The Community for Technology Leaders
Green Image
Issue No. 04 - April (2012 vol. 23)
ISSN: 1045-9219
pp: 579-588
Tiffany M. Mintz , University of South Carolina, Columbia
Jason D. Bakos , University of South Carolina, Columbia
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.
Biology and genetics, distributed systems, parallelism and concurrency, reconfigurable hardware.

T. M. Mintz and J. D. Bakos, "A Cluster-on-a-Chip Architecture for High-Throughput Phylogeny Search," in IEEE Transactions on Parallel & Distributed Systems, vol. 23, no. , pp. 579-588, 2010.
94 ms
(Ver 3.3 (11022016))