As CMOS technology enters the nanometer-regime, one of the most fundamental challenges will result from the loss of predictability of design behavior due to both variations during manufacturing and interferences between components during normal operation. As features on the die continue to shrink, control of the physical parameters, such as the feature size of transistors, their doping levels, and oxide thickness, will become increasingly difficult to control, resulting in dramatic increased uncertainty in the electrical characteristics of individual devices. Also, the close proximity of devices to each other will give rise to significant interference from elements surrounding a device, due to inductive and capacitive coupling, and due to environmental factors, such as power supply and temperature fluctuations. The increase in the number of uncertainties, as well as their severity will result in a general loss of predictability in nanometer-CMOS design and will threaten the ability to produce robust designs. <br/><br/>In this project, we are developing a statistical framework for analysis and optimization of system performance, power, and functional integrity, as well as their newly emerging trade-offs in nanometer design. In the presence of variations due to process fluctuations and environmental interferences, signals are inherently stochastic as are the basic measures of design quality, such as delay and power. The research is therefore investigating the development of stochastic models for performance metrics that capture their dependence on the various sources of uncertainty. The new design methodology will focus on robustness as a new measure of design quality, including delay, power consumption and measures of functional integrity, and will allow these design objectives to be constrained at prescribed levels of confidence. Furthermore, the research team is considering new methods for simultaneous optimization of performance, energy, and functional integrity that effectively exploit new trade-offs and interactions between these objectives in nanometer design.
ITR: Methodologies for Robust Design of Information Systems under Multiple Sources of Uncertainty