Year: 2020
Type: article
Abstract: Extracting insight from population genetic data often demands computationally intensive modeling. dadi is a popular program for fitting models of demographic history and natural selection to such data. Here, I show that running dadi on a Graphics Processing Unit (GPU) can speed computation by orders of magnitude compared to the CPU implementation, with minimal user burden. This speed increase enables the analysis of more complex models, which motivated the extension of dadi to four- and five-population models. Remarkably, dadi performs almost as well on inexpensive consumer-grade GPUs as on expensive server-grade GPUs. GPU computing thus offers large and accessible benefits to the community of dadi users. This functionality is available in dadi version 2.1.0, https://bitbucket.org/gutenkunstlab/dadi/ .
Source: Molecular Biology and Evolution
Author: Ryan N Gutenkunst
Institution: University of Arizona
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $3,418
OpenAlex ID: W3124674487