Nonequilibrium Surface Growth and Scalability of Parallel Algorithms for Large Asynchronous Systems

  • G. Korniss
  • M. A. Novotny
  • Z. Toroczkai
  • P. A. Rikvold
Part of the Springer Proceedings in Physics book series (SPPHY, volume 86)


The scalability of massively parallel algorithms is a fundamental question in computer science. We study the scalability and the efficiency of a conservative massively parallel algorithm for discrete-event simulations where the discrete events are Poisson arrivals. The parallel algorithm is applicable to a wide range of problems, including dynamic Monte Carlo simulations for large asynchronous systems with short-range interactions. The evolution of the simulated time horizon is analogous to a growing and fluctuating surface, and the efficiency of the algorithm corresponds to the density of local minima of this surface. In one dimension we find that the steady state of the macroscopic landscape is governed by the Edwards-Wilkinson Hamiltonian, which implies that the algorithm is scalable. Preliminary results for higher-dimensional logical topologies are discussed.


Monte Carlo Processing Element Parallel Algorithm Parallel Scheme Surface Width 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • G. Korniss
    • 1
    • 4
  • M. A. Novotny
    • 1
    • 4
  • Z. Toroczkai
    • 2
  • P. A. Rikvold
    • 1
    • 3
    • 4
  1. 1.School of Computational Science and Information TechnologyFlorida State UniversityTallahasseeUSA
  2. 2.Department of PhysicsUniversity of MarylandCollege ParkUSA
  3. 3.Department of Physics and Center for Materials Research and TechnologyFlorida State UniversityTallahasseeUSA
  4. 4.Department of Physics, Applied Physics, and AstronomyRensselaer Polytechnic InstituteTroyUSA

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