Hardware accelerator architecture for simultaneous short-read DNA sequences alignment with enhanced traceback phase

Abstract

Dynamic programming algorithms are widely used to find the optimal sequence alignment between any two DNA sequences. This manuscript presents a new, flexible and scalable hardware accelerator architecture to speedup the implementation of the frequently used Smith–Waterman algorithm. When integrated with a general purpose processor, the developed accelerator significantly reduces the computation time and memory space requirements of alignment tasks. Such efficiency mainly comes from two innovative techniques that are proposed. First, the usage of the maximum score cell coordinates, gathered during the computation of the alignment scores in the matrix-fill phase, in order to significantly reduce the time and memory requirements of the traceback phase. Second, the exploitation of an additional level of parallelism in order to simultaneously align several query sequences with the same reference sequence, targeting the processing of short-read DNA sequences. The results obtained from the implementation of a complete alignment system based on the new accelerator architecture in a Virtex-4 FPGA showed that the proposed techniques are feasible and the developed accelerator is able to provide speedups as high as 16 for the considered test sequences. Moreover, it was also shown that the proposed approach allows the processing of larger DNA sequences in memory restricted environments.