From Massively Parallel Algorithms and Fluctuating Time Horizons to Non-equilibrium Surface Growth

Details From Massively Parallel Algorithms and Fluctuating Time Horizons to Non-equilibrium Surface Growth From Massively Parallel Algorithms and Fluctuating Time Horizons to Non-equilibrium Surface Growth

1999-09-07

arxiv.org/abs/cond-mat/9909114v2

Phys. Rev. Lett. 84, 1351 (2000).

Physics

Condensed Matter

Statistical Mechanics

RevTex, 4 pages, 3 figures

Scientific paper

10.1103/PhysRevLett.84.1351

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.

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