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Photonic convolutional neural network architecture based on optical delay line caching

A convolutional neural network and optical delay technology, applied in the field of photonic convolutional neural network architecture, achieves high energy efficiency ratio, simplifies data shift hardware design, and improves convolution calculation speed

Pending Publication Date: 2019-11-29
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

However, most of the current research is to use photonic devices to realize the matrix multiplication unit, and the photonic devices have not been fully utilized to realize the convolution calculation unit.

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  • Photonic convolutional neural network architecture based on optical delay line caching
  • Photonic convolutional neural network architecture based on optical delay line caching
  • Photonic convolutional neural network architecture based on optical delay line caching

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[0032] The technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings and examples, and detailed implementation methods and processes will be given, but the scope of protection of the present invention is not limited to the following examples.

[0033] see figure 1 , figure 1 It is a diagram of an embodiment of the photon convolutional neural network architecture based on the optical delay line cache in the present invention. It can be seen from the figure that the photon convolutional neural network architecture based on the optical delay line buffer of the present invention includes a laser array 1 , a high-speed modulator array 2 , an optical buffer array 3 , a dual output modulator array 4 and a balanced detector array 5 . In this embodiment, M=N=2, Q=3.

[0034] The laser array 1 includes two lasers, which generate wavelengths of λ 1 , lambda 2 point-frequency continuous light; the high-speed modulator ...

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Abstract

The invention discloses a photonic convolutional neural network architecture based on optical delay line caching. The architecture can achieve the large-scale optical caching through employing the wavelength division multiplexing technology and the optical delay line technology, thereby completing the data shift operation which must be included in convolution calculation. Moreover, the architecture simultaneously realizes signal input and weight loading by using the array input electro-optical modulator and the array weight unit, can realize convolution calculation of the non-von Noemann architecture when the scale is expanded, gives full play to photon broadband and rate advantages, and reduces convolution calculation power consumption.

Description

technical field [0001] The invention relates to an intelligent photon signal processing technology and a neural network technology, in particular to a photon convolutional neural network architecture based on an optical delay line cache. [0002] technical background [0003] With the development of big data and computer technology, deep learning has made extensive breakthroughs in image recognition, speech processing, machine translation and other application fields, and has attracted a lot of attention from the industry and academia. Convolutional neural network is a widely used deep learning computing model, which has a very good feature extraction effect on normalized data such as images and videos. Therefore, people use convolutional neural network to greatly improve the accuracy of object recognition and face recognition. rate, even surpassing the human level. [0004] In order to cope with the energy efficiency ratio of neural network computing in the future, people t...

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Application Information

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IPC IPC(8): G06N3/067H01S3/23
CPCG06N3/067H01S3/23
Inventor 邹卫文徐绍夫陈建平
Owner SHANGHAI JIAO TONG UNIV
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