Low-power die-level process variation and temperature monitors for yield analysis and optimization in deep-submicron CMOS.

This paper reports design, efficiency, and measurement results of the process variation and temperature monitors for yield analysis and enhancement in deep-submicron CMOS circuits. Additionally, to guide the verification process with the information obtained through monitoring, two efficient algorithms based on an expectation-maximization method and adjusted support vector machine classifier are proposed. The monitors and algorithms are evaluated on a prototype 12-bit analog-to-digital converter fabricated in standard single poly six-metal 90-nm CMOS.