An FPGA-based systolic array to accelerate the BWA-MEM genomic mapping algorithm

Abstract

We present the first accelerated implementation of BWA-MEM, a popular genome sequence alignment algorithm widely used in next generation sequencing genomics pipelines. The Smith-Waterman-like sequence alignment kernel requires a significant portion of overall execution time. We propose and evaluate a number of FPGA-based systolic array architectures, presenting optimizations generally applicable to variable length Smith-Waterman execution. Our kernel implementation is up to 3× faster, compared to software-only execution. This translates into an overall application speedup of up to 45%, which is 96% of the theoretically maximum achievable speedup when accelerating only this kernel.