Hardware Architecture and Computational Flow of Binary Weighted Convolutional Neural Network Accelerator
A binary weight convolution and neural network technology, which is applied to the hardware architecture and calculation process of the binary weight convolution neural network dedicated accelerator, to achieve the effects of reducing access, improving efficiency, and reducing power consumption
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment Construction
[0039] Embodiments of the invention are described in detail below, examples of which are illustrated in the accompanying drawings. Firstly, the necessary overall hardware architecture is introduced, and then the optimized calculation process based on this hardware architecture is introduced. The implementations described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limitations of the present invention.
[0040] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", "vertical", "horizontal" etc. The orientation or positional relationship is only a simplified description for the convenience of describing the present invention, and does not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com