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dc.contributor.authorGutenkunst, Ryan N
dc.date.accessioned2021-06-11T02:21:51Z
dc.date.available2021-06-11T02:21:51Z
dc.date.issued2021
dc.identifier.citationGutenkunst, R. N. (2021). Dadi.CUDA: Accelerating Population Genetics Inference with Graphics Processing Units. Molecular Biology and Evolution, 38(5), 2177–2178.en_US
dc.identifier.pmid33480999
dc.identifier.doi10.1093/molbev/msaa305
dc.identifier.urihttp://hdl.handle.net/10150/659873
dc.description.abstractdadi is a popular but computationally intensive program for inferring models of demographic history and natural selection from population genetic data. I show that running dadi on a Graphics Processing Unit can dramatically speed computation compared with the CPU implementation, with minimal user burden. Motivated by this speed increase, I also extended dadi to four- and five-population models. This functionality is available in dadi version 2.1.0, https://bitbucket.org/gutenkunstlab/dadi/. © 2021 The Author(s).en_US
dc.language.isoenen_US
dc.publisherOxford University Pressen_US
dc.rights© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/).en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.subjectGPU Computingen_US
dc.subjectdadien_US
dc.subjectDemographic historyen_US
dc.subjectPopulation Geneticsen_US
dc.titledadi.CUDA: Accelerating Population Genetics Inference with Graphics Processing Unitsen_US
dc.typeArticleen_US
dc.identifier.eissn1537-1719
dc.contributor.departmentDepartment of Molecular and Cellular Biology, University of Arizonaen_US
dc.identifier.journalMolecular Biology and Evolutionen_US
dc.description.noteOpen access articleen_US
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en_US
dc.eprint.versionFinal published versionen_US
dc.source.journaltitleMolecular biology and evolution
dc.source.volume38
dc.source.issue5
dc.source.beginpage2177
dc.source.endpage2178
refterms.dateFOA2021-06-11T02:21:51Z
dc.source.countryUnited States
dc.source.countryUnited States


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© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/).
Except where otherwise noted, this item's license is described as © The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/).