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ARPE: A Tool To Build Equation Models of Computing Systems
Martina Maggio, Lund University; Henry Hoffmann, University of Chicago
An important challenge in the design and implementation of self-optimizing systems is that of finding a model that maps changes in a tunable parameter (or “knob”) into an effect on the performance, power, or energy, of the overall system. This paper describes ARPE (Analyzing the Relationship between Parameters and Effectors), an open source tool to analyze the effect of parameter changes on the behavior of applications in a complex system with interrelated knobs.
We evaluate ARPE in several case studies on real systems with different sensors and parameters. Our results show that ARPE can help determine the best sensors for a system designed to predict application execution time. For space limitations, only one case study is here shown, demonstrating that the error of modeling energy consumption is limited to the range 0.1–10% for previously unseen benchmarks.
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author = {Martina Maggio and Henry Hoffmann},
title = {{ARPE}: A Tool To Build Equation Models of Computing Systems},
booktitle = {8th International Workshop on Feedback Computing (Feedback Computing 13)},
year = {2013},
address = {San Jose, CA},
url = {https://www.usenix.org/conference/feedbackcomputing13/workshop-program/presentation/maggio},
publisher = {USENIX Association},
month = jun
}
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