Parallelization of the dynamic programming algorithm for solving the longest common subsequence problem

Authors:
Bchira Ben Mabrouk;Hamadi Hasni;Zaher Mahjoub
Affiliations:
École Supérieure des Sciences et des Techniques de Tunis, 1008, Bab Mnara, Tunisie;École Nationale des Sciences de l'Informatique, Campus universitaire, 2010, Manouba, Tunisie;Faculté des Sciences de Tunis, Campus universitaire, Manar 2, 2092, Tunisie
Venue:
AICCSA '10 Proceedings of the ACS/IEEE International Conference on Computer Systems and Applications - AICCSA 2010
Year:
2010

Citing 0
Cited 2

On supernode transformations and multithreading for the longest common subsequence problem

AusPDC '12 Proceedings of the Tenth Australasian Symposium on Parallel and Distributed Computing - Volume 127
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International Journal of Parallel Programming

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Abstract

We address in this paper the design and analysis of cost-optimal parallel algorithms for solving the problem of the longest common subsequence. Starting from the standard sequential dynamic programming algorithm which has the structure of a perfect nest of two embedded loops, we make use of a specific three-step parallelization approach consisting in (i) a dependence analysis within the nest ; (ii) the determination of a particular unimodular transformation leading to a new nest whose second loop is parallel ; (iii) the design of two linear time schedulings for the derived parallel algorithm when a given number of processors is available. The first scheduling is fitted to the nest structure while the second is greedy oriented and optimal. The makespans of the two schedulings are explicitly determined. This permits to establish a comparison showing their respective efficiencies.