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Home » Institute » Departments & Research Groups » High-Performance Computing in Materials Science

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ICAMS Research Group

High-performance Computing in Materials Science

A most efficient implementation of computer simulations methods is a key element in theoretical research on materials. The development and implementation of simulation methods for parallel computers has become an indispensable way to tackle nowadays materials science problems in order to map the requirements for size and complexity.


Godehard SutmannRUB, Marquard
Prof. Dr. Godehard Sutmann

Research Group Leader

Room:
Tel.: +49 2461 61 6746
E-Mail: godehard.sutmann@rub.de




Research

The research group High Performance Computing in Materials Science at ICAMS is working on the development of parallel methods and algorithms for the efficient simulation of materials science applications on different levels of approximation. Apart from original research, the group has strong links to the other ICAMS departments and supports the development of simulation codes and the efficient parallelization of programs developed at ICAMS.

Bridging the scale: Atoms, microstructures, properties.
Comparison of a parallel simulation with OpenPhase using a domain decomposition without (top) and with (bottom) load balancing, based on a block decomposition. Left: distribution of processors; Right: color coding for work distribution.
ICAMS, RUB

Currently, the group’s work focuses on various topics, represented by the three departments at ICAMS, i.e. Atomistic Modelling and Simulation (AMS), Scalebridging Thermodynamic and Kinetic Simulation (STKS) and Micromecanical and Macroscopic Modelling (MMM). Recently, we have concentrated on highly efficient implementations of particle based simulation methods, e.g. molecular dynamics, the combination of Monte Carlo and molecular dynamics (MD) in a parallel environment, parallel phase field simulations, and the problem of load balancing for different methods.



Competences

  • Parallel algorithms
  • Molecular dynamics, Monte Carlo
  • Particle simulation methods
  • Load balancing
Members
  • Sutmann, Prof. Dr. Godehard
Recent Publications
  • S. Bekemeier, C. Caldeira Rêgo, H. Mai et al. Advancing digital transformation in material science: the role of workflows within the MaterialDigital initiative. Advanced Engineering Materials, 1, 2402149, (2025)
  • M. Uddagiri, O. Shchyglo, I. Steinbach et al. Solidification of the Ni-based superalloy CMSX-4 simulated with full complexity in 3-dimensions. Progress in Additive Manufacturing, 8, 1, (2023)
  • H. Schaar, I. Steinbach, M. Tegeler. Numerical study of epitaxial growth after partial remelting during selective electron beam melting in the context of Ni–Al. Metals, 11, 2012, (2021)
  • R. Schiedung, M. Tegeler, D. Medvedev et al. Simulation of capillary-driven kinetics with multi-phase-field and lattice Boltzmann method. Modelling and Simulation in Materials Science and Engineering, 28, 065008, (2020)
  • R. Halver, J. H. Meinke, G. Sutmann. Kokkos implementation of an Ewald Coulomb solver and analysis of performance portability. Journal of Parallel and Distributed Computing, 138, 48-54, (2020)
  • R. Halver, J. Meinke, G. Sutmann. Examining performance portability with Kokkos for an Ewald sum Coulomb solver. Parallel Processing and Applied Mathematics, 12044, 35-45, (2020)

All publications



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