Back to Search Start Over

Capacitive Content-Addressable Memory

Authors :
Yiming Chen
Huazhong Yang
Guodong Yin
Sumitha George
Nuo Xiu
Xiaoyang Ma
Xueqing Li
Source :
ACM Great Lakes Symposium on VLSI
Publication Year :
2021
Publisher :
ACM, 2021.

Abstract

Content-addressable memory (CAM) has been a critical component in pattern matching and also machine-learning applications. Recently emerged CAM that is capable of delivering multi-level distance calculation is promising for applications that need matching results beyond Boolean results of ?matched" and ?not matched". However, existing multi-level CAM designs are constrained by the bit-cell device discharging current mismatch and the strict timing of sensing operations for distance calculation. This fact results in the challenge of further improving the accuracy and scalability towards higher-resolution and higher-dimension matching. This work presents a multi-level CAM design that is capable of delivering high-accuracy and high-scalability search, which is immune to the discharging device mismatch and needs no strict timing for result sensing. The inherent enabler is the charge-domain computing mechanism. This work will present the operating mechanisms, the circuit simulation, and content-matching evaluation results, showing the promise towards high reliability, high energy efficiency, and high scalability.

Details

Database :
OpenAIRE
Journal :
Proceedings of the 2021 on Great Lakes Symposium on VLSI
Accession number :
edsair.doi...........c4cff5a4b109cb50dc4292e59f0764e4
Full Text :
https://doi.org/10.1145/3453688.3461744