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

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 specif...

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Bibliographic Details
Published in:ACS/IEEE International Conference on Computer Systems and Applications - AICCSA 2010 pp. 1 - 8
Main Authors: Ben Mabrouk, Bchira, Hasni, Hamadi, Mahjoub, Zaher
Format: Conference Proceeding
Language:English
Published: IEEE 01.05.2010
Subjects:
Arrays
Artificial neural networks
bioinformatics
Complexity theory
dependence analysis
dynamic program-ming
greedy approch
Lead
longest common subsequence
loop nest
makespan
parallel algorithm
Phase change random access memory
scheduling
unimodular transformation
ISBN:9781424477166, 1424477166
ISSN:2161-5322
Online Access:Get full text
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Summary: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.
ISBN:9781424477166
1424477166
ISSN:2161-5322
DOI:10.1109/AICCSA.2010.5587006