MPME-DP: Multi-population moment estimation via dirichlet process for efficient validation of analog/mixed-signal circuits

Abstract

Moment estimation is one of the most important tasks to appropriately characterize the performance variability of today's nanoscale integrated circuits. In this paper, we propose an efficient algorithm of multi-population moment estimation via Dirichlet Process (MPME-DP) for validation of analog and mixed-signal circuits with extremely small sample size. The key idea is to partition all populations (e.g., different environmental conditions, setup configurations, etc.) into groups. The populations within the same group are similar and their common knowledge can be extracted to improve the accuracy of moment estimation. As will be demonstrated by the silicon measurement data of a high-speed I/O link, MPME-DP reduces the moment estimation error by up to 65% compared to other conventional estimators.