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

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dc.creatorKorniss, G.
dc.creatorToroczkai, Z.
dc.creatorNovotny, M. A.
dc.creatorRikvold, P. A.
dc.date1999-09-07
dc.date2000-02-01
dc.date.accessioned2026-07-07T03:14:29Z
dc.date.available2026-07-07T03:14:29Z
dc.descriptionWe 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.
dc.descriptionRevTex, 4 pages, 3 figures
dc.identifierhttps://arxiv.org/abs/cond-mat/9909114
dc.identifierhttp://arxiv.org/abs/cond-mat/9909114
dc.identifierPhys. Rev. Lett. 84, 1351 (2000).
dc.identifierdoi:10.1103/PhysRevLett.84.1351
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/29687
dc.subjectStatistical Mechanics
dc.subjectDistributed, Parallel, and Cluster Computing
dc.subjectComputational Physics
dc.titleFrom Massively Parallel Algorithms and Fluctuating Time Horizons to Non-equilibrium Surface Growth
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