GCOC: A Genome Classifier-On-Chip Based on Similarity Search Content Addressable Memory
Yuval Harary, Paz Snapir, Shir Siman Tov, Chen Kruphman, Eyal Rechef, Zuher Jahshan, Esteban Garzón, Leonid Yavits
Abstract
GCOC is a genome classification system-on-chip (SoC) that classifies genomes by $k$-mer matching, an approach that divides a DNA query sequence into a set of short DNA fragments of size k, which are searched in a reference genome database, with the underlying assumption that sequenced DNA reads of the same organism (or its close variants) share most of such $k$-mers. At the core of GCOC is a similarity, or approximate search-capable Content Addressable Memory (SAS-CAM), which in addition to exact match, also supports approximate, or Hamming distance tolerant search. Classification operation is controlled by an embedded RISC-V processor. GCOC classification platform was designed and manufactured in a commercial 65nm process. We conduct a thorough analysis of GCOC classification efficiency as well as its performance, silicon area, and power consumption using silicon measurements. GCOC classifies 769.2K short DNA reads/sec. The silicon area of GCOC SoC is 3.12 $\mathrm{mm}^{2}$ and its power consumption is 1.27 $\mathrm{mW}$. We envision GCOC deployed as a field (for example at points of care) portable classifier where the classification is required to be real-time, easy to operate and energy efficient.