Publikationsrepositorium - Helmholtz-Zentrum Dresden-Rossendorf

Lattice Monte-Carlo methods are used to study out-of- and towards-equilibrium systems, like surface growth, spin systems and even phase separation in solid mixtures using kinetic Metropolis lattice Monte-Carlo (KLMC). Applications range from the study of universal scaling or aging behaviors to concrete systems, where coarsening of nanocomposites or self-organization of functional nanostructures is relevant, for example spinodal decomposition in solar cell absorber layers. In these systems, scaling needs to be followed for long times to allow structures to grow over orders of magnitude, which requires large-scale simulations. For the evolution of nanostructures, atomistic simulations at experimental spatiotemporal scales are often desired.

This talk will give an overview over a variety of lattice Monte-Carlo algorithms, which have been found or made suitable for implementation on GPUs: Stochastic cellular automata can be implemented very efficiently [1-3] and are suitable for many systems. The efficient implementation of random sequential dynamics is more challenging. Solutions will be presented for a dimer lattice gas mapped to surface growth [4,5] and KLMC [6]. The latter was also extended to implement dynamics driven by ion-beam mixing triggering long-range interactions. However, these implementations hinge on the fact, that only a very small number of states need to be encoded at each lattice site. A more flexible implementation, employing a variation of multisurface-coding to enable vectorization, will be presented for simulations of restricted solid-on-solid and Potts models with random sequential dynamics. [7]

[1] Block, B., Virnau, P., Preis, T.: Comp. Phys. Comm. 181(9), 1549 (2010)
[2] Lulli, M., Bernaschi, M., Parisi, G.: Comp. Phys. Comm. 196, 290 (2015)
[3] Kelling, J., Ódor, G., Gemming, S.: 2016 IEEE Int. Conf. Intell. Eng. Syst., arXiv:1606.00310 (2016)
[4] Kelling, J., Ódor, G.: Phys. Rev. E 84, 061150 (2011)
[5] Ódor, G., Kelling, J., Gemming, S.: Phys. Rev. E 89, 032146 (2014)
[6] Kelling, J., Ódor, G., Nagy, M. F., Schulz, H., Heinig, K.: EPJST 210, 175 (2012)
[7] Kelling, J., Ódor, G., Gemming, S.: arXiv:1605.02620 (2016)