Hamming Distance Tolerant Content-Addressable Memory (HD-CAM) for DNA Classification

IEEE Access

卷:10

Adam Teman¹  Zuher Jahshan¹  Esteban Garzon²  Leonid Yavits²  Natan Vinshtok-Melnik³  Robert Hanhan³  Marco Lanuzza⁴  Roman Golman⁴ 

[1] Systems (EnICS) Labs, Faculty of Engineering, Bar-Ilan University, Ramat-Gan, Israel;

[2] Department of Computer Engineering, Modeling, Electronics and Systems, University of Calabria, Rende, Italy;

[3] Department of Electrical Engineering, Technion-Israel Institute of Technology, Haifa, Israel;

[4] Emerging Nanoscaled Integrated Circuits &x0026;

关键词: Approximate search;    content addressable memory;    DNA classification;    hamming distance (HD);   

DOI  :  10.1109/ACCESS.2022.3158305

来源: DOAJ

【 摘 要 】

This paper proposes a novel Hamming distance tolerant content-addressable memory (HD-CAM) for energy-efficient in-memory approximate matching applications. HD-CAM exploits NOR-type based static associative memory bitcells, where we add circuitry to enable approximate search with programmable tolerance. HD-CAM implements approximate search using matchline charge redistribution rather than its rise or fall time, frequently employed in state-of-the-art solutions. HD-CAM was designed in a 65 $\mathrm { \text {n} \text {m} }$ 1.2 $\mathrm { \text {V}}$ CMOS technology and evaluated through extensive Monte Carlo simulations. Our analysis shows that HD-CAM supports robust operation under significant process variations and changes in the design parameters, enabling a wide range of mismatch threshold (tolerable Hamming distance) levels and pattern lengths. HD-CAM was functionally evaluated for virus DNA classification, which makes HD-CAM suitable for hardware acceleration of genomic surveillance of viral outbreaks, such as Covid-19 pandemics.

【 授权许可】

Unknown