Physics – Condensed Matter – Statistical Mechanics
Scientific paper
2000-02-29
Springer Proceedings in Physics, Vol. 86, Computer Simulation Studies in Condensed-Matter Physics XIII, edited by D.P. Landau,
Physics
Condensed Matter
Statistical Mechanics
to appear in Computer Simulation Studies in Condensed Matter Physics XIII, edited by D.P. Landau, S.P. Lewis, and H.-B. Schutt
Scientific paper
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.
Korniss Gyorgy
Novotny Mark A.
Rikvold Per Arne
Toroczkai Zoltan
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