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

Ryan N. Gutenkunst

doi:10.1093/molbev/msaa305

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

Ryan N. Gutenkunst

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

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/.

Original language	English (US)
Pages (from-to)	2177-2178
Number of pages	2
Journal	Molecular biology and evolution
Volume	38
Issue number	5
DOIs	https://doi.org/10.1093/molbev/msaa305
State	Published - May 1 2021
Externally published	Yes

Keywords

GPU computing
dadi
demographic history
population genetics

ASJC Scopus subject areas

Ecology, Evolution, Behavior and Systematics
Molecular Biology
Genetics

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10.1093/molbev/msaa305

Cite this

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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/.",

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KW - population genetics

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

Abstract

Keywords

ASJC Scopus subject areas

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