With the growing importance of parametric (process and environmental) variations in advanced technologies, it has become a serious challenge to design reliable, fast and low-power embedded memories. Adopting a variation-aware design paradigm requires a holistic perspective of memory-wide metrics such as yield, power and performance. However, accurate estimation of such metrics is largely dependent on circuit implementation styles, technology parameters and architecture-level specifics. In this paper, we propose a fully automated tool - INFORMER - that helps high-level designers estimate memory reliability metrics rapidly and accurately. The tool relies on accurate circuit-level simulations of failure mechanisms such as soft-errors and parametric failures. The statistics obtained can then help couple low-level metrics with higher-level design choices. A new technique for rapid estimation of low-probability failure events is also proposed. We present three use-cases of our prototype tool to demonstrate its diverse capabilities in autonomously guiding large SRAM based robust memory designs. © 2014 EDAA.

Peer Reviewed