A Deterministic Parallel Algorithm for Bipartite Perfect Matching.

A fundamental quest in the theory of computing is to understand the power of randomness. It is not known whether every problem with an efficient randomized algorithm also has one that does not use randomness. One of the extensively studied problems under this theme is that of perfect matching. The p...

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Publicado en:Communications of the ACM Vol. 62; no. 3; pp. 109 - 116
Autores principales: Fenner, Stephen, Gurjar, Rohit, Thierauf, Thomas
Formato: Artículo
Publicado: Association for Computing Machinery Mar2019
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Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2019
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        atl: A Deterministic Parallel Algorithm for Bipartite Perfect Matching.
      aug:
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          Fenner, Stephen
          Gurjar, Rohit
          Thierauf, Thomas
        affil:
          University of South Carolina, Columbia, SC, USA
          California Institute of Technology, Pasadena, CA, USA
          Aalen University, Germany
      su:
        Algorithms
        Bipartite graphs
        Computer science
      sug:
        subj:
          Algorithms
          Bipartite graphs
          Computer science
      ab: A fundamental quest in the theory of computing is to understand the power of randomness. It is not known whether every problem with an efficient randomized algorithm also has one that does not use randomness. One of the extensively studied problems under this theme is that of perfect matching. The perfect matching problem has a randomized parallel (NC) algorithm based on the Isolation Lemma of Mulmuley, Vazirani, and Vazirani. It is a long-standing open question whether this algorithm can be derandomized. In this article, we give an almost complete derandomization of the Isolation Lemma for perfect matchings in bipartite graphs. This gives us a deterministic parallel (quasi-NC) algorithm for the bipartite perfect matching problem. Derandomization of the Isolation Lemma means that we deterministically construct a weight assignment so that the minimum weight perfect matching is unique. We present three different ways of doing this construction with a common main idea.
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      doctype: Article
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    language: English
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