  We discuss the efficiency of parallelization on graphical processing units
(GPUs) for the simulation of the one dimensional Potts model with long range
interactions via parallel tempering. We investigate the behaviour of some
thermodynamic properties, such as equilibrium energy and magnetization,
critical temperatures as well as the separation between the first- and
second-order regime. By implementing multispin coding techniques and an
efficient parallelization of the interaction energy computation among threads,
the GPU-accelerated approach reached speedup factors of up to 37.
