q-State Potts model metastability study using optimized GPU-based Monte Carlo algorithms
Abstract
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 numbers generators to each thread. The implementation allows to simulate systems up to ~10^9 spins with an average time per spin flip of 0.147ns on the fastest GPU card tested, representing a speedup up to 155x, 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 Binder's criterion, namely, on the existence or not of specific heat singularities at spinodal temperatures different of the transition one.
Cite
@article{arxiv.1101.0876,
title = {q-State Potts model metastability study using optimized GPU-based Monte Carlo algorithms},
author = {Ezequiel E. Ferrero and Juan Pablo De Francesco and Nicolás Wolovick and Sergio A. Cannas},
journal= {arXiv preprint arXiv:1101.0876},
year = {2012}
}
Comments
30 pages, 7 figures. Accepted in Computer Physics Communications. code available at: http://www.famaf.unc.edu.ar/grupos/GPGPU/Potts/CUDAPotts.html