Mahdi Taheri - Department of Information and Communication Technology, Tallinn University of Technology, Tallinn ۱۹۰۸۶, Estonia
Hamed Zandevakili - Reliable and Smart Systems Lab (RSS), Shahid Bahonar University of Kerman, Kerman ۷۶۱۶۹۱۳۴۳۹, Iran
Ali Mahani - Reliable and Smart Systems Lab (RSS), Shahid Bahonar University of Kerman, Kerman ۷۶۱۶۹۱۳۴۳۹, Iran

It is crucial to detect potential overlaps between any pair of the input reads and a reference genome in genome sequencing, but it takes an excessive amount of time, especially for ultra-long reads. Even though lots of acceleration designs are proposed for different sequencing methods, several crucial drawbacks impact these methods. One of these difficulties stems from the difference in read lengths that may take place as input data. In this work, we propose a new Race-logic implementation of the seed extension kernel of the BWA-MEM alignment algorithm. The first proposed method does not need reconfiguration to execute the seed extension kernel for different read lengths. We use MEMRISTORs instead of the conventional, complementary metal-oxide-semiconductor (CMOS), which leads to lower area overhead and power consumption. Also, we benefit from Field-Programmable Nanowire Interconnect Architecture as our matrix output resulting in a flexible output that bypasses the reconfiguration procedure of the system for reads with different lengths. Considering the power, area, and delay efficiency, we gain better results than other state-of-the-art implementations. Consequently, we gain up to ۲۲x speedup compared to the state-of-the-art systolic arrays, ۶۰۰x speed up considering different seed lengths of the previous state-of-the-art proposed methods, at least ۱۰x improvements in area overhead, and ۱۰۵x improvements in power.

Bioinformatics, BWA-MEM, memristor, Race logic