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sPEGG: high throughput eco-evolutionary simulations on commodity graphics processors

Kenichi W. Okamoto, Priyanga Amarasekare
Department of Ecology and Evolutionary Biology, University of California, Los Angeles
arXiv:1603.09255 [q-bio.QM], (30 Mar 2016)

@article{okamoto2016spegg,

   title={sPEGG: high throughput eco-evolutionary simulations on commodity graphics processors},

   author={Okamoto, Kenichi W. and Amarasekare, Priyanga},

   year={2016},

   month={mar},

   archivePrefix={"arXiv"},

   primaryClass={q-bio.QM}

}

Integrating population genetics into community ecology theory is a major goal in ecology and evolution, but analyzing the resulting models is computationally daunting. Here we describe sPEGG (simulating Phenotypic Evolution on General Purpose Graphics Processing Units (GPGPUs)), an open-source, multi-species forward-time population genetics simulator. Using a single commodity GPGPU instead of a single central processor, we find sPEGG can accelerate eco-evolutionary simulations by a factor of over 200, comparable to performance on a small-to-medium sized computer cluster.
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