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Domain-Specific Energy Modeling for Drug Discovery and Magnetohydrodynamics Applications
DescriptionFrequency scaling is a well-known energy-saving power management technique that modulates the device frequency to explore the trade-off between energy and performance. Higher energy savings require a frequency tuning phase since different applications can have different energy and time behavior depending on the frequency setting. Machine learning models can be used to predict the optimal frequency configuration based on static or dynamic features extracted from the target application. While general-purpose energy models can be very accurate on a wide range of applications their accuracy can be limited by the specific input of the target application. We present an energy characterization that spans the fields of drug discovery and magnetohydrodynamics by using two real-world applications as case studies: LiGen and Cronos. To overcome the limitations of general-purpose approaches, we define two domain-specific energy models, which enhance the general-purpose energy models by leveraging the target application's input parameter to increase the accuracy.
Event Type
Workshop
TimeSunday, 12 November 20232:55pm - 3:20pm MST
Location603
Tags
Artificial Intelligence/Machine Learning
Energy Efficiency
Green Computing
Performance Measurement, Modeling, and Tools
Sustainability
Registration Categories
W