Processor and processing method applied to sparse neural network

A neural network and processor technology, applied in biological neural network models, inference methods, neural architectures, etc., to save computing power, improve computing efficiency, and speed up computing rates

Inactive Publication Date: 2017-12-29
INST OF COMPUTING TECH CHINESE ACAD OF SCI
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

As the scale of neural network computing circuits increases and the data throughput increases, operating power consumption becomes a serious issue

Method used

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  • Processor and processing method applied to sparse neural network
  • Processor and processing method applied to sparse neural network
  • Processor and processing method applied to sparse neural network

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Embodiment Construction

[0028] In order to make the purpose, technical solution, design method and advantages of the present invention clearer, the present invention will be further described in detail through specific embodiments in conjunction with the accompanying drawings. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0029] Such as figure 1 The general topological diagram of the neural network in the prior art is shown. The neural network is a mathematical model formed by modeling the structure and behavior of the human brain. It is usually divided into structures such as an input layer, a hidden layer, and an output layer. Each layer is It is composed of multiple neuron nodes, and the output value of the neuron nodes in this layer will be passed as input to the neuron nodes in the next layer, and connected layer by layer. The neural network itself has the characteristics of bionics, and...

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Abstract

The invention provides a processor applied to a sparse neural network. The processor includes a storage unit used for storing data and instructions, a control unit used for getting the instructions stored in the storage unit and sending out control signals, and a calculation unit used for getting the node values in a layer of a neural network and corresponding weight value data from the storage unit in order to get the node values in a next layer. When any of elements to be calculated is equal to zero, the calculation unit does not implement the multiplication of the calculation element, wherein the elements to be calculated include node values and weight values. By using the processor of the invention, the computing speed of the neural network can be improved, and power can be saved.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a processor and a processing method applied to a sparse neural network. Background technique [0002] Artificial intelligence technology has developed rapidly in recent years and has attracted widespread attention all over the world. Both industry and academia have carried out research on artificial intelligence technology. At present, artificial intelligence technology has penetrated into visual Perception, speech recognition, assisted driving, smart home, traffic dispatching and other fields. [0003] Deep learning technology is a booster for the development of artificial intelligence technology. Deep learning uses the topology of deep neural networks for training, optimization and reasoning. Deep neural networks include convolutional neural networks, deep belief networks, and recurrent neural networks. Taking the application of image recognition as an example,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/063G06N3/04G06N5/04
CPCG06N3/063G06N5/04G06N3/045
Inventor 韩银和许浩博王颖
Owner INST OF COMPUTING TECH CHINESE ACAD OF SCI
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