Multiscale Simulation Methods for Soft Matter Systems

Multiscale modeling is a central topic in theoretical condensed matter physics and materials science. One prominent class of materials, whose properties can rarely be understood on one length scale and one time scale alone, is soft matter. The properties of soft materials are determined by an intricate interplay of energy and entropy, and minute changes of molecular interactions may lead to massive changes of the system’s macroscopic properties.

The ZDV coordinates the central support project, which offers software development services for the science projects within TRR 146 and which is itself a research project that analyses and optimizes the usage of HPC resources within the context of soft-matter systems. The scientific projects described in this proposal depend on a reliable and flexible software platform that allows to efficiently implement and test new methods and algorithms and which provides a toolset for data analysis. The MD software framework ESPResSo++ will become thiscore platform within the TRR 146 and the focus of project G will be explained based on ESPResSo++. Nevertheless, other platforms within this TRR face very similar challenges and the investigations will be extended to all projects within this TRR.

The aim of this central support project is to provide a central software platform that provides solutions to the aforementioned problems and that is accessible byall collaboration partners. It therefore:

• Supports the scientific projects in the development process of simulation software and helps to transfer algorithms from CPUs to acceleratorsand couples the individual modules with ESPResSo++.
• Develops load-balancing schemes for MD simulations, which are able to efficiently scale to HPC environments. The load-balancing schemes will be initially implemented in the core ESPResSo++-modules and will be afterwards transferred to the other simulation environments of the TRR.
• Provides an asynchronous checkpointing environment, which is able to scale by distributing the checkpoints in the HPC cluster, using techniques, which are independent from the programming framework.
• Allows applications to steer their IO-behavior and therefore enables them to improve IO performance even after the development process has finished

Project Partnes

• Zentrum für Datenverarbeitung
• Max-Planck-Institut für Polymerforschung

Funding Period

10/2014 -- 06/2022

External Links

Web site of the TRR 146

Contact

• Prof. Dr. André Brinkmann
• Zhen-Hao Xu, Ph.D.
• James Vance

Publications

2023

2017

2016

2015

2014