Simulating Lattice Spin Models on Graphics Processing Units

Abstract

Lattice spin models are useful for studying critical phenomena and allow the extraction of equilibrium and dynamical properties. Simulations of such systems are usually based on Monte Carlo (MC) techniques, and the main difficulty is often the large computational effort needed when approaching critical points. In this work, it is shown how such simulations can be accelerated with the use of NVIDIA graphics processing units (GPUs) using the CUDA programming architecture. We have developed two different algorithms for lattice spin models, the first useful for equilibrium properties near a second-order phase transition point and the second for dynamical slowing down near a glass transition. The algorithms are based on parallel MC techniques, and speedups from 70- to 150-fold over conventional single-threaded computer codes are obtained using consumer-grade hardware.

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Cited by in corpus (8)

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• GPU-based Swendsen-Wang multi-cluster algorithm for the simulation of two-dimensional classical spin systems
• Highly optimized simulations on single- and multi-GPU systems of 3D Ising spin glass
• A GPU-based Large-scale Monte Carlo Simulation Method for Systems with Long-range Interactions
• Reaction-diffusion model Monte Carlo simulations on the GPU
• Report: GPU Based Massive Parallel Kawasaki Kinetics In Monte Carlo Modelling of Lipid Microdomains