A New Algorithm for Reducing Communication Cost of Time-dependent Monte Carlo Transport

L. Deng, W. Zhang, H. Xu, R. Wang, Z. Huang, and S. Li (PRC)


Time-dependent, particle transport, adaptive processor assignment, scattering source, and layered sample


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 layered sampling technique for treatment of scattering source communication. It greatly reduces the communication cost. The parallel expandability is obviously improved. The larger speedup over the basic algorithm is obtained.

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