Shudler, Sergei ; Vrabec, Jadran ; Wolf, Felix (2019)
Understanding the Scalability of Molecular Simulation using Empirical Performance Modeling.
7th Workshop on Extreme Scale Programming Tools (ESPT 2018). Dallas, USA (11.-16.11.2018)
doi: 10.1007/978-3-030-17872-7_8
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (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.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2019 |
| Autor(en): | Shudler, Sergei ; Vrabec, Jadran ; Wolf, Felix |
| Art des Eintrags: | Bibliographie |
| Titel: | Understanding the Scalability of Molecular Simulation using Empirical Performance Modeling |
| Sprache: | Englisch |
| Publikationsjahr: | 24 April 2019 |
| Verlag: | Springer |
| Buchtitel: | Programming and Performance Visualization Tools: International Workshops |
| Reihe: | Lecture Notes in Computer Science |
| Band einer Reihe: | 11027 |
| Veranstaltungstitel: | 7th Workshop on Extreme Scale Programming Tools (ESPT 2018) |
| Veranstaltungsort: | Dallas, USA |
| Veranstaltungsdatum: | 11.-16.11.2018 |
| DOI: | 10.1007/978-3-030-17872-7_8 |
| Kurzbeschreibung (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. |
| Freie Schlagworte: | DFG|320898076, BMBF|01IH16008D, DoE|DE-SC0015524 |
| Zusätzliche Informationen: | held in conjunction with the International Conference on High Performance Computing, Networking, Storage and Analysis (SC 2018) |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Parallele Programmierung Zentrale Einrichtungen Zentrale Einrichtungen > Hochschulrechenzentrum (HRZ) Zentrale Einrichtungen > Hochschulrechenzentrum (HRZ) > Hochleistungsrechner |
| Hinterlegungsdatum: | 01 Nov 2018 10:12 |
| Letzte Änderung: | 01 Mär 2024 13:26 |
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