From Massively Parallel Algorithms and Fluctuating Time Horizons to Non-equilibrium Surface Growth
<|reference_start|>From Massively Parallel Algorithms and Fluctuating Time Horizons to Non-equilibrium Surface Growth: We study the asymptotic scaling properties of a massively parallel algorithm for discrete-event simulations where the discrete events are Poisson arrivals. The evolution of the simulated time horizon is analogous to a non-equilibrium surface. Monte Carlo simulations and a coarse-grained approximation indicate that the macroscopic landscape in the steady state is governed by the Edwards-Wilkinson Hamiltonian. Since the efficiency of the algorithm corresponds to the density of local minima in the associated surface, our results imply that the algorithm is asymptotically scalable.<|reference_end|>
@article{korniss1999from,
    title={From Massively Parallel Algorithms and Fluctuating Time Horizons to
  Non-equilibrium Surface Growth},
    author={G. Korniss, Z. Toroczkai, M. A. Novotny, and P. A. Rikvold},
    journal={Phys. Rev. Lett. 84, 1351 (2000).},
    year={1999},
    doi={10.1103/PhysRevLett.84.1351},
    number={FSU-SCRI-99-58},
    archivePrefix={arXiv},
    eprint={cond-mat/9909114},
    primaryClass={cond-mat.stat-mech cs.DC physics.comp-ph}
}