In this paper, we introduce an efficient transistorlevel simulation tool with SPICE-accuracy for deepsubmicrometer very large-scale integration circuits with strong-coupling effects. The new approach uses multigrid for huge networks of power/ground, clock, and interconnect with strong coupling. Mutual inductance can be incorporated without error-prone matrix sparsification approximations or expensive matrix inversion. Transistor devices are integrated using a novel two-stage Newton–Raphson method to dynamically model the linear network and nonlinear devices boundary. Orders-ofmagnitude speedup over Berkeley SPICE3 is observed for sets of real deep-submicrometer design circuits.

In this paper, we introduce a general operator splitting method for transient simulation of VLSI circuits. The proposed approach generates special partitions of the circuits and alternates the explicit and implicit integrations between the partitions. We prove that the method is unconditionally stable independent of the step size. The splitting scheme greatly reduces the nonzero fill-ins generated in direct methods like LU decomposition. Orders of magnitude speedup over Berkeley SPICE3 is observed for sets of circuits.

In this paper, we introduce an efficient transistor level simulation tool with SPICE-accuracy for deep-submicron(DSM) VLSI circuits with strong coupling effects. The new approach uses multigrid for large networks of power/ground, clock and signal interconnect. Transistor devices are integrated using a novel two-stage Newton-Raphson method to dynamically model the linear network and nonlinear devices interface. Orders of magnitude speedup over Berkeley SPICE3 is observed for sets of DSM design circuits.

An efficient matrix solver is critical to the analytical placement. As the size of the matrix becomes huge, the multilevel methods turn out to be more efficient and more scalable. Algebraic Multigrid (AMG) is a multilevel technique to speedup the iterative matrix solver [10]. We apply the algebraic multigrid method to solve the linear equations that arise from the analytical placement. A layout based clustering scheme is put forward to generate coarsening levels for the multigrid method. The experimental results show that the algebraic multigrid solver is promising for analytical placement.

In this paper, we introduce an efficient analysis method for the power network of general topology. The new approach is based on algebraic multigrid (AMG) method that can avoid the slow convergence of basic iterative methods. An innovative adaptive coarsening and error-smoothing scheme is employed to further speed up the performance, taking advantage of the spatial variation of power supply noise. Experimental results show that our method is more than 100 times faster than SPICE3.