期刊论文详细信息
IEEE Access 卷:10
Hamming Distance Tolerant Content-Addressable Memory (HD-CAM) for DNA Classification
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   

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