Neural network algorithm oriented analog perception computing architecture

A neural network algorithm and computing architecture technology, which is applied in the field of analog perception computing architecture, can solve the problems of high energy consumption of special digital integrated circuits and the inability to realize feature classification, and achieve the goal of reducing analog-to-digital and digital-to-analog conversion modules and reducing energy consumption Effect

Active Publication Date: 2018-02-09
TSINGHUA UNIV
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Problems solved by technology

[0005] In order to solve the problem that the ASIC in the prior art can only realize the feature extraction of the convolutional neural network, but cannot realize the feature clas

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  • Neural network algorithm oriented analog perception computing architecture
  • Neural network algorithm oriented analog perception computing architecture
  • Neural network algorithm oriented analog perception computing architecture

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[0044] The implementation of the present invention will be described in detail below with reference to the accompanying drawings and embodiments, so as to fully understand how the present invention applies technical means to solve technical problems and achieve the realization process of technical effects and implement them accordingly. It should be noted that, as long as there is no conflict, each embodiment of the present invention and each feature in each embodiment can be combined with each other, and the technical solutions formed are all within the protection scope of the present invention.

[0045] figure 1 It is a block diagram of a neural network algorithm-oriented analog perception computing architecture according to an embodiment of the present invention, the following reference figure 1 The present invention will be described in detail.

[0046] The neural network algorithm-oriented analog perception calculation architecture includes a neuron value buffer 120, an analog ...

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Abstract

The invention discloses a neural network algorithm oriented analog perception computing architecture which comprises a neuron value buffer configured to cache the sample parameters of an object to beanalyzed, a synaptic weight buffer configured to store synaptic weights corresponding to the sample parameters, and an analog computation processing module configured to extract and classify the features of the object to be analyzed in the analog domain according to the synaptic weights and the sample parameters. According to the invention, the features of the object to be analyzed can be extracted and classified, and the sample parameters and the synaptic weights are computed in the analog domain. The architecture has the characteristics of high efficiency. Moreover, the cost of analog-to-digital and digital-to-analog conversion modules is reduced, and the energy consumption is reduced.

Description

Technical field [0001] The present invention relates to the field of artificial intelligence, in particular to a neural network algorithm-oriented analog perception computing architecture. Background technique [0002] In recent years, artificial intelligence (AI) has been booming. As one of the most effective ways to realize artificial intelligence, neural networks have attracted more and more attention from academia and industry. Neural networks have been widely used in the fields of image, video and speech recognition. [0003] Among the many neural networks, Convolutional Neural Network (CNN) and Deep Neural Networks (DNN) are the most widely used. Both CNN and DNN are computationally intensive neural networks. The neural network is large in scale and requires high computing power on the platform. Especially when processing high-dimensional data of images and videos, the data transmission rate may exceed the real-time processing capability of the computing platform , At prese...

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Application Information

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IPC IPC(8): G06N3/063G06N3/04
CPCG06N3/065G06N3/045
Inventor 乔飞贾凯歌刘哲宇魏琦谢福贵刘辛军杨华中
Owner TSINGHUA UNIV
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