PowerRush: An Efficient Simulator for Static Power Grid Analysis

Efficient power grid analysis is critical for modern very large scale integration design but is computationally challenging in runtime and memory consumption because of the increasing size of power grids. PowerRush is proposed as an efficient IR-drop simulator, which includes an efficient SPICE parser, a robust circuit builder, and a linear solver Algebraic MultiGrid Preconditioned Conjugate Gradient. The proposed AMG-PCG solver is a pure algebraic method, which can provide stable convergence without geometric information. Aggregation-based AMG with K-cycle acceleration is adopted as a preconditioner to improve the scalability of iterative method. In multigrid scheme, double pairwise aggregation technique is applied to matrix graph in coarsening to ensure low setup cost and memory requirement. Furthermore, K-cycle multigrid scheme is adopted to provide Krylov subspace acceleration at each level to guarantee enhanced robustness and scalability. The experimental results for large-scale power grids have shown that PowerRush has remarkable scalability both in runtime and memory consumption. DC analysis of power grid with 60-million nodes can be solved by PowerRush for 0.01 $mV$ accuracy within 150 s and 21.99 GB total memory used. Moreover, the proposed AMG-PCG solver can perform much better than widely used direct solver Cholmod and well-developed Hybrid solver both on runtime and memory consumption.