AutoPas in ls1 mardyn: Massively parallel particle simulations with node-level auto-tuning

Steffen Seckler, Fabio Gratl, Matthias Heinen, Jadran Vrabec, Hans Joachim Bungartz, Philipp Neumann

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Due to computational cost, simulation software is confronted with the need to always use optimal building blocks — data structures, solver algorithms, parallelization schemes, and so forth — in terms of efficiency, while it typically needs to support a variety of hardware architectures. AutoPas implements the computationally most expensive molecular dynamics (MD) steps (e.g., force calculation) and chooses on-the-fly, i.e., at run time, the optimal combination of the previously mentioned building blocks. We detail decisions made in AutoPas to enable the interplay with MPI-parallel simulations and, to our knowledge, showcase the first MPI-parallel MD simulations that use dynamic tuning. We discuss the benefits of this approach for three simulation scenarios from process engineering, in which we obtain performance improvements of up to 50%, compared to the baseline performance of the highly optimized ls1 mardyn software.

Original languageEnglish
Article number101296
JournalJournal of Computational Science
Volume50
DOIs
StatePublished - Mar 2021

Keywords

  • Auto-tuning
  • AutoPas
  • MPI
  • Molecular dynamics
  • Particle simulations
  • ls1 mardyn

Fingerprint

Dive into the research topics of 'AutoPas in ls1 mardyn: Massively parallel particle simulations with node-level auto-tuning'. Together they form a unique fingerprint.

Cite this