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Main Title: Understanding the Scalability of Molecular Simulation Using Empirical Performance Modeling
Author(s): Shudler, Sergei
Vrabec, Jadran
Wolf, Felix
Type: Conference Object
Language Code: en
Abstract: Molecular dynamics (MD) simulation allows for the study of static and dynamic properties of molecular ensembles at various molecular scales, from 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 specifically on the needs of industrial users in engineering. Within CME, the simulation code ms2 allows users to calculate thermodynamic properties of bulk fluids. 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 parameters on the execution time. Our approach is a systematic workflow that can be 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.
Issue Date: 24-Apr-2019
Date Available: 5-Dec-2019
DDC Class: 000 Informatik, Informationswissenschaft, allgemeine Werke
621 Angewandte Physik
Subject(s): molecular dynamics
performance modeling
parallel programming
Sponsor/Funder: BMBF, 01IH16008D, Verbundprojekt: TaLPas - Task-basierte Lastverteilung und Auto-Tuning in der Partikelsimulation
DFG, 323299120, ExtraPeak - Automatische Leistungsmodellierung von HPC-Anwendungen mit multiplen Modellparametern
Proceedings Title: Programming and Performance Visualization Tools : ESPT 2017, ESPT 2018, VPA 2017, VPA 2018
Editor: Bhatele, Abhinav
Boehme, David
Levine, Joshua A.
Malony, Allen D.
Schulz, Martin
Publisher: Springer
Publisher Place: Cham
Publisher DOI: 10.1007/978-3-030-17872-7_8
Page Start: 125
Page End: 143
Series: Lecture Notes in Computer Science
Series Number: 11027
EISSN: 1611-3349
ISBN: 978-3-030-17872-7
ISSN: 0302-9743
Notes: The final authenticated publication is available online at
Appears in Collections:FG Thermodynamik und Thermische Verfahrenstechnik » Publications

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