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Motivation: Analysis of large biological data sets using a variety of parallel processor computer architectures is a common task in bioinformatics. The efficiency of the analysis can be significantly improved by properly handling redundancy present in these data combined with taking advantage of the unique features of these compute architectures. Results: We describe a generalized approach to this analysis, but present specific results using the program CEPAR, an efficient implementation of thedoi:10.1093/bioinformatics/bth184 pmid:15044237 fatcat:mv4x6dkgdfgprpfcmulel2fxyi