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A Parallel Domain Decomposition FDTD Algorithm Based on Cloud Computing

机译:基于云计算的平行域分解FDTD算法

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This paper presents a parallel domain decomposition finite difference time domain (DD-FDTD) algorithm based on MapReduce architectural pattern in a Hadoop cloud computing cluster. The algorithm is implemented on a 6-nodes Hadoop laboratory test cloud computing cluster to compute the electromagnetic fields of lightning in the downtown area in Shanghai city, PR China. The speedup ratio under different numbers of computational sub domains is evaluated. It shows that the maximum speedup ratio of the algorithm implemented on our Hadoop cluster is about 2.4, which will increase with the scale of the mesh model and the nodes of the Hadoop cluster.
机译:本文介绍了基于Hadoop云计算群集中MapReduce架构模式的并行域分解有限差分时域(DD-FDTD)算法。该算法在6个节点Hadoop实验室测试云计算集群上实现,以计算PR中国上海市市中心区的闪电电磁场。评估不同数量的计算子域下的加速比。它表明,在我们的Hadoop集群上实现的算法的最大加速度约为2.4,这将随网格模型的比例和Hadoop集群的节点增加。

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