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Capacitive Content-Addressable Memory
- 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.
- Subjects :
- 010302 applied physics
Matching (statistics)
business.industry
Computer science
Reliability (computer networking)
Capacitive sensing
02 engineering and technology
Content-addressable memory
01 natural sciences
020202 computer hardware & architecture
Component (UML)
0103 physical sciences
Scalability
0202 electrical engineering, electronic engineering, information engineering
Pattern matching
business
Computer hardware
Efficient energy use
Subjects
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