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We present an ef?cient parallel algorithm for lattice gas Monte Carlo simulations in the framework of an Ising model that allows arbitrary interaction on any lattice, a model often called a cluster expansion. Thermodynamic Monte Carlo simulations strive for the equilibrium properties of a system by exchanging atoms over a long range, while preserving detailed balance. This long-range exchange of atoms renders other frequent parallelization techniques, like domain decomposition, unfavorable due to excessive communication cost. Our ansatz, based on the Metropolis algorithm, minimizes communication between parallel processes. We present this new “partial sequence preserving” (PSP) algorithm, as well as benchmark data for a physical alloy system (NiAl) comprised of one billion atoms.

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