  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.
