PARC: A Processing-in-CAM Architecture for Genomic Long Read Pairwise Alignment using ReRAM

Technological advances in long read sequences have greatly facilitated the development of genomics. However, managing and analyzing the raw genomic data that outpaces Moore's Law requires extremely high computational efficiency. On the one hand, existing software solutions can take hundreds of CPU hours to complete human genome alignment. On the other hand, the recently proposed hardware platforms achieve low processing throughput with significant overhead. In this paper, we propose PARC, an Processing-in-Memory architecture for long read pairwise alignment leveraging emerging resistive CAM (content-addressable memory) to accelerate the bottleneck chaining step in DNA alignment. Chaining takes 2-tuple anchors as inputs and identifies a set of correlated anchors as potential alignment candidates. Unlike traditional main memory which organizes relational data structure in a linear address space, PARC stores tuples in two neighboring crossbar arrays with shared row decoder such that column-wise in-memory computational operations and row-wise memory accesses can be performed in-situ in a symmetric crossbar structure. Compared to both software tools and state-of-the-art accelerators, PARC shows significant improvement in alignment throughput and energy efficiency, thanks to the in-site computation capability and optimized data mapping.