A Coarse-Grained Reconfigurable Processor for Sequencing and Phylogenetic Algorithms in Bioinformatics
Reconfigurable Computing and FPGAs, International Conference on (2011)
Cancun, Quintana Roo Mexico
Nov. 30, 2011 to Dec. 2, 2011
A coarse-grained reconfigurable processor tailored for accelerating multiple bioinformatics algorithms is proposed. In this paper, a programmable and scalable architectural platform instantiates an array of coarse grained light weight processing elements, which allows arbitrary partitioning, scheduling schemes and capable of solving complete four popular bioinformatics algorithms: the Needleman-Wunsch, Smith-Waterman, and HMMER on sequencing, and Maximum Likelihood on phylogenetic. The key difference of the proposed CGRA based solution compared to FPGA and GPU based solutions is a much better match on architecture and algorithms for the core computational needs, as well as the system level architectural needs. For the same degree of parallelism, we provide a 5X to 14X speed-up improvements compared to FPGA solutions and 15X to 78X compared to GPU acceleration on 3 sequencing algorithms. We also provide 2.8X speed-up compared to FPGA with the same amount of core logic and 70X compared to GPU with the same silicon area for Maximum Likelihood.
Bioinformatics, Coarse Grained Reconfigurable Architecture, Needleman Wunsch, Smith Waterman, HMMER, Maximum Likelihood, Phylogenetic Inference, VLSI
A. Hemani, K. Paul, F. O. Ebrahim and P. Liu, "A Coarse-Grained Reconfigurable Processor for Sequencing and Phylogenetic Algorithms in Bioinformatics," 2011 International Conference on Reconfigurable Computing and FPGAs (ReConFig 2011)(RECONFIG), Cancun, 2011, pp. 190-197.