Dynamic Configuration Prefetching Based on Piecewise Linear Prediction
Design, Automation & Test in Europe (DATE 2013), Grenoble, France, March 18-22, 2013.
Modern systems demand high performance, as well as high degrees of flexibility and adaptability. Many current applications exhibit a dynamic and nonstationary behavior, having certain characteristics in one phase of their execution, that will change as the applications enter new phases, in a manner unpredictable at design-time. In order to meet the performance requirements of such systems, it is important to have on-line optimization algorithms, coupled with adaptive hardware platforms, that together can adjust to the run-time conditions. We propose an optimization technique that minimizes the expected execution time of an application by dynamically scheduling hardware prefetches. We use a piecewise linear predictor in order to capture correlations and predict the hardware modules to be reached. Experiments show that the proposed algorithm outperforms the previous state-of-art in reducing the expected execution time by up to 27% on average.
[LEP13] Adrian Lifa, Petru Eles, Zebo Peng, "Dynamic Configuration Prefetching Based on Piecewise Linear Prediction", Design, Automation & Test in Europe (DATE 2013), Grenoble, France, March 18-22, 2013.