Serializing neural network computing unit
By using a neural network computing unit with serialized input and low-precision storage elements, the problem of limited efficiency in high-precision converter circuits in existing technologies is solved, and a more efficient computing process is achieved.
Patent Information
- Application Number
- CN202080082888.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Priority Date
- 2020-12-01
- Filing Date
- 2020-12-02
- Publication Date
- 2026-02-27
- Estimated Expiration
- 2040-12-02
AI Technical Summary
Existing neural network computing units require complex high-precision digital-to-analog converter circuits and analog-to-digital converter circuits in their in-memory computing architecture, which limits their efficiency.
By employing a serialized input method, utilizing low-precision storage elements and a 1-bit sensing amplifier, the input is sequentially applied to the storage elements through a control circuit to generate an output current, which is then converted into binary code by an accumulator circuit, simplifying the signal conversion process.
This reduces reliance on high-precision converter circuits, improves computational efficiency and performance, and lowers the demand for high-precision synaptic components.
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Abstract
Citation Information
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