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AutoPas: Auto-tuning for particle simulations

  • Technical University of Munich
  • Universität Hamburg

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

The C++ library AutoPas aims at delivering optimal node-level performance for particle simulations. This paper describes the internally implemented algorithms, and how the library uses auto-tuning to dynamically select their optimal combination at run-time. Results are presented, which show that all available algorithms and configuration options have their specific advantages. To demonstrate the library's capabilities in relevant application settings, it has been integrated into the software package ls1 mardyn. An example of a realistic molecular dynamics simulation from thermodynamics is shown in which AutoPas detects a change in the best possible algorithm configuration. It adapts the simulation algorithm accordingly, sustaining optimal performance without additional user input.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 33rd International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages748-757
Number of pages10
ISBN (Electronic)9781728135106
DOIs
StatePublished - May 2019
Event33rd IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2019 - Rio de Janeiro, Brazil
Duration: 20 May 201924 May 2019

Publication series

NameProceedings - 2019 IEEE 33rd International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2019

Conference

Conference33rd IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2019
Country/TerritoryBrazil
CityRio de Janeiro
Period20/05/1924/05/19

Keywords

  • Auto-Tuning
  • Automatic Algorithm Selection
  • Dynamic Tuning
  • HPC
  • Molecular Dynamics

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