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DTSTART;TZID=America/Chicago:20181116T092000
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UID:submissions.supercomputing.org_SC18_sess153_ws_espt102@linklings.com
SUMMARY:Understanding the Scalability of Molecular Simulation Using Empiri
 cal Performance Modeling
DESCRIPTION:Sergei Shudler (Technical University Darmstadt), Jadran Vrabec
  (University of Paderborn), and Felix Wolf (Technical University Darmstadt
 )\n\nMolecular dynamics (MD) simulation allows for the study of static and
  dynamic properties of molecular ensembles at various molecular scales, fr
 om monatomics to macromolecules such as proteins and nucleic acids. It has
  applications in biology, materials science, biochemistry, and biophysics.
  Recent developments in simulation techniques spurred the emergence of the
  computational molecular engineering (CME) field, which focuses specifical
 ly on the needs of industrial users in engineering. Within CME, the simula
 tion code ms2 allows users to calculate thermodynamic properties of bulk f
 luids. It is a parallel code that aims to scale the temporal range of the 
 simulation while keeping the execution time minimal. In this paper, we use
  empirical performance modeling to study the impact of simulation paramete
 rs on the execution time. Our approach is a systematic workflow that can b
 e used as a blue-print in other fields that aim to scale their simulation 
 codes. We show that the generated models can help users better understand 
 how to scale the simulation with minimal increase in execution time.\n\nTa
 g: Performance, Productivity\n\nRegistration Category: Workshop Reg Pass\n
 \nSession Chairs: Martin Schulz (Technical University of Munich, Leibniz S
 upercomputing Centre (LRZ)) and Felix Wolf (Technical University of Darmst
 adt)\n\n
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