GPSCP) is proposed to significantly improve the matrix solving time and reduce the memory consumption during large-scale non-linear circuit simulations. We show that by decomposing the system Jacobian matrix at a given solution point into a graph Laplacian matrix as well as a matrix including all voltage and controlled sources, and subsequently sparsifying the graph Laplacian matrix based on support graph theory, the general-purpose support-circuit preconditioning matrix can be efficiently obtained, thereby serving as a very effective and efficient preconditioner in solving the original Jacobian matrix through Krylov-subspace iterations. Additionally, a novel critical node selection method and an energy-based spanning-graph scaling method have been proposed to further improve the quality of ultra-sparsifier support graph. To gain higher computational efficiency during transient circuit analysis, a dynamic support-circuit preconditioner updating approach has also been investigated. Our experimental results for a variety of large-scale nonlinear circuit designs show that the proposed technique can achieve up to 14.0X runtime speedups and 6.7X memory reduction in DC and transient simulations." @default.
- W1989036882 created "2016-06-24" @default.
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- W1989036882 date "2012-11-05" @default.
- W1989036882 modified "2023-09-23" @default.
- W1989036882 title "GPSCP" @default.
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- W1989036882 doi "https://doi.org/10.1145/2429384.2429473" @default.
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