AI RESEARCH
A Fast and Energy-Efficient Latch-Based Memristive Analog Content-Addressable Memory
arXiv CS.LG
•
ArXi:2605.11847v1 Announce Type: cross Analog content-addressable memories (aCAMs) based on memristors provide a promising pathway toward energy-efficient large-scale associative computing for Edge AI and embedded intelligence applications. They have been successfully applied to decision-tree inference and extend the capabilities of compute-in-memory (CIM) architectures beyond conventional vector-matrix multiplication. However, conventional designs such as the 6T2M architecture suffer from static search power, limited voltage gain, and pronounced match-line crosstalk, cons