A parallel approximate string matching under Levenshtein distance on graphics processing units using warp-shuffle operations

Approximate string matching with k-differences has a number of practical applications, ranging from pattern recognition to computational biology. This paper proposes an efficient memory-access algorithm for parallel approximate string matching with k-differences on Graphics Processing Units (GPUs)....

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Veröffentlicht in:PloS one Jg. 12; H. 10; S. e0186251
Hauptverfasser: Ho, ThienLuan, Oh, Seung-Rohk, Kim, HyunJin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States Public Library of Science 10.10.2017
Public Library of Science (PLoS)
Schlagworte:
Algorithms
Approximate string matching
Architectural engineering
Base Sequence
Bioinformatics
Biology and Life Sciences
Cloud computing
Computational biology
Computational Biology - methods
Computer and Information Sciences
Computer applications
Computer engineering
Computer Graphics
Computer memory
Deoxyribonucleic acid
DNA
DNA - analysis
Electrical engineering
Electronics industry
Engineering and Technology
Field programmable gate arrays
Graphics processing units
International conferences
Pattern recognition
Physical Sciences
Proteins
Research and Analysis Methods
Software
Technology application
Warp
Workloads
South Korea
ISSN:1932-6203, 1932-6203
Online-Zugang:Volltext
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Zusammenfassung:Approximate string matching with k-differences has a number of practical applications, ranging from pattern recognition to computational biology. This paper proposes an efficient memory-access algorithm for parallel approximate string matching with k-differences on Graphics Processing Units (GPUs). In the proposed algorithm, all threads in the same GPUs warp share data using warp-shuffle operation instead of accessing the shared memory. Moreover, we implement the proposed algorithm by exploiting the memory structure of GPUs to optimize its performance. Experiment results for real DNA packages revealed that the performance of the proposed algorithm and its implementation archived up to 122.64 and 1.53 times compared to that of sequential algorithm on CPU and previous parallel approximate string matching algorithm on GPUs, respectively.
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Competing Interests: The authors have declared that no competing interests exist.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0186251