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Parallel computing for globally optimal decision making on cluster systems

机译:集群系统中全局最优决策的并行计算

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摘要

This paper presents a new scheme for parallel computations on cluster systems for time-consuming problems of globally optimal decision making. This uniform scheme (without any centralized control processor) is based on the idea of multidimensional problem reduction. Using same new multiple mappings (of the Peano curve type), a multidimensional problem is reduced to a family of univariate problems which can be solved in parallel in such a way that each of these processors shares the information obtained by the other processors.
机译:本文提出了一种用于集群系统并行计算的新方案,用于解决全局最优决策的耗时问题。这种统一的方案(没有任何集中控制处理器)基于多维问题减少的思想。使用相同的新的(Peano曲线类型的)多重映射,多维问题被简化为一类单变量问题,可以以这些处理器中的每一个共享其他处理器获得的信息的方式并行解决。

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