Statistical design with importance sampling reuse

摘要

A mechanism is provided for reusing importance sampling for efficient cell failure rate estimation of process variations and other design considerations. First, the mechanism performs a search across circuit parameters to determine failures with respect to a set of performance variables. For a single failure region, the initial search may be a uniform sampling of the parameter space. Mixture importance sampling (MIS) efficiently may estimate the single failure region. The mechanism then finds a center of gravity for each metric and finds importance samples. Then, for each new origin corresponding to a process variation or other design consideration, the mechanism finds a suitable projection and recomputes new importance sampling (IS) ratios.

主权项

1. A method, in a data processing system, for determining failure rate of a device using importance sampling reuse, the method comprising:
performing, by the data processing system, a uniform distribution sampling over a random sample space for a performance metric for the device with respect to an origin to form a uniform distribution set of samples, wherein the origin represents nominal values for device parameters for a given design of the device, wherein the metric is an operational performance value of the device, and wherein the uniform distribution set of samples comprises one or more failing samples; determining, by the data processing system, a center of gravity of the one or more failing samples with respect to the origin; determining, by the data processing system, an importance sampling weight function based on the center of gravity of the one or more failing samples; selecting a new origin representing alternative values for device parameters corresponding to a process variation or design consideration; determining, by the data processing system, a new importance sampling weight function with respect to the new origin; applying the new importance sampling weight function to the uniform distribution set of samples to form a weighted set of samples; and determining, by the data processing system, a failure rate for the device using the weighted set of samples for the alternative values for the device parameters.