A Low-Power Content-Addressable-Memory Based on Clustered-Sparse-Networks

TL;DR

This paper presents a low-power CAM design using clustered-sparse-networks that reduces energy consumption and search delay by eliminating unnecessary comparisons, leveraging binary-weighted connections for efficient associativity.

Contribution

It introduces a novel CAM architecture based on clustered-sparse-networks that significantly lowers dynamic energy and search delay compared to conventional designs.

Findings

Energy consumption reduced to 9.5% of conventional design

Search delay decreased to 30.4% of conventional design

Slight increase in transistor count by 3.4%

Abstract

A low-power Content-Addressable-Memory (CAM) is introduced employing a new mechanism for associativity between the input tags and the corresponding address of the output data. The proposed architecture is based on a recently developed clustered-sparse-network using binary-weighted connections that on-average will eliminate most of the parallel comparisons performed during a search. Therefore, the dynamic energy consumption of the proposed design is significantly lower compared to that of a conventional low-power CAM design. Given an input tag, the proposed architecture computes a few possibilities for the location of the matched tag and performs the comparisons on them to locate a single valid match. A 0.13 um CMOS technology was used for simulation purposes. The energy consumption and the search delay of the proposed design are 9.5%, and 30.4% of that of the conventional NAND architecture respectively with a 3.4% higher number of transistors.