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Parallel time and space upper-bounds for the subset-sum problem

机译:子集和问题的并行时空上限

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摘要

Three new parallel scalable algorithms for solving the Subset-Sum Problem in O(n/p(C-w{sub}(min))) time and O(n + c) space in the PRAM model are presented, where n is the number of objects, c is the capacity, w{sub}(min) is the smallest weight and p is the number of processors. These time and space bounds are better than the direct parallelization of Bellman's algorithm, which was the most efficient known result.
机译:提出了三种新的并行可扩展算法,用于解决O(n / p(Cw {sub}(min)))时间和PRAM模型中O(n + c)空间中的子集和问题,其中n是对象,c是容量,w {sub}(min)是最小的权重,p是处理器的数量。这些时间和空间界限比Bellman算法的直接并行化效果更好,后者是最有效的已知结果。

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