Abstract: Monte Carlo method (Monte Carlo, MC) is an important particle transport simulation method in nuclear reactor design and analysis. The MC method can simulate complex geometric shapes and the calculation results have high accuracy. The disadvantage is that it takes a lot of time to simulate hundreds of millions of particles to obtain accurate results. How to improve the performance of the Monte Carlo program has become a challenge for large-scale Monte Carlo numerical simulation. Based on the heap MC analysis program RMC, this paper has successively carried out a series of optimization methods such as dynamic memory allocation optimization based on TCMalloc, OpenMP thread scheduling strategy optimization, and vector memory alignment optimization, and parallel I/O optimization based on HDF5. Under the example of calculating 2 million particles, the overall program performance is improved by more than 26.45%.

Key words: Monte Carlo method, performance optimization, memory management, parallel I/O