Towards efficient SPICE-accurate nonlinear circuit simulation with on-the-fly support-circuit preconditioners

Abstract

SPICE-accurate simulation of present-day large-scale nonlinear integrated circuit (IC) systems with millions of linear/nonlinear components can be prohibitively expensive, and thus extremely challenging. In this paper, we present a novel support-circuit preconditioning (SCP) technique for tackling large-scale nonlinear circuit simulations by exploiting sparsified graphs of a given circuit network. By extracting support graphs (SGs) from the original linear circuit networks, and combining them with nonlinear devices, support-circuit preconditioner can be efficiently computed using existing matrix solvers, allowing for on-the-fly updates during transient simulations when adopted in Krylov-subspace iterative solvers. Experimental results for a variety of large-scale circuit designs show that the proposed method achieves up to 22X speedups in solving the matrices involved in DC and transient (TR) simulations, and up to 8X reduction in memory usage, when compared with the simulator powered by the state-of-the-art direct solver KLU.