Parallel UPGMA Algorithm on Graphics Processing Units Using CUDA

Abstract

The construction of phylogenetic trees is important for the computational biology, especially for the development of biological taxonomies. UPGMA is one of the most popular heuristic algorithms for constructing ultrametric trees (UT). Although the UT constructed by the UPGMA often is not a true tree unless the molecular clock assumption holds, the UT is still useful for the clocklike data. However, a fundamental problem with the previous implementations of this method is its limitation to handle large tax a sets within a reasonable time. In this paper, we present GPU-UPGMA which can provide a fast construction of very large datasets for biologists. Experimental results show that GPU-UPGMA obtains about 95 times speedup on NVIDIA Tesla C2050 GPU over the 2.13 GHz CPU implementation.