Study of a GPU-based parallel computing method for the Monte Carlo program

The Monte Carlo method can be widely applied to particle transport through numerous simulated data processing operations. However, this process consumes much time. Traditional parallel computing based on multi-CPU or multi-core CPU can effectively address this issue, but it is limited by inadequate computer hardware. Nonetheless, the current programmability and parallel processing capability of digital graphics processing units (GPUs) can sustain general computing applications such as Monte Carlo program simulation. This paper presents a method that facilitates the parallel computation of the Monte Carlo procedure through GPUs. Its feasibility is verified through a sample of simplified photon transport program, the results indicate that execution time can be shortened by approximately 90 times. Based on the general Monte Carlo program Geant4, the photon and electronic coupled transport module was examined, analyzed, and rewritten using the GPU programming language OpenCL to generate a Geant4 parallel tool [base on GPU parallel computing tool (BOGPT)]. The simulation results of the standard examples demonstrated that the outcomes of the BOGPT program are similar to those of Geant4 and the simulation time can be reduced by approximately three times. Finally, the GPU programming-based parallel computing method for Monte Carlo applications is accelerated and implementation prospects are broadened following further optimization. (authors)