Runtime workload behavior prediction using statistical metric modeling with application to dynamic power management

@article{Sarikaya2010RuntimeWB,
  title={Runtime workload behavior prediction using statistical metric modeling with application to dynamic power management},
  author={Ruhi Sarikaya and Canturk Isci and Alper Buyuktosunoglu},
  journal={IEEE International Symposium on Workload Characterization (IISWC'10)},
  year={2010},
  pages={1-10}
}
Adaptive computing systems rely on accurate predictions of workload behavior to understand and respond to the dynamically-varying application characteristics. In this study, we propose a Statistical Metric Model (SMM) that is system-and metric-independent for predicting workload behavior. SMM is a probability distribution over workload patterns and it attempts to model how frequently a specific behavior occurs. Maximum Likelihood Estimation (MLE) criterion is used to estimate the parameters of… CONTINUE READING

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