dadi.CUDA: Accelerating Population Genetics Inference with Graphics Processing Units

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Author
Gutenkunst, Ryan N
Affiliation
Department of Molecular and Cellular Biology, University of Arizona
Issue Date
2021
Keywords
GPU Computing
dadi
Demographic history
Population Genetics

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Publisher
Oxford University Press
Citation
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 Evolution
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/).
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 article
EISSN
1537-1719
PubMed ID
33480999
DOI
10.1093/molbev/msaa305
Version
Final published version
Collections
© 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/).