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- W3046335004 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." @default.
- W3046335004 created "2020-08-07" @default.
- W3046335004 creator A5056381387 @default.
- W3046335004 date "2020-07-31" @default.
- W3046335004 modified "2023-10-17" @default.
- W3046335004 title "dadi.CUDA: Accelerating population genetic inference with Graphics Processing Units" @default.
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- W3046335004 doi "https://doi.org/10.1101/2020.07.30.229336" @default.
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