Dynamic molecular dynamics ensembles for multiscale simulation coupling

Philipp Neumann (), Niklas Wittmer, Vahid Jafari, Steffen Seckler and Matthias Heinen
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Philipp Neumann: Helmut Schmidt University, Chair for High Performance Computing
Niklas Wittmer: Helmut Schmidt University, Chair for High Performance Computing
Vahid Jafari: Helmut Schmidt University, Chair for High Performance Computing
Steffen Seckler: Technical University of Munich, Chair of Scientific Computing
Matthias Heinen: Technical University of Berlin, Chair of Thermodynamics

A chapter in High Performance Computing in Science and Engineering '21, 2023, pp 425-438 from Springer

Abstract: Abstract Molecular dynamics (MD) simulation has become a valuable tool in process engineering. Despite our efforts in software developments for large-scale molecular simulations over several years, which have amongst others enabled record-breaking trillion-atom runs, MD simulations are—as stand-alone simulations—limited to rather small time and length scales. To make bigger scales accessible, we propose to work towards a coupling of CFD solvers with our efficient MD software ls 1 mardyn. As a first step, we discuss extensions to our coupling software MaMiCo, addressing the challenge of efficiently sampling hydrodynamic quantities from MD: due to the high level of thermal fluctuations, MD ensemble considerations are required for sampling. We propose an extension of MaMiCo that allows to handle dynamic ensembles, i.e. to launch and remove MD simulations on-the-fly over the course of a coupled simulation. We explain the underlying implementation and provide first scalability results.

Date: 2023
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DOI: 10.1007/978-3-031-17937-2_26

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