6533b7d0fe1ef96bd125b937
RESEARCH PRODUCT
GPU accelerated Monte Carlo simulations of lattice spin models
Taras Yavors'kiiMartin Weigelsubject
cluster algorithmsStatistical Mechanics (cond-mat.stat-mech)Computer scienceComputationNumerical analysisspin modelsMonte Carlo methodHigh Energy Physics - Lattice (hep-lat)FOS: Physical sciencesStatistical mechanicsGPU computingPhysics and Astronomy(all)Computational Physics (physics.comp-ph)generalized-ensemble simulationsMonte Carlo simulationsComputational scienceCUDAHigh Energy Physics - LatticeSpin modelGeneral-purpose computing on graphics processing unitsGraphicsPhysics - Computational PhysicsCondensed Matter - Statistical Mechanicsdescription
We consider Monte Carlo simulations of classical spin models of statistical mechanics using the massively parallel architecture provided by graphics processing units (GPUs). We discuss simulations of models with discrete and continuous variables, and using an array of algorithms ranging from single-spin flip Metropolis updates over cluster algorithms to multicanonical and Wang-Landau techniques to judge the scope and limitations of GPU accelerated computation in this field. For most simulations discussed, we find significant speed-ups by two to three orders of magnitude as compared to single-threaded CPU implementations.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2011-07-27 |