Standby Supply Voltage Minimization for Reliable Nanoscale SRAMs

Increased leakage current and device variability are posing major challenges to CMOS circuit designs in deeply scaled technologies. Static Random Accessed Memory (SRAM) has been and continues to be the largest component in embedded digital systems or Systems-onChip (SoCs). It is expected to occupy over 90% of the area of SoC by 2013 (Nakagome et al., 2003). As a result, SRAM is more vulnerable to those challenges. To effectively reduce SRAM leakage and/or active power, supply voltage (VDD) is often scaled down during standby operation (e.g. (Qin et al., 2004; Flautner et al., 2002; Bhavnagarwala et al., 2004; Wang et al., 2007)) and/or active operation (e.g. (Morita et al., 2006; Joshi et al., 2007)). For ultra-low-energy applications, SRAMs operating with VDD near/below the threshold voltage (VT) are also proposed (e.g. (Calhoun & Chandrakasan, 2007; Verma & Chandrakasan, 2008)). However, all SRAM functions, including read stability, write ability, access performance, and hold stability, are less reliable at lower voltage, which leads to the reduction of yield. The minimum supply voltage (Vmin) is limited by the lowest acceptable yield and determines the maximum achievable power reduction. Applying an underestimated Vmin will cause intolerable failures and decrease SRAM yield. On the other hand, applying an overestimated Vmin will waste power and energy. However, finding the optimum Vmin becomes difficult in the presence of global and local variations. In this chapter, we particularly explore SRAM Vmin during standby mode, i.e. data retention voltage (DRV). We first analyze the impacts of local/random and global/systematic variations on DRV, and then present new statistical and adaptive design methods to address those impacts. The goal of this chapter is to develop effective methods for achieving the best leakage power savings while maintaining the desired yield under variations.