The parallel computation of time-dependent Monte Carlo transport

Parallel Monte Carlo methods are successful because particles are typically independent and easily distributed to multiple processors. For time-dependent Monte Carlo particle transport problem, due to the communication of each time-step about scattering source attribute and meshes, it reduces the parallel efficiency and limits enlarge of parallel scale. We research parallel computation of two types of time-dependent particle transport problems. Adaptive processor assignment in parallel computation and three parallel I/O models with low-cost communication are presented. The optimized processor choice is obtained. We propose a scheme that is based upon Monte Carlo layered sample technique. It is used to treat communication of scattering source. The parallel expandability is greatly improved. The large speedups over the basic methods are obtained.