Abstract

A content-addressable memory compares an input search word against all rows of stored words in an array in a highly parallel manner. While supplying a very powerful functionality for many applications in pattern matching and search, it suffers from large area, cost and power consumption, limiting its use. Past improvements have been realized by using memristors to replace the static random-access memory cell in conventional designs, but employ similar schemes based only on binary or ternary states for storage and search. We propose a new analog content-addressable memory concept and circuit to overcome these limitations by utilizing the analog conductance tunability of memristors. Our analog content-addressable memory stores data within the programmable conductance and can take as input either analog or digital search values. Experimental demonstrations, scaled simulations and analysis show that our analog content-addressable memory can reduce area and power consumption, which enables the acceleration of existing applications, but also new computing application areas.

Designing low power and high performance content-addressable memory remains a challenge. Here, the authors demonstrate a content-addressable memory concept and circuit which leverages the analog conductance tunability of memristors, reduces power consumption, and enables new functionalities and applications.

Details

Title
Analog content-addressable memories with memristors
Author
Li, Can 1   VIAFID ORCID Logo  ; Graves, Catherine E 1   VIAFID ORCID Logo  ; Xia, Sheng 1 ; Miller, Darrin 2   VIAFID ORCID Logo  ; Foltin, Martin 2 ; Pedretti Giacomo 3 ; Strachan, John Paul 1   VIAFID ORCID Logo 

 Hewlett Packard Enterprise, Hewlett Packard Labs, Palo Alto, USA (GRID:grid.474602.3) (ISNI:0000 0004 4909 3316) 
 Hewlett Packard Enterprise, Silicon Design Lab, Fort Collins, USA (GRID:grid.474602.3) (ISNI:0000 0004 4909 3316) 
 Hewlett Packard Enterprise, Hewlett Packard Labs, Palo Alto, USA (GRID:grid.474602.3) (ISNI:0000 0004 4909 3316); Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria, Milan, Italy (GRID:grid.4643.5) (ISNI:0000 0004 1937 0327) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2386368801
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.