{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/spegg-high-throughput-eco-evolutionary","title":"sPEGG: high throughput eco-evolutionary simulations on commodity graphics processors","arxiv_id":"1603.09255","date":"2016-03-30","proceeding":null,"authors":[],"abstract":"Integrating population genetics into community ecology theory is a major goal\nin ecology and evolution, but analyzing the resulting models is computationally\ndaunting. Here we describe sPEGG ($\\underline{\\textrm{s}}\\textrm{imulating}$\n$\\underline{\\textrm{P}}\\textrm{henotypic}$\n$\\underline{\\textrm{E}}\\textrm{volution}$ on\n$\\underline{\\textrm{G}}\\textrm{eneral Purpose}$\n$\\underline{\\textrm{G}}\\textrm{raphics Processing Units}$ (GPGPUs)), an\nopen-source, multi-species forward-time population genetics simulator. Using a\nsingle commodity GPGPU instead of a single central processor, we find sPEGG can\naccelerate eco-evolutionary simulations by a factor of over 200, comparable to\nperformance on a small-to-medium sized computer cluster.","url_abs":"http://arxiv.org/abs/1603.09255v1","url_pdf":"http://arxiv.org/pdf/1603.09255v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"spegg-high-throughput-eco-evolutionary","repo_url":"https://github.com/kewok/spegg","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"high","task_name":"Vocal Bursts Intensity Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}