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Motivation: Bioinformatics researchers have a variety of programming languages and architectures at their disposal, and recent advances in graphics processing unit (GPU) computing have added a promising new option. However, many performance comparisons inflate the actual advantages of GPU technology. In this study, we carry out a realistic performance evaluation of SNPrank, a network centrality algorithm that ranks single nucleotide polymorhisms (SNPs) based on their importance in the contextdoi:10.1093/bioinformatics/btq638 pmid:21115438 pmcid:PMC3018810 fatcat:mbseqsmgifgjxasxaypgpb2qau