Fast hierarchical clustering and other applications of dynamic closest pairs
Journal of Experimental Algorithmics (JEA)
WABI '08 Proceedings of the 8th international workshop on Algorithms in Bioinformatics
Debunking the 100X GPU vs. CPU myth: an evaluation of throughput computing on CPU and GPU
Proceedings of the 37th annual international symposium on Computer architecture
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Distance estimators are needed as input for popular distance based phylogenetic reconstruction methods such as UPGMA and neighbour-joining. Computation of these takes O(n2l) time for n sequences with length l which is usually fast compared to reconstructing a phylogenetic tree of n taxa. However, with the introduction of fast search heuristics for distance based phylogenetic reconstruction methods, the computation of distance estimators has become a bottleneck especially for long sequences. Elias et al. have shown how distance estimators can be computed efficiently from unaligned nucleotide sequences using vectorisation of code. In this paper we extend their method to allow efficient computation of distance estimators from aligned nucleotide and amino acid sequences using vectorisation of code and parallelisation on both CPUs and GPUs. Experiments are presented which show an increase in performance of up to 36x and 8x relative to the naive approach when computing distance estimators from nucleotides and amino acids alignments respectively.