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Issue No.04 - April (2012 vol.23)
pp: 579-588
Tiffany M. Mintz , University of South Carolina, Columbia
Jason D. Bakos , University of South Carolina, Columbia
ABSTRACT
In this paper, we describe an FPGA-based coprocessor architecture that performs a high-throughput branch-and-bound search of the space of phylogenetic trees corresponding to the number of input taxa. Our coprocessor architecture is designed to accelerate maximum-parsimony phylogeny reconstruction for gene-order and sequence data and is amenable to both exhaustive and heuristic tree searches. Our architecture exposes coarse-grain parallelism by dividing the search space among parallel processing elements (PEs) and each PE exposes fine-grain memory parallelism for their lower-bound computation, the kernel computation performed by each PE. Inter-PE communication is performed entirely on-chip. When using this coprocessor for maximum-parsimony reconstruction for gene-order data, our coprocessor achieves a 40X improvement over software in search throughput, corresponding to a 14X end-to-end application improvement when including all communication and systems overheads.
INDEX TERMS
Biology and genetics, distributed systems, parallelism and concurrency, reconfigurable hardware.
CITATION
Tiffany M. Mintz, Jason D. Bakos, "A Cluster-on-a-Chip Architecture for High-Throughput Phylogeny Search", IEEE Transactions on Parallel & Distributed Systems, vol.23, no. 4, pp. 579-588, April 2012, doi:10.1109/TPDS.2010.191
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