  Uncertainties have become a major concern in integrated circuit design. In
order to avoid the huge number of repeated simulations in conventional Monte
Carlo flows, this paper presents an intrusive spectral simulator for
statistical circuit analysis. Our simulator employs the recently developed
generalized polynomial chaos expansion to perform uncertainty quantification of
nonlinear transistor circuits with both Gaussian and non-Gaussian random
parameters. We modify the nonintrusive stochastic collocation (SC) method and
develop an intrusive variant called stochastic testing (ST) method to
accelerate the numerical simulation. Compared with the stochastic Galerkin (SG)
method, the resulting coupled deterministic equations from our proposed ST
method can be solved in a decoupled manner at each time point. At the same
time, ST uses fewer samples and allows more flexible time step size controls
than directly using a nonintrusive SC solver. These two properties make ST more
efficient than SG and than existing SC methods, and more suitable for
time-domain circuit simulation. Simulation results of several digital, analog
and RF circuits are reported. Since our algorithm is based on generic
mathematical models, the proposed ST algorithm can be applied to many other
engineering problems.
