PARALLEL SIMULATION OF LARGE-SCALE ARTIFICIAL SOCIETY WITH GPU AS COPROCESSOR

Abstract

Large-scale artificial societies with millions or billions of agents call for high-performance parallel simulation. Prevailing supercomputers with thousands of CPUs and GPUs make it possible to carry out such simulation. The key is to distribute large-scale agents to massive cores of CPUs and GPUs properly for parallel computing with efficient communication and synchronization. For simplicity and efficiency, a modified discrete event system specification (DEVS) is proposed for large-scale artificial society modeling and parallelism is exploited in agent models because similar agents usually share similar behaviors. Through phased synchronization, a two-tier parallel simulation engine is designed with support of MPI and OpenCL where GPU is used as coprocessor. One-sided communication is used for reflection of remote simulation objects and message passing between processes. A general kernel function prototype is elaborately designed and conditionally compiled for execution on both CPU and GPU. An artificial society for epidemic study is used to test the performance on a supercomputer with 1024 CPU cores and 1792 GPU cores. The speedup reaches 3512 for even 2 billion agents with GPU acceleration which is far over 701 when only CPUs are used. It turns out feasible for parallel simulation of large-scale artificial society with GPU as coprocessor.