An essential basis for designing novel materials is the understanding of their properties on the nanoscale. Molecular dynamics are an important tool for the analysis of a material on that scale.
To this end, we offer Tremolo-X, a massively parallel software package for numerical simulation in molecular dynamics. Here, much emphasis has been placed on the parallel implementation and its efficiency. In addition, a user-friendly graphical interface is beeing provided. Tremolo-X has been successfully applied within various projects in different fields of applications, e.g. nanotechnology, material science, biochemistry and biophysics.
- TREMOLO-X is a powerful software package used for the numerical simulation of interactions between atoms and molecules, the molecular dynamics. It provides the environment to design new innovative materials.
- TREMOLO-X uses highly efficient state of the art algorithms for the treatment of short- and long-range potentials, where much emphasis has been placed on the parallel implementation and its efficiency. All potential types are included which are commonly used for modeling of systems in the areas material science, nanotechnology and biophysics.
- TREMOLO-X includes also TREMOLO-X-GUI, which is an user-friendly graphical user interface frontend. This provides an easy set-up and analysis of numerical experiments.
- TREMOLO-X is already successfully applied in many different practical projects in different areas. The focus is on computations in nanotechnology, material science, biochemistry and biophysics.
TREMOLO-X – A Parallel Molecular Dynamics Software Package
- User-friendly GUI frontend
- Parallel version for distributed memory computers (MIMD) with the message passing interface (MPI)
- Parallel implementation of reactive many body potentials of Brenner, Marian, Tersoff, Feuston-Garofalini, Stillinger-Weber and Sutton-Chen
- Parallel implementation of fixed bond, angle, torsion (dihedral) and inversion potentials
- NVE, NVT and NPT ensemble, structural optimization and dissipative particle dynamics (DPD)
- Several time integrators and local optimizers: Verlet, multistep like Beeman-Verlet as well as Fletcher-Reeves and Polak-Ribière
- Replica exchange methods like Hybrid Monte Carlo and Parallel Tempering
- Computation of many measuring quantities, e.g. diffusion coefficients, stress-strain diagrams, elastic constants, distribution functions, correlation functions and shortest-path-ring statistics
- Fast implementation of short-range potentials via linked-cell method and parallelization by dynamic load-balanced domain decomposition
- Fast algorithms for long-range potentials: Particle-Mesh-Ewald with domain decomposition and parallel 3D-FFT and parallel multigrid. Also Barnes-Hut/fast multiple methods and parallelisation by space-filling curves
- Simply extendible to new potential types by modularity