Abstract—The graphic processing unit (GPU) gets strong computing ability with relatively low energy and money consumption, it has been widely used in the field of large-scale simulation and computation. Among which the CPU-GPU heterogeneous collaborative computing model has become an effective ways to solve the simulation performance of large-scale artificial society. But there are lots of problems in GPU-based ABS. The paper proposes a GPU-based conservative parallel discrete event simulation algorithm for ABS. We reorganize data structure for CPU/GPU-based heterogeneous collaborative parallel simulation, design a GPU kernel scheduling algorithm based on conservative time synchronization strategy, propose an efficient organization and scheduling algorithm for simulation event and improve execution efficiency of conservative time synchronization algorithm through the optimization of large-scale parallel time reduction algorithm. Finally, we analyze the algorithms proposed and the GPU-based simulation kernel with GameOfLife model, up to 11.2x speedup is obtained compared to CPU.
Index Terms—Artificial society, ABS, CPU/GPU, heterogeneous collaborative simulation, conservative parallel.
The authors are with the College of Information System and Management, National University of Defense Technology, Changsha, Hunan, P. R. China, 410073 (e-mail: listyle1991@gmail.com)
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Cite: Li Zhen, Qiuxiao Gang, Guo Gang, and Chen Bin, "A GPU-Based Simulation Kernel within Heterogeneous Collaborative Computation on Large-Scale Artificial Society," International Journal of Modeling and Optimization vol. 4, no. 3, pp. 205-210-99, 2014.
