An early prediction methodology for aging sensor insertion to assure safe circuit operation due to NBTI aging

This paper proposes an early resilience methodology to identify circuit output nodes where aging sensors should be inserted for an error prediction framework. The methodology is based in a pre-layout statistical estimation of the signal paths likely to become critical due to NBTI and/or Process Variations. To handle the fact that spatial correlation information is not available at early steps of the design flow, a statistical approach maximizing critical paths coverage is proposed. The results obtained with the early prediction methodology are compared with those obtained with spatial correlation information. The proposed methodology provides a good prediction of the set of critical paths to be monitored. Furthermore, location and number of aging sensors required to be inserted at critical paths output nodes are closely predicted.