NBTI-aware data allocation strategies for scratchpad memory based embedded systems

While performance and power continue to be important metrics for embedded systems, as CMOS technologies continue to shrink, new metrics such as variability and reliability have emerged as limiting factors in the design of modern embedded systems. In particular, the reliability impact of pMOS negative bias temperature instability (NBTI) has become a serious concern. Recent works have shown how conventional leakage optimization techniques can help mitigate NBTI-induced aging effects on cache memories. In this paper we focus specifically on scratchpad memory (SPM) and present novel software approaches as a means of alleviating the NBTI-induced aging effects. In particular, we demonstrate how intelligent software directed data allocation strategies can extend the lifetime of partitioned SPMs by means of distributing the idleness across the memory sub-banks.