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Approximate Content-Addressable Memories: A Review

Esteban Garzón, Leonid Yavits, Adam Teman, Marco Lanuzza

2023Chips15 citationsDOIOpen Access PDF

Abstract

Content-addressable memory (CAM) has been part of the memory market for more than five decades. CAM can carry out a single clock cycle lookup based on the content rather than an address. Thanks to this attractive feature, CAM is utilized in memory systems where a high-speed content lookup technique is required. However, typical CAM applications only support exact matching, as opposed to approximate matching, where a certain Hamming distance (several mismatching characters between a query pattern and the dataset stored in CAM) needs to be tolerated. Recent interest in approximate search has led to the development of new CAM-based alternatives, accelerating the processing of large data workloads in the realm of big data, genomics, and other data-intensive applications. In this review, we provide an overview of approximate CAM and describe its current and potential applications that would benefit from approximate search computing.

Topics & Concepts

Computer scienceContent-addressable memoryContent (measure theory)Feature (linguistics)Matching (statistics)Lookup tableParallel computingTheoretical computer scienceComputer engineeringArtificial intelligenceOperating systemLinguisticsArtificial neural networkPhilosophyMathematical analysisMathematicsStatisticsNetwork Packet Processing and OptimizationCaching and Content DeliveryAdvanced Data Storage Technologies
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