In-Memory Computing with Associative Memories: A Cross-Layer Perspective

Associative memories (AMs), which efficiently “associate” input queries with appropriate data words/locations in the memory, are powerful in-memory-computing cores. Harnessing the benefits of AMs requires cross-layer design efforts that span from devices and circuits to architectures and applications. This paper showcases representative AM designs based on different non-volatile memory technologies (resistive RAM (RRAM), ferroelectric FETs (FeFETs), and Flash). End-to-end evaluations for machine learning applications are discussed to demonstrate the benefits derived from each design layer, which can serve as a guide for future research efforts.