A parallel algorithm is described for computing the minimum spanning tree of an undirected, connected and weighted graph withn vertices. We assume a shared-memory single-instruction-stream, multiple-data-stream model ...
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A parallel algorithm is described for computing the minimum spanning tree of an undirected, connected and weighted graph withn vertices. We assume a shared-memory single-instruction-stream, multiple-data-stream model of computation which does not allow read or write conflicts. The algorithm is adaptive in the sense that it usesn 1?e processors and runs inO(n 1+e ) time wheree lies between 0 and 1 and depends on the number of available processors. In view of the obvious Ω(n 2) lower bound on the number of operations required to compute a minimum spanning tree, the algorithm is also cost-optimal.
Given a sequence of n ordered but not sorted b-bit integers, an algorithm is presented to select the kth smallest by reducing the length of the original sequence until only the required kth value of those equal to the...
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Given a sequence of n ordered but not sorted b-bit integers, an algorithm is presented to select the kth smallest by reducing the length of the original sequence until only the required kth value of those equal to the kth remain. The parallel selection algorithm proposed has optimalcost, and like Akl's (1984) algorithm, it is adaptive. However, the algorithm is designed for the tree machine and thus has the advantage of being well suited to very large scale integration implementation. Also, if the number of leaves is equal to one, an optimal sequential algorithm is obtained that is conceptually simpler than that of Blum, Floyd, Pratt, Rivest, and Tarjan (1972).
A parallel algorithm for generating all combinations ofm out ofn items in lexicographic order is presented. The algorithm usesm processors and runs inO(nCm) time. The cost of the algorithm, which is the parallel runni...
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A parallel algorithm for generating all combinations ofm out ofn items in lexicographic order is presented. The algorithm usesm processors and runs inO(nCm) time. The cost of the algorithm, which is the parallel running time multiplied by the number of processors used, is optimal to within a constant multiplicative factor in view of the Ω(ncm*m) lower bound on the number of operations required to solve this problem using a sequential computer.
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