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Neural network computing device and method

A computing device and neural network technology, applied in the field of data processing, can solve problems such as occupying a large amount of storage resources and computing resources, and achieve the effects of increasing computing speed, improving efficiency, and reducing computing workload

Active Publication Date: 2021-07-30
SHANGHAI CAMBRICON INFORMATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

When the processing data is very large, the storage and operation of the matrix need to occupy a large amount of storage resources and computing resources

Method used

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  • Neural network computing device and method
  • Neural network computing device and method
  • Neural network computing device and method

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Embodiment Construction

[0058] In order to make the purpose, technical solutions and advantages of the present disclosure clearer, the present disclosure will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings. The advantages and effects of the present disclosure will be more obvious through the following contents of the present disclosure. The drawings accompanying this description are simplified and used for illustration purposes. The number, shape and size of the components shown in the drawings can be modified according to the actual situation, and the configuration of the components may be more complicated. Other aspects of practice or application can also be carried out in this disclosure, and various changes and adjustments can be made without departing from the spirit and scope defined in this disclosure.

[0059] figure 2 Schematic diagram of the structure of the matrix multiplication and addition operation device ...

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Abstract

The present disclosure provides a neural network computing device and method. Wherein, the neural network operation device includes a sub-matrix division module, which is used to use the convolution kernel matrix as the first matrix, and uses each sub-matrix as the second matrix; the matrix element storage module contains multiple storage spaces, and is used to receive the first matrix according to the rules. The binary number after the conversion of the matrix elements in the matrix; the symbol operation module is used to determine the sign bit of the operation result; the numerical operation module is used to add the matrix elements at the corresponding positions, and shift the addition result to the left by i-j bits to obtain The intermediate result of the operation; the accumulation module is used to add the intermediate results of the operation in the 1st to i-1 storage spaces to obtain the result of the multiplication and addition operation of the first matrix and the second matrix; the convolution result acquisition module is used to obtain the results according to In a sliding sequence, the multiple multiplication and addition operation results are formed into a matrix as the result of the convolution operation.

Description

technical field [0001] The present disclosure relates to the technical field of data processing, and in particular to a neural network computing device and a neural network computing method. Background technique [0002] For the neural network field, a lot of multiplication and addition operations need to be done. As one of the frequently used important operations, the convolution operation also has the problem of large storage resources and computing resources. [0003] Matrix operations are widely used in data processing in various research fields. When the processing data is very large, the storage and operation of the matrix needs to occupy a large amount of storage resources and computing resources. Contents of the invention [0004] In the first aspect of the present disclosure, a neural network computing device is provided, including: [0005] The sub-matrix division module is used to slide on the neuron matrix with the convolution kernel matrix as the sliding wi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/04G06N3/063
CPCG06F17/16G06N3/065G06N3/045G06N3/04G06N3/06G06N3/063G06F7/5443
Inventor 不公告发明人
Owner SHANGHAI CAMBRICON INFORMATION TECH CO LTD