dadi.CUDA: Accelerating Population Genetics Inference with Graphics Processing Units
Affiliation
Department of Molecular and Cellular Biology, University of ArizonaIssue Date
2021Metadata
Show full item recordPublisher
Oxford University PressCitation
Gutenkunst, R. N. (2021). Dadi.CUDA: Accelerating Population Genetics Inference with Graphics Processing Units. Molecular Biology and Evolution, 38(5), 2177–2178.Journal
Molecular Biology and EvolutionRights
© 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/).Collection Information
This 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.Abstract
dadi 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).Note
Open access articleEISSN
1537-1719PubMed ID
33480999Version
Final published versionScopus Count
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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/).