Neural-network operation device and method

A neural network and computing device technology, applied in the field of artificial neural networks, can solve problems affecting the use of neural networks and reduce the computing speed of neural networks, so as to achieve the effects of reducing the amount of computing, increasing the speed of computing, and improving efficiency

Pending Publication Date: 2018-06-29
SHANGHAI CAMBRICON INFORMATION TECH CO LTD
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The resulting problem is that the neural network needs to do more calculations, especially the convolutional neural network. A large number of

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  • Neural-network operation device and method
  • Neural-network operation device and method
  • Neural-network operation device and method

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Embodiment Construction

[0054] Other aspects, advantages and salient features of the present disclosure will become apparent to those skilled in the art from the following detailed description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings.

[0055] In this disclosure, the terms "include" and "comprising" and their derivatives mean to include but not to limit; the term "or" is inclusive, meaning and / or.

[0056] In this specification, the various embodiments described below to describe the principles of the present disclosure are illustrative only and should not be construed as limiting the scope of the invention in any way. The following description with reference to the accompanying drawings is provided to assist in a comprehensive understanding of exemplary embodiments of the present disclosure as defined by the claims and their equivalents. The following description includes numerous specific details to aid in understanding, but these should be co...

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Abstract

The invention discloses a neural-network operation device. The device includes: a sparseness processing unit, which is used for carrying out sparseness processing on a weight matrix to generate a binary sparse sequence, wherein "0" corresponds to an element, of which a numerical value is "0", in the weight matrix, and "1" corresponds to an element, of which a numerical value is not 0, in the transformed weight matrix; a mapping unit, which is used for generating a mapping relationship table of the sparse sequence and element positions in a neuron matrix, wherein a K-th bit of the sparse sequence corresponds to an element of an i-th row and a j-th column in the neuron matrix of M rows x N columns, and it is met that (i-1) x N + j = K or (j-1) x M + i = K; and a controller, which is used forcontrolling the sparseness processing unit to generate the sparse sequence, and controlling the mapping unit to generate the mapping relationship table.

Description

technical field [0001] The present disclosure relates to the technical field of artificial neural networks, and in particular to a neural network computing device and a neural network computing method. Background technique [0002] Multi-layer artificial neural networks are widely used in the fields of pattern recognition, image processing, function approximation, and optimization calculations. In recent years, multi-layer artificial neural networks have been favored by academic circles and industry is getting more and more attention. [0003] In order to meet the increasingly high task requirements, the scale of neural networks has become larger and larger. At present, large-scale convolutional neural networks have included hundreds of layers of network layer structures. The resulting problem is that the neural network needs to do more calculations, especially the convolutional neural network. A large number of convolution operations reduce the calculation speed of the neu...

Claims

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Application Information

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IPC IPC(8): G06N3/04G06N3/063
CPCG06N3/065G06N3/045
Inventor 不公告发明人
Owner SHANGHAI CAMBRICON INFORMATION TECH CO LTD
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