DNA sequence alignment: hybrid parallel programming on a multicore cluster

DNA sequence alignment is one of the most important operations of computational biology. In 1981, Smith and Waterman developed a method for sequences local alignment. Due to its computational power and memory requirements, various heuristics have been developed to reduce execution time at the expens...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Rucci, Enzo, De Giusti, Armando Eduardo, Chichizola, Franco, Naiouf, Marcelo, De Giusti, Laura Cristina
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	2011
Materias:	Ciencias Informáticas Bioinformatics Sequence alignment Parallel algorithms Multicore cluster Pipeline computing
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/83228
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-83228
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Ciencias Informáticas Bioinformatics Sequence alignment Parallel algorithms Multicore cluster Pipeline computing
spellingShingle	Ciencias Informáticas Bioinformatics Sequence alignment Parallel algorithms Multicore cluster Pipeline computing Rucci, Enzo De Giusti, Armando Eduardo Chichizola, Franco Naiouf, Marcelo De Giusti, Laura Cristina DNA sequence alignment: hybrid parallel programming on a multicore cluster
topic_facet	Ciencias Informáticas Bioinformatics Sequence alignment Parallel algorithms Multicore cluster Pipeline computing
description	DNA sequence alignment is one of the most important operations of computational biology. In 1981, Smith and Waterman developed a method for sequences local alignment. Due to its computational power and memory requirements, various heuristics have been developed to reduce execution time at the expense of a loss of accuracy in the result. This is why heuristics do not ensure that the best alignment is found. For this reason, it is interesting to study how to apply the computer power of different parallel platforms to speed up the sequence alignment process without losing result accuracy. In this article, a new parallelization strategy (HI-M) of Smith-Waterman algorithm on a multi-core cluster is presented, configuring a pipeline with a hybrid communication model. Additionally, a performance analysis is carried out and compared with two previously presented parallel solutions. Finally, experimental results are presented, as well as future research lines.
format	Objeto de conferencia Objeto de conferencia
author	Rucci, Enzo De Giusti, Armando Eduardo Chichizola, Franco Naiouf, Marcelo De Giusti, Laura Cristina
author_facet	Rucci, Enzo De Giusti, Armando Eduardo Chichizola, Franco Naiouf, Marcelo De Giusti, Laura Cristina
author_sort	Rucci, Enzo
title	DNA sequence alignment: hybrid parallel programming on a multicore cluster
title_short	DNA sequence alignment: hybrid parallel programming on a multicore cluster
title_full	DNA sequence alignment: hybrid parallel programming on a multicore cluster
title_fullStr	DNA sequence alignment: hybrid parallel programming on a multicore cluster
title_full_unstemmed	DNA sequence alignment: hybrid parallel programming on a multicore cluster
title_sort	dna sequence alignment: hybrid parallel programming on a multicore cluster
publishDate	2011
url	http://sedici.unlp.edu.ar/handle/10915/83228
work_keys_str_mv	AT ruccienzo dnasequencealignmenthybridparallelprogrammingonamulticorecluster AT degiustiarmandoeduardo dnasequencealignmenthybridparallelprogrammingonamulticorecluster AT chichizolafranco dnasequencealignmenthybridparallelprogrammingonamulticorecluster AT naioufmarcelo dnasequencealignmenthybridparallelprogrammingonamulticorecluster AT degiustilauracristina dnasequencealignmenthybridparallelprogrammingonamulticorecluster
bdutipo_str	Repositorios
_version_	1764820488407744514

DNA sequence alignment: hybrid parallel programming on a multicore cluster

Ejemplares similares