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1. CN108229654 - Neural network convolution operation device and method

Office
China
Application Number 201711343539.7
Application Date 14.12.2017
Publication Number 108229654
Publication Date 29.06.2018
Grant Number 108229654
Grant Date 14.08.2020
Publication Kind B
IPC
G06N 3/04
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architecture, e.g. interconnection topology
G06N 3/063
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
06Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
063using electronic means
CPC
G06N 3/0454
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architectures, e.g. interconnection topology
0454using a combination of multiple neural nets
G06N 3/0635
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
06Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
063using electronic means
0635using analogue means
G06N 3/04
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architectures, e.g. interconnection topology
G06N 3/063
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
06Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
063using electronic means
G06F 17/16
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
17Digital computing or data processing equipment or methods, specially adapted for specific functions
10Complex mathematical operations
16Matrix or vector computation ; , e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
G06N 3/02
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
Applicants SHANGHAI CAMBRICON INFORMATION TECHNOLOGY CO., LTD.
上海寒武纪信息科技有限公司
Inventors THE INVENTOR HAS WAIVED THE RIGHT TO BE MENTIONED
不公告发明人
Agents 中科专利商标代理有限责任公司 11021
Priority Data 2016111525375 14.12.2016 CN
Title
(EN) Neural network convolution operation device and method
(ZH) 神经网络卷积运算装置及方法
Abstract
(EN)
The invention discloses a neural network convolution operation device and method. The device is used for realizing convolution operation of a weight value matrix and a neural element matrix in a neural network via a matrix multiplication manner, and comprises a displacement operation unit, a matrix multiplication operation unit and a controller, wherein the displacement operation unit is used forrespectively carrying out winograd transformation on the neural element matrix and weight value matrix so as to obtain a transformed neural element matrix and a transformed weight value matrix; the matrix multiplication operation unit is used for carrying out a matrix multiplication operation such as counterpoint multiplication on the transformed neural element matrix and the transformed weight value matrix so as to obtain a multiplication matrix; the displacement operation unit is furthermore used for carrying out winograd inverse transformation on the multiplication matrix so as to obtain aconvolution operation result; and the controller is used for controlling the displacement operation unit to carry out the winograd transformation or the winograd inverse transformation, and controlling the matrix multiplication operation unit to carry out the matrix multiplication operation.

(ZH)
一种神经网络卷积运算装置和方法,其中装置用于以矩阵乘法的方式实现神经网络中的权值矩阵与神经元的卷积运算,其中包括:移位运算器,用于对所述神经元矩阵和权值矩阵分别进行winograd变换,得到变换后神经元矩阵和变换后权值矩阵;矩阵乘法运算器,用于将所述变换后神经元矩阵和变换后权值矩阵进行对位相乘的矩阵乘法操作,得到乘法矩阵;所述移位运算器还用于将所述乘法矩阵进行winograd反变换,得到卷积运算结果;控制器,用于控制所述移位运算器进行winograd变换或winograd反变换,还用于控制所述矩阵乘法运算器进行矩阵乘法操作。

Also published as
EP2017882134