English

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

Quantitative Methods 2016-03-31 v1 Populations and Evolution

Abstract

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\underline{\textrm{s}}\textrm{imulating} Phenotypic\underline{\textrm{P}}\textrm{henotypic} Evolution\underline{\textrm{E}}\textrm{volution} on General Purpose\underline{\textrm{G}}\textrm{eneral Purpose} Graphics Processing Units\underline{\textrm{G}}\textrm{raphics 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.

Keywords

Cite

@article{arxiv.1603.09255,
  title  = {sPEGG: high throughput eco-evolutionary simulations on commodity graphics processors},
  author = {Kenichi W. Okamoto and Priyanga Amarasekare},
  journal= {arXiv preprint arXiv:1603.09255},
  year   = {2016}
}
R2 v1 2026-06-22T13:21:36.744Z