SRAM Design Exploration with Integrated Application-Aware Aging Analysis

On-Chip SRAMs are an integral part of safety-critical System-on-Chips. At the same time however, they are also most susceptible to reliability threats such as Bias Temperature Instability (BTI), originating from the continuous trend of technology shrinking. BTI leads to a significant performance degradation, especially in the Sense Amplifiers (SAs) of SRAMs, where failures are fatal, since the data of a whole column is destroyed. As BTI strongly depends on the workload of an application, the aging rates of SAs in a memory array differ significantly and the incorporation of workload information into aging simulations is vital. Especially in safety-critical systems precise estimation of application specific reliability requirements to predict the memory lifetime is a key concern. In this paper we present a workload-aware aging analysis for On-Chip SRAMs that incorporates the workload of real applications executed on a processor. According to this workload, we predict the performance degradation of the SAs in the memory. We integrate this aging analysis into an aging-aware SRAM design exploration framework that generates and characterizes memories of different array granularity to select the most reliable memory architecture for the intended application. We show that this technique can mitigate SA degradation significantly depending on the environmental conditions and the application workload.