Assessment of the parallelization approach of d2_cluster for high-performance sequence clustering
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Published on: June 28, 2018
John E Carpenter1, Alan Christoffels, Yael Weinbach
1SGI, 655E Lone Oak Drive, Eagan, Minnesota 55121, USA.
Journal of Computational Chemistry
|April 12, 2002
Abstract:
The exponential increase in expressed sequence tag (EST) sequence data amplifies the computational cost of clustering sequences such that new algorithms are required to analyze data at a greater rate. We have parallelized d2_cluster on a SGI Origin 2000 multiprocessor and observed a speedup of approximately 100x on 126 processors when processing a 15,876 EST dataset. The parallelized d2_cluster code is obtainable from the SANBI website (http://www.sanbi.ac.za/CODES).