Convolution neural network algorithm optimization method and device based on Neon instruction

A convolutional neural network and optimization method technology, applied in biological neural network models, neural architecture, computing and other directions, can solve problems such as poor real-time performance and long time-consuming convolutional neural network algorithms, and achieve the effect of improving computing performance

Inactive Publication Date: 2018-02-16
BEIJING ICETECH SCI & TECH CO LTD
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  • Convolution neural network algorithm optimization method and device based on Neon instruction
  • Convolution neural network algorithm optimization method and device based on Neon instruction

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[0031] In order to enable your examiners to further understand the structure, features and other purposes of the present invention, the attached preferred embodiments are now described in detail as follows. The described preferred embodiments are only used to illustrate the technical solutions of the present invention, not to limit the present invention. invention.

[0032] figure 1 A flow chart of the first embodiment of the algorithm optimization method of the convolutional neural network based on the Neon instruction according to the present invention is given. like figure 1 Shown, according to the algorithm optimization method of the convolutional neural network based on Neon instruction of the present invention comprises:

[0033] In the first step S1, the convolution kernel image of the convolution layer is matrixed, the corresponding A matrix is ​​obtained, and the number of columns of the A matrix is ​​aligned by a multiple of 4;

[0034] In the second step S2, inpu...

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Abstract

The invention provides a convolution neural network algorithm optimization method based on the Neon instruction. The method comprises the steps that matrix processing is carried out on the convolutionkernel image of a convolution layer to acquire a corresponding A matrix, and the A matrix columns are aligned according to the multiple of four; a to-be-convoluted image is input; matrix processing is carried out on the input image to be convoluted to acquire a corresponding B matrix; the B matrix rows are aligned according to the multiple of four; the B matrix is transposed to acquire a transposed matrix Bt; the row and row dot product of the A matrix and the Bt matrix is calculated; and the Neon instruction is used for parallel optimization. Compared with the prior art, the method providedby the invention can effectively improve the computing performance of the convolution neural network.

Description

technical field [0001] The invention relates to image processing, video monitoring and convolutional neural networks, in particular to an algorithm optimization method and device for convolutional neural networks based on Neon instructions. Background technique [0002] With the rapid development of artificial intelligence, deep learning has been increasingly introduced into the fields of image processing and pattern recognition, and has performed well in solving related problems. Among them, convolutional neural networks (CNN for short), as a model structure of deep learning, are especially good at dealing with machine learning problems related to images, especially large images, and have been widely used and the most in-depth research. [0003] However, in the practical application of image processing and pattern recognition, the convolutional neural network is generally implemented with more network layers, and its computational complexity is relatively high, including a ...

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Application Information

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IPC IPC(8): G06N3/04G06F17/15
CPCG06F17/153G06N3/045
Inventor 朱明曾建平张智鹏耿磊
Owner BEIJING ICETECH SCI & TECH CO LTD
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