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Cost-efficient parallel programs based on set-distributions for polynomial interpolation

机译:基于集合分布的具有成本效益的多项式插值并行程序

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The paper presents parallel algorithms for Lagrange and Hermite interpolation methods formally derived from specifications, and using set-distributions. Set-distributions are based on set-valued mappings, and they assign a data object to more than one process. The derivation from specifications assures the correctness, and the set-distributions assure the efficiency of the programs. The obtained parallel algorithms have very good time complexities and speeds-up, and they are also cost-efficient. We consider the number of processes p to be a parameter of the algorithms, so, bounded parallelism is considered. The derivation of the algorithms is not ruled by any particular interconnection network. The possible mappings on different networks could be evaluated. The performance analysis is done considering a full-connected network, and other two interconnection networks: hypercube and multi-mesh hypercube, which preserve the cost-efficiency of the algorithms.
机译:本文提出了从规范中正式导出并使用集分布的Lagrange和Hermite插值方法的并行算法。集分布基于集值映射,它们将一个数据对象分配给多个进程。规格的派生确保了正确性,而集合分布则确保了程序的效率。所获得的并行算法具有很好的时间复杂度和速度,并且还具有成本效益。我们认为进程数p是算法的参数,因此考虑了有界并行性。算法的推导不受任何特定的互连网络的管辖。可以评估不同网络上的可能映射。在考虑全连接网络和其他两个互连网络(超立方体和多网格超立方体)的情况下进行了性能分析,这保留了算法的成本效益。

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