title: From massively parallel algorithms and fluctuating time horizons to nonequilibrium surface growth
abstract: 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 nonequilibrium 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.
authors.affiliation: Supercomputer Computations Research Institute, Florida State University, Tallahassee, Florida 32306-4130, USA.
authors.initials: G
authors.lastname: Korniss
authors.initials: Z
authors.lastname: Toroczkai
authors.initials: MA
authors.lastname: Novotny
authors.initials: PA
authors.lastname: Rikvold