GPU accelerated Monte Carlo simulation of the 2D and 3D Ising model

0021-9991/$ see front matter 2009 Elsevier Inc doi:10.1016/j.jcp.2009.03.018 q The consumer graphics card GeForce GTX 280 fr * Corresponding author. Address: Department of P 7, D-55099 Mainz, Germany. E-mail address: [email protected] (T. Preis). The compute unified device architecture (CUDA) is a programming approach for performing scientific calculations on a graphics processing unit (GPU) as a data-parallel computing device. The programming interface allows to implement algorithms using extensions to standard C language. With continuously increased number of cores in combination with a high memory bandwidth, a recent GPU offers incredible resources for general purpose computing. First, we apply this new technology to Monte Carlo simulations of the two dimensional ferromagnetic square lattice Ising model. By implementing a variant of the checkerboard algorithm, results are obtained up to 60 times faster on the GPU than on a current CPU core. An implementation of the three dimensional ferromagnetic cubic lattice Ising model on a GPU is able to generate results up to 35 times faster than on a current CPU core. As proof of concept we calculate the critical temperature of the 2D and 3D Ising model using finite size scaling techniques. Theoretical results for the 2D Ising model and previous simulation results for the 3D Ising model can be reproduced. 2009 Elsevier Inc. All rights reserved.