FINDING BICONNECTED COMPONEMTS AND COMPUTING TREE FUNCTIONS IN LOGARITHMIC PARALLEL TIME Extended Summary

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Názov: FINDING BICONNECTED COMPONEMTS AND COMPUTING TREE FUNCTIONS IN LOGARITHMIC PARALLEL TIME Extended Summary
Prispievatelia: The Pennsylvania State University CiteSeerX Archives
Zdroj: http://www.mpi-inf.mpg.de/departments/d1/teaching/ws10/models_of_computation/Tarjan, Vishkin - 1984 - Finding biconnected components and computing tree functions in logarithmic parallel time.pdf.
Zbierka: CiteSeerX
Predmety: Parallel graph algorithm, biconnected components
Popis: In this paper we propose a new algorithm for finding the blocks (biconnected components) of an undirected graph. A serial implementation runs in O(n+m) time and space on a graph of n vertices and m edges. 4 parallel implementation runs in O(log n) time and O(n+m) space using O(n+m) processors on a concurrent-read, concurrent-write parallel RAM. An alternative implementation runs in Obn2/p3 time and O(n2) space using any number p C n /log n of processors, on a concurrent-read, exclusive-write parallel RAM. The latter algorithm has optimal speedup, assuming an adjacency matrix representation of the input. A general algorithmic technique which simplifies and improves computation of various functions on trees is introduced. This technique typically requires o(1og n) time using o(n) processors and O(n) space on an exclusive-read exclusive-write parallel RAM.
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Jazyk: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.419.3088
Dostupnosť: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.419.3088
http://www.mpi-inf.mpg.de/departments/d1/teaching/ws10/models_of_computation/Tarjan, Vishkin - 1984 - Finding biconnected components and computing tree functions in logarithmic parallel time.pdf
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Prístupové číslo: edsbas.7EC111B4
Databáza: BASE
Popis
Abstrakt:In this paper we propose a new algorithm for finding the blocks (biconnected components) of an undirected graph. A serial implementation runs in O(n+m) time and space on a graph of n vertices and m edges. 4 parallel implementation runs in O(log n) time and O(n+m) space using O(n+m) processors on a concurrent-read, concurrent-write parallel RAM. An alternative implementation runs in Obn2/p3 time and O(n2) space using any number p C n /log n of processors, on a concurrent-read, exclusive-write parallel RAM. The latter algorithm has optimal speedup, assuming an adjacency matrix representation of the input. A general algorithmic technique which simplifies and improves computation of various functions on trees is introduced. This technique typically requires o(1og n) time using o(n) processors and O(n) space on an exclusive-read exclusive-write parallel RAM.