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Stochastic verification of run-time performance adaptation with field delay testing

Run-time performance adaptation with field delay testing is a promising approach for minimizing design margin while sustaining necessary operational margin in the field. However, run-time performance adaptation has not been adopted in industrial designs since a serious concern on timing error occurrence exists. For putting the run-time performance adaptation in a practical use, we need to verify and optimize the run-time adaptation system in design time. For this purpose, we have developed a stochastic framework for error rate estimation that models adaptive speed control as a continuous-time Markov process. In this paper, we evaluate MTTF and power consumption of an embedded processor whose performance is adaptively controlled with online testing and offline testing. This evaluation quantitatively shows the power reduction and MTTF improvement thanks to run-time performance adaptation.