PARALLEL ACCELERATION ALGORITHM FOR SPIN MODELS

Abstract
We describe and implement a multi-scale acceleration algorithm for spin models on a massively parallel supercomputer, the Connection Machine CM-200. Unlike usual cluster algorithms, our algorithm is completely parallelizable. The time to update all variables in a system of volume Ld scales as Ld log 2L. We prove this by computing the time for one lattice sweep for the 2-d XY model for our algorithm on lattices of size up to 2048×2048.

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