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大地电磁三维交错网格有限差分数值模拟的并行计算研究 被引量:20

A study on parallel computation for 3D magnetotelluric modeling using the staggered-grid finite difference method
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摘要 为了更有效的提高大地电磁三维正演的计算速度,引入了并行处理技术.大地电磁三维交错网格有限差分数值模拟是按照不同频率来计算的,各频率之间求取电磁场值的过程是相互独立的.根据这一特点,可以将多个频率的计算任务平均划分为一个或者几个频率的计算子任务,分配到各个计算节点去并行执行,计算完成后将结果汇总.本文通过采用主从并行模式、分频并行计算的方案,在曙光TC5000A高性能并行平台上实现了基于MPI的大地电磁三维正演的并行计算.通过两个理论模型对实现的大地电磁三维正演并行算法进行试算,对比分析了多个节点机下程序的执行效率.测试结果表明,所实现的三维正演并行算法是正确的、高效的,为进一步的大地电磁三维反演并行算法研究奠定了重要基础. Computation time and memory requirements are two common problems for magnetotelluric modeling of three-dimensional conductivity structures.We develop a new parallel processing scheme that can efficiently improve the computational speed of 3D magnetotelluric modeling.The scheme of 3D megnetotelluric modeling based on the staggered-grid finite difference method is implemented in frequency domain,and the calculation process of the EM field for each frequency is independent.Therefore,considering the naturally parallelizable character,the whole computation burden of all frequencies can be divided into many minor calculation tasks for single or multiple frequencies,which will be assigned to different computing nodes and parallelly calculated.In this paper,by adopting master-slave parallel mode and parallel computation with frequencies scheme,we have implemented the parallel computation of 3D MT modeling using MPI on TC5000A high-performance parallel platform.Furthermore,we tested our parallel algorithm of 3D MT modeling using two 3D theoretical models and analyzed the calculation efficiency on a multiple-nodes computer,and the results show that the parallel algorithm is effective and efficient,which lays a solid foundation for subsequent three-dimensional parallel magnetotelluric inversion.
出处 《地球物理学报》 SCIE EI CAS CSCD 北大核心 2012年第12期4036-4043,共8页 Chinese Journal of Geophysics
基金 国家深部专项(SinoProbe-01) 国家自然科学基金(40974040) 湖北省自然科学基金(2011CDA123)联合资助
关键词 大地电磁 三维正演数值模拟 交错采样有限差分 并行算法 MPI Magnetotelluric 3D forward modeling Staggered-grid finite difference Parallel algorithm MPI
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