Abstract
We report on the parallelization of two widely used algorithms in computational physics: The local-update Metropolis Monte Carlo simulation of the Ising model and a cluster identification algorithm which is used for percolation or percolation-like problems. The algorithm for the identification of clusters for the percolation-like problems was tested on the Swendsen-Wang method for the simulation of the Ising model. Simulation results are presented for a quench from a disordered state to a state below the coexistence curve. We show that the resulting domain growth has an exponential instead of a power law. The simulations were carried out on a parallel computer based on the transputer concept with up to 128 processors. The performance data show that the algorithms can perform with a linear speed-up. A scaling law for the performance of geometric parallel algorithms is proposed and tested.
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Heermann, D.W., Burkitt, A.N. (1990). Parallelization of Computational Physics Algorithms. In: Landau, D.P., Mon, K.K., Schüttler, HB. (eds) Computer Simulation Studies in Condensed Matter Physics II. Springer Proceedings in Physics, vol 45. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-75234-6_3
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DOI: https://doi.org/10.1007/978-3-642-75234-6_3
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