Neural network algorithm oriented analog perception computing architecture

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...

AI Technical Summary

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 classification and the high energy consumption of the ASIC, the present invention provides an analog sensing algorithm oriented to the neural network algorithm. computing architecture

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