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Related Experiment Video

Updated: Sep 9, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Published on: March 9, 2019

Charge-domain content addressable memory based on ferroelectric capacitive memory for reliable and energy-efficient

Zuopu Zhou¹, Hongtao Zhong², Leming Jiao¹

¹Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.

Nature Communications

|August 28, 2025

Summary

This study introduces a novel charge-domain ferroelectric capacitive memory CAM for faster, more reliable Hamming distance computation in memory augmented neural networks. This innovation enhances efficient learning from minimal data.

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Gradient Echo Quantum Memory in Warm Atomic Vapor

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Published on: November 11, 2013

Area of Science:

Materials Science
Computer Engineering
Artificial Intelligence

Background:

Non-volatile content addressable memories (NV-CAMs) are crucial for accelerating memory augmented neural networks (MANNs) and enabling few-shot learning.
Existing NV-CAMs often operate in the current domain, leading to challenges in reliable, low-power, and sensing-friendly Hamming distance (HD) computation.

Purpose of the Study:

To address the limitations of current-domain NV-CAMs by proposing a novel charge-domain computation approach.
To introduce the first charge-domain 2-transistor ferroelectric capacitive memory (2FCM) CAM based on inversion-type FCM.

Main Methods:

Data is stored as device capacitance within the 2FCM CAM structure.
The CAM directly outputs HD as linear multi-level voltages, simplifying sensing and reducing peripheral costs.
Differential operation provides immunity to device variations for accurate long data vector computation.

Main Results:

Experimental demonstration of parallel 16-bit HD computation using a fabricated 16x16 2FCM CAM array.
Achieved record performance at the array level for charge-domain computation.
Validated the accuracy and efficiency of the proposed CAM for in-memory search applications.

Conclusions:

The proposed charge-domain 2FCM CAM offers a superior alternative to current-domain NV-CAMs for MANNs.
This technology significantly enhances reliability, power efficiency, and sensing simplicity for HD computation.
The demonstrated performance showcases the potential of charge-domain computation for advanced in-memory search applications.