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UID:submissions.supercomputing.org_SC23_sess433_ws_ships101@linklings.com
SUMMARY:Domain-Specific Energy Modeling for Drug Discovery and Magnetohydr
 odynamics Applications
DESCRIPTION:Lorenzo Carpentieri, Marco D'Antonio, Kaijie Fan, Luigi Crisci
 , and Biagio Cosenza (University of Salerno); Federico Ficarelli and Danie
 le Cesarini (CINECA); Gianmarco Accordi, Davide Gadioli, and Gianluca Pale
 rmo (Polytechnic University of Milan); Peter Thoman and Philip Salzmann (U
 niversity of Innsbruck); Philipp Gschwandtner (University of Innsbruck, PH
 3 GmbH); Markus Wippler (PH3 GmbH); Filippo Marchetti and Daniele Gregori 
 (E4); and Andrea Rosario Beccari (Dompé Farmaceutici Spa)\n\nFrequency sca
 ling is a well-known energy-saving power management technique that modulat
 es the device frequency to explore the trade-off between energy and perfor
 mance.  Higher energy savings require a frequency tuning phase since diffe
 rent applications can have different energy and time behavior depending on
  the frequency setting.  Machine learning models can be used to predict th
 e optimal frequency configuration based on static or dynamic features extr
 acted from the target application.  While general-purpose energy models ca
 n be very accurate on a wide range of applications their accuracy can be l
 imited by the specific input of the target application.  We present an ene
 rgy characterization that spans the fields of drug discovery and magnetohy
 drodynamics by using two real-world applications as case studies: LiGen an
 d Cronos.  To overcome the limitations of general-purpose approaches, we d
 efine two domain-specific energy models, which enhance the general-purpose
  energy models by leveraging the target application's input parameter to i
 ncrease the accuracy.\n\nTag: Artificial Intelligence/Machine Learning, En
 ergy Efficiency, Green Computing, Performance Measurement, Modeling, and T
 ools, Sustainability\n\nRegistration Category: Workshop Reg Pass\n\nSessio
 n Chairs: Andrea Borghesi (University of Bologna; Department of Electrical
 , Electronic and Information Engineering) and Daniela Loreti (University o
 f Bologna)\n\n
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