State-of-the-Art in Smith–Waterman Protein Database Search on HPC Platforms View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2016

AUTHORS

Enzo Rucci , Carlos García , Guillermo Botella , Armando De Giusti , Marcelo Naiouf , Manuel Prieto-Matías

ABSTRACT

Searching biological sequence database is a common and repeated task in bioinformatics and molecular biology. The Smith–Waterman algorithm is the most accurate method for this kind of search. Unfortunately, this algorithm is computationally demanding and the situation gets worse due to the exponential growth of biological data in the last years. For that reason, the scientific community has made great efforts to accelerate Smith–Waterman biological database searches in a wide variety of hardware platforms. We give a survey of the state-of-the-art in Smith–Waterman protein database search, focusing on four hardware architectures: central processing units, graphics processing units, field programmable gate arrays and Xeon Phi coprocessors. After briefly describing each hardware platform, we analyse temporal evolution, contributions, limitations and experimental work and the results of each implementation. Additionally, as energy efficiency is becoming more important every day, we also survey performance/power consumption works. Finally, we give our view on the future of Smith–Waterman protein searches considering next generations of hardware architectures and its upcoming technologies. More... »

PAGES

197-223

Book

TITLE

Big Data Analytics in Genomics

ISBN

978-3-319-41278-8
978-3-319-41279-5

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-41279-5_6

DOI

http://dx.doi.org/10.1007/978-3-319-41279-5_6

DIMENSIONS

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