q-state Potts model metastability study using optimized GPU-based Monte Carlo algorithms Original Research Article

We implemented a GPU-based parallel code to perform Monte Carlo simulations of the two-dimensional q-state Potts model. The algorithm is based on a checkerboard update scheme and assigns independent random number generators to each thread. The implementation allows to simulate systems up to ∼109 spins with an average time per spin flip of 0.147 ns on the fastest GPU card tested, representing a speedup up to 155×, compared with an optimized serial code running on a high-end CPU. The possibility of performing high speed simulations at large enough system sizes allowed us to provide a positive numerical evidence about the existence of metastability on very large systems based on Binderʼs criterion, namely, on the existence or not of specific heat singularities at spinodal temperatures different of the transition one.