SMM: scalable analysis of power delivery networks by stochastic moment matching

This paper proposes a novel method for analyzing large on-chip power delivery networks via a stochastic moment matching (SMM) method. The proposed method extends the existing direct stochastic random walk method that can be only applied to DC analysis in purely resistive networks or transient analysis of RC networks with low efficiency. The new method can analyze general structure RLC networks by combining the stochastic process with frequency domain moment matching technique. As a result, we achieve better scalability than traditional frequency domain P/G analysis approaches, and better efficiency than the existing random walk transient analysis techniques. Our experimental results show that SMM can easily trade efficiency for accuracy or vise versa. SMM can easily deliver 10times-100times speedup over a LU-based direct solver and about 10times speedup over the pure random walk method with reasonable accuracy on large industry P/G networks