Predict and act

摘要

In this paper, we propose a proactive dynamic thermal management scheme for chip multiprocessors that run multi-threaded workloads. We introduce a new predictor that utilizes the band-limited property of the temperature frequency spectrum. A big advantage of our predictor is that it does not require the costly training phase like ARMA [7]. Our thermal management scheme incorporates temperature prediction information and runtime workload characterization to perform efficient thermally aware scheduling. Our results show that applying our algorithm considerably improves the average system temperature, hottest core temperature, product MTTF and performance by 6 °C, 8 °C, 41% and 72% respectively.