Multi-dimensional optimization for approximate near-threshold computing

The demise of Dennard’s scaling has created both power and utilization wall challenges for computer systems.As transistors operating in the near-threshold region are able to obtain flexible trade-offs between power and performance,it is regarded as an alternative solution to the scaling challenge.A reduction in supply voltage will nevertheless generate significant reliability challenges,while maintaining an error-free system that generates high costs in both performance and energy consumption.The main purpose of research on computer architecture has therefore shifted from performance improvement to complex multi-objective optimization.In this paper,we propose a three-dimensional optimization approach which can effectively identify the best system configuration to establish a balance among performance,energy,and reliability.We use a dynamic programming algorithm to determine the proper voltage and approximate level based on three predictors:system performance,energy consumption,and output quality.We propose an output quality predictor which uses a hardware/software co-design fault injection platform to evaluate the impact of the error on output quality under near-threshold computing(NTC).Evaluation results demonstrate that our approach can lead to a 28% improvement in output quality with a 10% drop in overall energy efficiency;this translates to an approximately 20% average improvement in accuracy,power,and performance.