Heterogeneous hardware/software acceleration of the BWA-MEM DNA alignment algorithm

The fast decrease in cost of DNA sequencing has resulted in an enormous growth in available genome data, and hence led to an increasing demand for fast DNA analysis algorithms used for diagnostics of genetic disorders, such as cancer. One of the most computationally intensive steps in the analysis is represented by the DNA read alignment. In this paper, we present an accelerated version of BWA-MEM, one of the most popular read alignment algorithms, by implementing a heterogeneous hardware/software optimized version on the Convey HC2ex platform. A challenging factor of the BWA-MEM algorithm is the fact that it consists of not one, but three computationally intensive kernels: SMEM generation, suffix array lookup and local Smith-Waterman. Obtaining substantial speedup is hence contingent on accelerating all of these three kernels at once. The paper shows an architecture containing two hardware-accelerated kernels and one kernel optimized in software. The two hardware kernels of suffix array lookup and local Smith-Waterman are able to reach speedups of 2.8x and 5.7x, respectively. The software optimization of the SMEM generation kernel is able to achieve a speedup of 1.7x. This enables a total application acceleration of 2.6x compared to the original software version.