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Having greater computational power on the desktop for processing taxa data sets has been a dream of biologists/statisticians involved in phylogenetics data analysis. Many existing algorithms have been highly optimized-one example being Felsenstein's PHYLIP code, written in C, for UPGMA and neighbor joining algorithms. However, the ability to process more than a few tens of taxa in a reasonable amount of time using conventional computers has not yielded a satisfactory speedup in data processing, making it difficult for phylogenetics practitioners to quickly explore data sets-such as might be done from a laptop computer. We discuss the application of custom computing techniques to phylogenetics. In particular, we apply this technology to speed up UPGMA algorithm execution by a factor of a hundred, against that of PHYLIP code running on the same PC. We report on these experiments and discuss how custom computing techniques can be used to not only accelerate phylogenetics algorithm performance on the desktop, but also on larger, high-performance computing engines, thus enabling the high-speed processing of data sets involving thousands of taxa.