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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.
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.
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