Surfing the Wavefront of Genome Alignment

Pairwise sequence alignment represents a fundamental step in genome and molecular analysis applications, accounting for most of their runtime. Given the quadratic time complexity of alignment algorithms, the community presses for the development of more efficient algorithms. Moreover, current limitations of general-purpose architectures push users to use hardware accelerators to reduce the analysis time. In this context, we present an FPGA implementation of the Wavefront Alignment (WFA) algorithm, a recently introduced solution that exploits homologous regions between the sequences to speed up the alignment process and whose complexity is related to the score of the alignment, rather than to the lengths of the sequences. Our multicore design can achieve up to 8.09 x improvement in speedup and 57.77 x in energy efficiency compared to the multi-threaded software implementation run on a Xeon Gold Processor. Moreover, our design highly outperforms the current State-of-the-Art hardware-accelerated solution, reaching up to 2876 Giga Cell Updates Per Second (GCUPS) and 68.47 GCUPS/W on a single FPGA, with an improvement of up to 2.29 x and 9.90 x in terms of performance and energy efficiency, respectively.