MC程序并行设计及提高加速比措施  

THE PARALLEL DESIGN OF MONTE CARLO CODE AND MEASURES OF ENHANCE SPEEDUP

作　　者：邓力[1,2] 谢仲生[1] 黄正丰[3] 许海燕[3] 

机构地区：[1]西安交通大学能动学院核能工程系 [2]北京应用物理与计算数学研究所,北京100088 [3]北京应用物理与计算数学研究所

出　　处：《计算物理》2001年第2期177-180,共4页Chinese Journal of Computational Physics

摘　　要：MC程序的并行设计涉及算法及模块划分 ,它直接关系到并行加速效率的高低 .中子 γ耦合输运蒙特卡罗程序MCNP经过并行改造 ,实现了PVM和MPI两种系统下的并行化 .由于作了模块化设计 ,并行加速效率极佳 .PVM版和MPI版并行程序在多个处理器下的加速比均呈线性增长 .相比PVM ,MPI的适应性更强 ,多数情况下其效率高于PVM ,并行MCNP程序的计算结果可靠 .MPI并行程序在 16、32和 6 4个处理器上的并行效率分别达到了 99%、97%和 89%The parallel design of Monte Carlo code involves computational method and module designs,which is crucial to the parallel efficiency.The coupled of neutron and photon transport Monte Carlo code MCNP has been realized the parallelization in PVM and MPI by modifying the serial code.Due to the form having module being optimized, the parallel efficiency is good where the efficiency of MPI code is stronger than that of PVM code and the speedup of MPI code is higher than that of PVM in most cases.The calculated results of parallel code are reasonable.Both the speedups of PVM code and MPI code have been the linear increasing with the processors.The parallel efficiencies are up to 99% in 16\|processors,97% in 32\|processors and 89% in 64\|processors respectively. [

关 键 词：MPI PVM 并行加速比 MONTE Carlo 并行设计 蒙特卡罗法 程序设计 

分 类 号：O242.2[理学—计算数学] O246[理学—数学]