New Processor Array Architecture for DNA Sequence Alignment Using Stevens-Song Algorithm

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Abstract: This paper proposes a new processor array architecture for an optimized parallel sequence alignment algorithm. This architecture is extracted by applying a nonlinear mapping methodology to the Stevens-Song optimized algorithm after expressing it as Regular Iterative Algorithm (RIA). This methodology uses a data scheduling and node projection techniques to explore the processor array architectures of the algorithm. The proposed architecture is one of the explored architectures and has the advantage that it can be modified to be reused for multiple pass processing in order to increase the number of processing elements that can be packed into a single FPGA and to increase the number of sequences that can be aligned in parallel in a single FPGA. This resolves the potential problem of many FPGA resources left unused for designs that have large values of short read length when using the previously published conventional hardware design. FPGA implementation results show that, for large values of short read lengths (M > 128), the proposed design has a slightly higher speed up and FPGA utilization over the the conventional one.

WSEAS Transactions on Circuits and Systems, ISSN / E-ISSN: 1109-2734 / 2224-266X, Volume 14, 2015, Art. #37

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Atef Ibrahim, Hamed Elsimary, Abdullah Aljumah, Fayez Gebali, "New Processor Array Architecture for DNA Sequence Alignment Using Stevens-Song Algorithm," WSEAS Transactions on Circuits and Systems, vol. 14, pp. 320-330, 2015, DOI:
Atef Ibrahim, Hamed Elsimary, Abdullah Aljumah, Fayez Gebali. New Processor Array Architecture for DNA Sequence Alignment Using Stevens-Song Algorithm. WSEAS Transactions on Circuits and Systems. 2015;14:320-330.
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