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Phys. Rev. Lett. 84, 1351–1354 (2000)

From Massively Parallel Algorithms and Fluctuating Time Horizons to Nonequilibrium Surface Growth

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G. Korniss1, Z. Toroczkai2,3, M. A. Novotny1, and P. A. Rikvold1,4
1Supercomputer Computations Research Institute, Florida State University, Tallahassee, Florida 32306-4130
2Department of Physics, University of Maryland, College Park, Maryland 20742-4111
3Department of Physics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061-0435
4Center for Materials Research and Technology and Department of Physics, Florida State University, Tallahassee, Florida 32306-4350

Received 7 September 1999; published in the issue dated 7 February 2000

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.

© 2000 The American Physical Society

URL:
http://link.aps.org/doi/10.1103/PhysRevLett.84.1351
DOI:
10.1103/PhysRevLett.84.1351
PACS:
89.80.+h, 02.70.Lq, 05.40.-a, 68.35.Ct
 
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