MrBayes tgMC³: a tight GPU implementation of MrBayes.

MrBayes is model-based phylogenetic inference tool using Bayesian statistics. However, model-based assessment of phylogenetic trees adds to the computational burden of tree-searching, and so poses significant computational challenges. Graphics Processing Units (GPUs) have been proposed as high perfo...

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Autores principales:	Cheng Ling, Tsuyoshi Hamada, Jianing Bai, Xianbin Li, Douglas Chesters, Weimin Zheng, Weifeng Shi
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/611d83443fe24bd9ab2c92e695121f1b
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spelling	oai:doaj.org-article:611d83443fe24bd9ab2c92e695121f1b2021-11-18T07:49:55ZMrBayes tgMC³: a tight GPU implementation of MrBayes.1932-620310.1371/journal.pone.0060667https://doaj.org/article/611d83443fe24bd9ab2c92e695121f1b2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23593277/?tool=EBIhttps://doaj.org/toc/1932-6203MrBayes is model-based phylogenetic inference tool using Bayesian statistics. However, model-based assessment of phylogenetic trees adds to the computational burden of tree-searching, and so poses significant computational challenges. Graphics Processing Units (GPUs) have been proposed as high performance, low cost acceleration platforms and several parallelized versions of the Metropolis Coupled Markov Chain Mote Carlo (MC(3)) algorithm in MrBayes have been presented that can run on GPUs. However, some bottlenecks decrease the efficiency of these implementations. To address these bottlenecks, we propose a tight GPU MC(3) (tgMC(3)) algorithm. tgMC(3) implements a different architecture from the one-to-one acceleration architecture employed in previously proposed methods. It merges multiply discrete GPU kernels according to the data dependency and hence decreases the number of kernels launched and the complexity of data transfer. We implemented tgMC(3) and made performance comparisons with an earlier proposed algorithm, nMC(3), and also with MrBayes MC(3) under serial and multiply concurrent CPU processes. All of the methods were benchmarked on the same computing node from DEGIMA. Experiments indicate that the tgMC(3) method outstrips nMC(3) (v1.0) with speedup factors from 2.1 to 2.7×. In addition, tgMC(3) outperforms the serial MrBayes MC(3) by a factor of 6 to 30× when using a single GTX480 card, whereas a speedup factor of around 51× can be achieved by using two GTX 480 cards on relatively long sequences. Moreover, tgMC(3) was compared with MrBayes accelerated by BEAGLE, and achieved speedup factors from 3.7 to 5.7×. The reported performance improvement of tgMC(3) is significant and appears to scale well with increasing dataset sizes. In addition, the strategy proposed in tgMC(3) could benefit the acceleration of other Bayesian-based phylogenetic analysis methods using GPUs.Cheng LingTsuyoshi HamadaJianing BaiXianbin LiDouglas ChestersWeimin ZhengWeifeng ShiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 4, p e60667 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Cheng Ling Tsuyoshi Hamada Jianing Bai Xianbin Li Douglas Chesters Weimin Zheng Weifeng Shi MrBayes tgMC³: a tight GPU implementation of MrBayes.
description	MrBayes is model-based phylogenetic inference tool using Bayesian statistics. However, model-based assessment of phylogenetic trees adds to the computational burden of tree-searching, and so poses significant computational challenges. Graphics Processing Units (GPUs) have been proposed as high performance, low cost acceleration platforms and several parallelized versions of the Metropolis Coupled Markov Chain Mote Carlo (MC(3)) algorithm in MrBayes have been presented that can run on GPUs. However, some bottlenecks decrease the efficiency of these implementations. To address these bottlenecks, we propose a tight GPU MC(3) (tgMC(3)) algorithm. tgMC(3) implements a different architecture from the one-to-one acceleration architecture employed in previously proposed methods. It merges multiply discrete GPU kernels according to the data dependency and hence decreases the number of kernels launched and the complexity of data transfer. We implemented tgMC(3) and made performance comparisons with an earlier proposed algorithm, nMC(3), and also with MrBayes MC(3) under serial and multiply concurrent CPU processes. All of the methods were benchmarked on the same computing node from DEGIMA. Experiments indicate that the tgMC(3) method outstrips nMC(3) (v1.0) with speedup factors from 2.1 to 2.7×. In addition, tgMC(3) outperforms the serial MrBayes MC(3) by a factor of 6 to 30× when using a single GTX480 card, whereas a speedup factor of around 51× can be achieved by using two GTX 480 cards on relatively long sequences. Moreover, tgMC(3) was compared with MrBayes accelerated by BEAGLE, and achieved speedup factors from 3.7 to 5.7×. The reported performance improvement of tgMC(3) is significant and appears to scale well with increasing dataset sizes. In addition, the strategy proposed in tgMC(3) could benefit the acceleration of other Bayesian-based phylogenetic analysis methods using GPUs.
format	article
author	Cheng Ling Tsuyoshi Hamada Jianing Bai Xianbin Li Douglas Chesters Weimin Zheng Weifeng Shi
author_facet	Cheng Ling Tsuyoshi Hamada Jianing Bai Xianbin Li Douglas Chesters Weimin Zheng Weifeng Shi
author_sort	Cheng Ling
title	MrBayes tgMC³: a tight GPU implementation of MrBayes.
title_short	MrBayes tgMC³: a tight GPU implementation of MrBayes.
title_full	MrBayes tgMC³: a tight GPU implementation of MrBayes.
title_fullStr	MrBayes tgMC³: a tight GPU implementation of MrBayes.
title_full_unstemmed	MrBayes tgMC³: a tight GPU implementation of MrBayes.
title_sort	mrbayes tgmc³: a tight gpu implementation of mrbayes.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/611d83443fe24bd9ab2c92e695121f1b
work_keys_str_mv	AT chengling mrbayestgmc3atightgpuimplementationofmrbayes AT tsuyoshihamada mrbayestgmc3atightgpuimplementationofmrbayes AT jianingbai mrbayestgmc3atightgpuimplementationofmrbayes AT xianbinli mrbayestgmc3atightgpuimplementationofmrbayes AT douglaschesters mrbayestgmc3atightgpuimplementationofmrbayes AT weiminzheng mrbayestgmc3atightgpuimplementationofmrbayes AT weifengshi mrbayestgmc3atightgpuimplementationofmrbayes
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MrBayes tgMC³: a tight GPU implementation of MrBayes.

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