A Non-volatile Near-Memory Read Mapping Accelerator

DNA sequencing is the physical or biochemical process of identifying the location of the four bases (Adenine, Guanine, Cytosine, Thymine) in a DNA strand. As semiconductor technology revolutionized computing, DNA sequencing technology (termed Next Generation Sequencing, NGS) revolutionized genomic research. Modern NGS platforms can sequence hundreds of millions of short DNA fragments in parallel. The output short DNA fragments from NGS platforms are termed reads. Mapping each output read to a reference genome of the same species (i.e., read mapping) is a common critical first step in a rich and diverse set of emerging bioinformatics applications. The importance of read mapping motivated various sequence alignment and mapping algorithms, which start to fall short of tackling the growing scale of the problem. Mapping represents a search-heavy memory-intensive operation and barely requires complex floating point arithmetic, therefore, can greatly benefit from in- or near-memory processing, where non-volatile memory can accommodate the large memory footprint in an area and energy efficient manner. This paper introduces a scalable, energy-efficient high-throughput near (non-volatile) memory read mapping accelerator: BioMAP. Instead of optimizing an algorithm developed for general-purpose computers or GPUs, BioMAP rethinks the algorithm and accelerator design together from the ground up. Thereby BioMAP can improve the throughput of read mapping by 4.0 times while reducing the energy consumption by 26.2 times when compared to a highly-optimized algorithm for modern GPUs.