A new algorithm for reducing communication cost of time-dependent Monte Carlo transport

Parallel algorithm of time-independent Monte Carlo transport problem is successful because particles are typically independent and easily distributed to multiple processors. However, for time-dependent Monte Carlo 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 two algorithms. Where adaptive processor assignment and the optimized processor choice are obtained. We propose a scheme that is based upon Monte Carlo stratified sampling technique for treatment of scattering source cornmunication. It greatly reduces the communication cost. The parallel scalability is obviously improved. The larger speedup over the basic algorithm is obtained.