Tunable Stochastic Computing using Layered Synthesis and Temperature Adaptive Voltage Scaling

Neel Gala1,  VR Devanathan2,  Vish Visvanathan2,  Virat Gandhi1,  Veezhinathan Kamakoti1
1IIT-Madras, 2Texas Instruments, India


With increasing computing power in mobile devices, conserving battery power (or extending battery life) has become crucial. This together with the fact that most applications running on these mobile devices are increasingly error tolerant, has created immense interest in stochastic (or inexact) computing. In this paper, we present a framework wherein, the devices can operate at varying error tolerant modes while significantly reducing the power dissipated. Further, in very deep sub-micron technologies, temperature has a crucial role in both performance and power. The proposed framework presents a novel layered synthesis optimization coupled with temperature aware supply and body bias voltage scaling to operate the design at various ”tunable” error tolerant modes. We implement the proposed technique on a H.264 decoder block in industrial 28nm low leakage technology node, and demonstrate reductions in total power varying from 30% to 45%, while changing the operating mode from exact computing to inaccurate/error-tolerant computing.