Cargando…

Genetically improved BarraCUDA

BACKGROUND: BarraCUDA is an open source C program which uses the BWA algorithm in parallel with nVidia CUDA to align short next generation DNA sequences against a reference genome. Recently its source code was optimised using “Genetic Improvement”. RESULTS: The genetically improved (GI) code is up t...

Descripción completa

Detalles Bibliográficos
Autores principales: Langdon, W. B., Lam, Brian Yee Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5541657/
https://www.ncbi.nlm.nih.gov/pubmed/28785314
http://dx.doi.org/10.1186/s13040-017-0149-1
_version_ 1783254856635514880
author Langdon, W. B.
Lam, Brian Yee Hong
author_facet Langdon, W. B.
Lam, Brian Yee Hong
author_sort Langdon, W. B.
collection PubMed
description BACKGROUND: BarraCUDA is an open source C program which uses the BWA algorithm in parallel with nVidia CUDA to align short next generation DNA sequences against a reference genome. Recently its source code was optimised using “Genetic Improvement”. RESULTS: The genetically improved (GI) code is up to three times faster on short paired end reads from The 1000 Genomes Project and 60% more accurate on a short BioPlanet.com GCAT alignment benchmark. GPGPU BarraCUDA running on a single K80 Tesla GPU can align short paired end nextGen sequences up to ten times faster than bwa on a 12 core server. CONCLUSIONS: The speed up was such that the GI version was adopted and has been regularly downloaded from SourceForge for more than 12 months.
format Online
Article
Text
id pubmed-5541657
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-55416572017-08-07 Genetically improved BarraCUDA Langdon, W. B. Lam, Brian Yee Hong BioData Min Short Report BACKGROUND: BarraCUDA is an open source C program which uses the BWA algorithm in parallel with nVidia CUDA to align short next generation DNA sequences against a reference genome. Recently its source code was optimised using “Genetic Improvement”. RESULTS: The genetically improved (GI) code is up to three times faster on short paired end reads from The 1000 Genomes Project and 60% more accurate on a short BioPlanet.com GCAT alignment benchmark. GPGPU BarraCUDA running on a single K80 Tesla GPU can align short paired end nextGen sequences up to ten times faster than bwa on a 12 core server. CONCLUSIONS: The speed up was such that the GI version was adopted and has been regularly downloaded from SourceForge for more than 12 months. BioMed Central 2017-08-02 /pmc/articles/PMC5541657/ /pubmed/28785314 http://dx.doi.org/10.1186/s13040-017-0149-1 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Short Report
Langdon, W. B.
Lam, Brian Yee Hong
Genetically improved BarraCUDA
title Genetically improved BarraCUDA
title_full Genetically improved BarraCUDA
title_fullStr Genetically improved BarraCUDA
title_full_unstemmed Genetically improved BarraCUDA
title_short Genetically improved BarraCUDA
title_sort genetically improved barracuda
topic Short Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5541657/
https://www.ncbi.nlm.nih.gov/pubmed/28785314
http://dx.doi.org/10.1186/s13040-017-0149-1
work_keys_str_mv AT langdonwb geneticallyimprovedbarracuda
AT lambrianyeehong geneticallyimprovedbarracuda