MTMap: A Long-Read Alignment Tool based on Multi-Core DSPs

Read alignment is a basic and important task in genomic data analysis. The popularity of the third—generation sequencing technology has brought the need of sequence alignment algorithms to analyze long-read sequences with longer read length and high error rate. Moreover, the rapid growth of sequence data has also presented challenges for read alignment. To improve the ability to process large volume of sequencing reads, we developed a long-read sequence alignment algorithm MTMap on the heterogeneous processor FT-m7032. MTMap utilizes multi-level parallel technologies: firstly, we tailored the data structure for the wide vector processing units of DSP to speedup the score matrix computation. Secondly, we developed multithread parallelization for base-level alignment on each DSP cluster. Finally, we implemented multi-process parallelization between DSP clusters to fully exploit the computing power of FT-m7032. Experiments show that, MTMap achieves up to 16 times of parallel acceleration performance compared with the original algorithm under the condition of ensuring accuracy.