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In this study, the multi-threading performance of the Geant4, MCNP6, and PHITS codes was evaluated as a function of the number of threads (N) and the complexity of the tetrahedral-mesh phantom. For this, three tetrahedral-mesh phantoms of varying complexity (simple, moderately complex, and highly complex) were prepared and implemented in the three different Monte Carlo codes, in photon and neutron transport simulations. Subsequently, for each case, the initialization time, calculation time, and memory usage were measured as a function of the number of threads used in the simulation. It was found that for all codes, the initialization time significantly increased with the complexity of the phantom, but not with the number of threads. Geant4 exhibited much longer initialization time than the other codes, especially for the complex phantom (MRCP). The improvement of computation speed due to the use of a multi-threaded code was calculated as the speed-up factor, the ratio of the computation speed on a multi-threaded code to the computation speed on a single-threaded code. Geant4 showed the best multi-threading performance among the codes considered in this study, with the speed-up factor almost linearly increasing with the number of threads, reaching ~30 when N = 40. PHITS and MCNP6 showed a much smaller increase of the speed-up factor with the number of threads. For PHITS, the speed-up factors were low when N = 40. For MCNP6, the increase of the speed-up factors was better, but they were still less than ~10 when N = 40. As for memory usage, Geant4 was found to use more memory than the other codes. In addition, compared to that of the other codes, the memory usage of Geant4 more rapidly increased with the number of threads, reaching as high as ~74 GB when N = 40 for the complex phantom (MRCP). It is notable that compared to that of the other codes, the memory usage of PHITS was much lower, regardless of both the complexity of the phantom and the number of threads, hardly increasing with the number of threads for the MRCP.
Han et al. (Tue,) studied this question.