  Process variations are a major concern in today's chip design since they can
significantly degrade chip performance. To predict such degradation, existing
circuit and MEMS simulators rely on Monte Carlo algorithms, which are typically
too slow. Therefore, novel fast stochastic simulators are highly desired. This
paper first reviews our recently developed stochastic testing simulator that
can achieve speedup factors of hundreds to thousands over Monte Carlo. Then, we
develop a fast hierarchical stochastic spectral simulator to simulate a complex
circuit or system consisting of several blocks. We further present a fast
simulation approach based on anchored ANOVA (analysis of variance) for some
design problems with many process variations. This approach can reduce the
simulation cost and can identify which variation sources have strong impacts on
the circuit's performance. The simulation results of some circuit and MEMS
examples are reported to show the effectiveness of our simulator
