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In-Memory Associative Processors: Tutorial, Potential, and Challenges

Mohammed E. Fouda, Hasan Erdem Yantır, Ahmed M. Eltawil, Fadi Kurdahi

2022IEEE Transactions on Circuits & Systems II Express Briefs19 citationsDOI

Abstract

In-memory computing is an emerging computing paradigm that overcomes the limitations of exiting Von-Neumann computing architectures such as the memory-wall bottleneck. In such paradigm, the computations are performed directly on the data stored in the memory, which highly reduces the memory-processor communications during computation. Hence, significant speedup and energy savings could be achieved especially with data-intensive applications. Associative processors (APs) were proposed in the seventies and recently were revived thanks to the high-density memories. In this tutorial brief, we overview the functionalities and recent trends of APs in addition to the implementation of each content-addressable memory with different technologies. The AP operations and runtime complexity are also summarized. We also explain and explore the possible applications that can benefit from APs. Finally, the AP limitations, challenges, and future directions are discussed.

Topics & Concepts

Computer scienceBottleneckVon Neumann architectureContent-addressable memorySpeedupParallel computingComputationComputer architectureIn-Memory ProcessingAssociative propertyMemory managementEmbedded systemSemiconductor memoryComputer hardwareSearch engineArtificial intelligenceOperating systemProgramming languageArtificial neural networkPure mathematicsInformation retrievalMathematicsQuery by ExampleWeb search queryAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNetwork Packet Processing and Optimization
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