Non-volatile memory-based activation function

Analog memory-based activation functions using non-volatile memory devices address inefficiencies in digital circuits by performing activation operations directly in the memory array, enhancing energy efficiency and computational speed in deep learning neural networks.

GB2638643BActive Publication Date: 2026-07-02INTERNATIONAL BUSINESS MACHINE CORPORATION
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Patent Information

Application Number
GB2025009616
Authority / Receiving Office
GB · GB
Patent Type
Patents
Current Assignee / Owner
Filing Date
2023-11-07
Publication Date
2026-07-02
Estimated Expiration
2043-11-07

AI Technical Summary

Technical Problem

Existing digital circuits for implementing activation functions in deep learning neural networks are inefficient in terms of energy consumption and require data movement, which hinders performance.

Method used

Implementing analog memory-based activation functions using non-volatile memory devices, such as memristive elements, to perform activation operations directly in the memory array, eliminating the need for data movement and reducing energy consumption.

Benefits of technology

This approach enhances energy efficiency and computational speed by performing activation functions in-place within the memory array, reducing the need for digital conversion and lowering overall energy usage.

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Abstract

Analog memory-based activation function for an artificial neural network can be provided. An apparatus can include at least two non-volatile memory devices connected in parallel such that the current
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Citation Information

Patent Citations

  • ReLU type memristor simulator

    CN113054947A

  • Artificial XOR dendrite based on memristor hybrid integration and implementation method thereof

    CN113822422A

  • Analog hardware implementation of activation functions

    US20220138548A1