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 Garzon, Leonid Yavits

Research output: Contribution to journalArticlepeer-review

Abstract

GCOC is a genome classification system-on-chip (SoC) that classifies genomes by <italic>k</italic>-mer matching, an approach that divides a DNA query sequence into a set of short DNA fragments of size <italic>k</italic>, 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 <italic>k</italic>-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 3.12mm2 and its power consumption is 1.27mW. 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.

Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalIEEE Transactions on Biomedical Circuits and Systems
Early online date28 Aug 2024
DOIs
StateE-pub ahead of print - 28 Aug 2024

Bibliographical note

Publisher Copyright:
IEEE

Keywords

  • Bioinformatics
  • CAM
  • Cams
  • Content-Addressable Memory
  • DNA
  • Genome Classification
  • Genomics
  • Hamming Distance Similarity Search
  • Pathogens
  • Random access memory
  • Sequential analysis

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