Reproducible large-scale social simulations on various computing environment

In this paper, we propose parallel computing techniques for reproducible large-scale social simulations on various computing environments including CPU (Central Processing Unit) or GPU (Graphic Processing Unit). When we use computing resources for large-scale social simulations, the reproducibility of a simulation should be considered. 'Reproducibility' means the same trial of a simulation can be repeated. If the same computing resources are available to repeat the trial, it is easy to reproduce the same simulation results. When not all the same computing resources are available, however, it becomes difficult to obtain the same trial since random number generators may become different from the original computation resources. In this study, we employ multi-thread computing on CPU or GPU. We propose two models to run reproducible social simulations on CPU or GPU. One is to parallelize trials (Trial Parallelization). The other is to parallelize agents of a single simulation (Agent Parallelization). These models can be ensured reproducibility even in different computing resources. Our experimental results show that the same computing processes are obtained on CPU or GPU. When we parallelize large-scale social simulation on CPU or GPU, we can accelerate the simulation as a secondary effect.