排序矩阵选择与搜索的高效并行算法

R. Sarnath, Xin He
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引用次数: 16

摘要

为更一般版本的众所周知的选择和搜索问题制定了并行算法。当元素集可以表示为具有排序行和列的n*n矩阵时,作者会考虑这些问题。在EREW PRAM上使用O(n/log nlog* n)个处理器,选择算法需要O(logloglog * n)时间。在CREW PRAM上使用O(n/loglog)个处理器,搜索算法需要O(loglog)时间,这是最优的。作者还证明,在c>或=1的情况下,使用最多n log/sup c/ n个处理器的算法都不能比Omega (log log n)更快地解决矩阵搜索问题。
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Efficient parallel algorithms for selection and searching on sorted matrices
Parallel algorithms for more general versions of the well known selection and searching problems are formulated. The authors look at these problems when the set of elements can be represented as an n*n matrix with sorted rows and columns. The selection algorithm takes O(lognloglogn log* n) time with O(n/log nlog* n) processors on an EREW PRAM. The searching algorithm takes O(loglogn) time with O(n/loglogn) processors on a CREW PRAM, which is optimal. The authors also show that no algorithm using at most n log/sup c/ n processors, c>or=1, can solve the matrix search problem in time faster than Omega (log log n).<>
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