Title
A Novel Matchline Scheduling Method for Low-Power and Reliable Search Operation in Cross-Point-Array Nonvolatile Ternary CAM
Abstract
Cross-point-array nonvolatile ternary content-addressable memory (CPA nvTCAM) has recently emerged as an alternative to static random-access-memory-type TCAM, based on increased demands for high-capacity and low-power attributes. The CPA structure has various structural weaknesses such as the searchline (SL) combining with the dischargeline and the minimum line pitch of the matchline (ML). This study analyzes these weaknesses in detail for the first time and resolves the issues caused by these weaknesses using the proposed novel ML shield scheduling method with a matching probability-based flexible searching time technique (MLSS + MPFST). The proposed MLSS + MPFST resolves various issues and achieves greater than sixfold smaller cell size (8F <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) than the non-CPA nvTCAM with the smallest cell size. To verify the proposed schemes, the Monte Carlo HSPICE simulations were performed using a 22-nm industry-compatible bulk FinFET model parameter in 20-nm resistive memory technology at a circuit level, and the gem5 simulations were performed at a system level. The simulation results indicated that the CPA nvTCAM with the proposed MLSS + MPFST achieved a comparable search operation time of 1 ns and a slight power consumption overhead of 10% but an acceptable system performance overhead of less than 0.6% by resolving the various issues, compared with the non-CPA nvTCAM having the best performance.
Year
DOI
Venue
2020
10.1109/TVLSI.2020.3027254
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Keywords
DocType
Volume
Content-addressable memory,coupling noise,cross-point-array structure,matchline (ML) scheduling,searchline (SL) bouncing,ternary content-addressable memory (TCAM)
Journal
28
Issue
ISSN
Citations 
12
1063-8210
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Hyun Kook Park111.38
Hong Keun Ahn201.01
Seong-ook Jung333253.74