MPI+OpenMP环境下的特征函数空间滤值并行化方法研究
Parallel Processing in Eigenfunction-based Spatial Filtering Using MPI+OpenMP Hybrid Parallelization
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摘要: 针对现有的特征函数空间滤值方法存在算法复杂、计算效率低下、难以满足海量空间数据应用需求等问题,提出一种特征函数空间滤值并行化方法。基于主从模型(master/slave模型)和MPI+OpenMP混合编程模式,充分挖掘多核集群下计算机的性能,并在多核集群平台上与纯MPI算法进行了对比实验。结果表明,基于MPI+OpenMP的方法能够获得更高的并行加速比和计算效率。Abstract: Based on the master/slave model,we present a hybrid MPI+OpenMP parallel implementation for the eigenfunction-base spatial filtering on the multi-core cluster.There are two different implementations of the algorithm: one based on MPI and the other based on a hybrid parallel paradigm with MPI+OpenMP.The experimental results show that MPI+OpenMP method can cut down the process-time effectively and improve the filtering efficiency.
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