title: gPGA: GPU Accelerated Population Genetics Analyses.
abstract: BACKGROUND
  The isolation with migration (IM) model is important for studies in population genetics and phylogeography. IM program applies the IM model to genetic data drawn from a pair of closely related populations or species based on Markov chain Monte Carlo (MCMC) simulations of gene genealogies. But computational burden of IM program has placed limits on its application.
  
  
  METHODS
  With strong computational power, Graphics Processing Unit (GPU) has been widely used in many fields. In this article, we present an effective implementation of IM program on one GPU based on Compute Unified Device Architecture (CUDA), which we call gPGA.
  
  
  CONCLUSIONS
  Compared with IM program, gPGA can achieve up to 52.30X speedup on one GPU. The evaluation results demonstrate that it allows datasets to be analyzed effectively and rapidly for research on divergence population genetics. The software is freely available with source code at https://github.com/chunbaozhou/gPGA.
authors.affiliation: Supercomputing Center, Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100190, China.
authors.forename: Chunbao
authors.initials: C
authors.lastname: Zhou
authors.affiliation: Supercomputing Center, Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100190, China.
authors.forename: Xianyu
authors.initials: X
authors.lastname: Lang
authors.affiliation: Supercomputing Center, Computer Network Information Center, Chinese Academy of Sciences, Beijing, 100190, China.
authors.forename: Yangang
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
authors.forename: Chaodong
authors.initials: C
authors.lastname: Zhu
mesh_terms: D003196:Computer Graphics; D005828:Genetics, Population / Q000706:statistics & numerical data*; D006801:Humans; D008390:Markov Chains; D009010:Monte Carlo Method; D012984:Software