Algorithms for approximate string matching
Information and Control
Introducing efficient parallelism into approximate string matching and a new serial algorithm
STOC '86 Proceedings of the eighteenth annual ACM symposium on Theory of computing
A time-efficient, linear-space local similarity algorithm
Advances in Applied Mathematics
In search of clusters: the coming battle in lowly parallel computing
In search of clusters: the coming battle in lowly parallel computing
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
A linear space algorithm for computing maximal common subsequences
Communications of the ACM
A guided tour to approximate string matching
ACM Computing Surveys (CSUR)
JIAJIA: A Software DSM System Based on a New Cache Coherence Protocol
HPCN Europe '99 Proceedings of the 7th International Conference on High-Performance Computing and Networking
A Parallel Smith-Waterman Algorithm Based on Divide and Conquer
ICA3PP '02 Proceedings of the Fifth International Conference on Algorithms and Architectures for Parallel Processing
Adaptive scheduling of master/worker applications on distributed computational resources
Adaptive scheduling of master/worker applications on distributed computational resources
Space and Time Optimal Parallel Sequence Alignments
IEEE Transactions on Parallel and Distributed Systems
Using a DSM application to locally align DNA sequences
CCGRID '04 Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid
Parallel smith-waterman algorithm for local DNA comparison in a cluster of workstations
WEA'05 Proceedings of the 4th international conference on Experimental and Efficient Algorithms
CUDAlign: using GPU to accelerate the comparison of megabase genomic sequences
Proceedings of the 15th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
BSB'07 Proceedings of the 2nd Brazilian conference on Advances in bioinformatics and computational biology
Long DNA sequence comparison on multicore architectures
Euro-Par'10 Proceedings of the 16th international Euro-Par conference on Parallel processing: Part II
Parallel performance evaluation of multithreaded local sequence alignment
Proceedings of the 12th International Conference on Computer Systems and Technologies
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Biological Sequence Comparison is one of the most important operations in Computational Biology since it is used to determine how similar two sequences are. Smith and Waterman proposed an exact algorithm (SW), based on dynamic programming, that is able to obtain the best local alignment between two sequences in quadratic time and space. In order to compare long biological sequences, SW is rarely used since the computation time and the amount of memory required becomes prohibitive. For this reason, heuristic methods like BLAST are widely used. Although faster, these heuristic methods do not guarantee that the best result will be produced. In this paper, we propose an exact parallel variant of the SW algorithm that obtains the best local alignments in quadratic time and reduced space. The results obtained in two clusters (8-machine and 16-machine) for DNA sequences longer than 32 KBP (kilo base-pairs) were very close to linear and, in some cases, superlinear. For very long DNA sequences (1.6 MBP), we were able to reduce execution time from 12.25 hours to 1.54 hours, in our 8-machine cluster. As far as we know, this is the first time 1.6 MBP sequences are compared with an exact SW variant. In this case, 30240 best local alignments were obtained.