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Vector fusion calculation method and device applied to neural network data processing

A technology of data processing and neural network, which is applied in the field of neural network, can solve the problem of low efficiency of input feature map, and achieve the effect of improving the accuracy of subsequent processing and increasing feature information

Pending Publication Date: 2022-06-07
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] Embodiments of the present invention provide a vector fusion calculation method and device applied in neural network

Method used

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  • Vector fusion calculation method and device applied to neural network data processing
  • Vector fusion calculation method and device applied to neural network data processing
  • Vector fusion calculation method and device applied to neural network data processing

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Experimental program
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Embodiment 1

[0036] According to an embodiment of the present invention, a vector fusion calculation method applied in neural network data processing is provided, including the following steps:

[0037] Using the method of instruction set control, two different Route operators and Shortcut operators are encoded into different parameters in the instruction set;

[0038] The operation of the system is controlled by means of a state machine, and the SRAM of the instruction set stores the functional information of each layer of the network, and then decodes it in the decoding state of the state machine;

[0039] When the operator type of the decoded instruction set is Route or Shortcut, then the corresponding operator processing is performed.

[0040] The vector fusion calculation method applied in the neural network data processing in the embodiment of the present invention adopts the instruction set control method, and encodes two different Route operators and Shortcut operators into differe...

Embodiment 2

[0063] According to another embodiment of the present invention, a vector fusion computing device applied in neural network data processing is provided, including:

[0064] The encoding unit is used to encode two different Route operators and Shortcut operators into different parameters in the instruction set by means of instruction set control;

[0065] The decoding unit is used to control the operation of the system by means of a state machine. The SRAM of the instruction set stores the functional information of each layer of the network, and then decodes it in the decoding state of the state machine;

[0066] The operator corresponds to the processing unit, which is used to perform corresponding operator processing when the operator type of the decoded instruction set is Route or Shortcut.

[0067] The vector fusion computing device applied in the neural network data processing in the embodiment of the present invention adopts the instruction set control method, and encodes...

Embodiment 3

[0081] A storage medium storing a program file capable of implementing any one of the above vector fusion calculation methods applied in neural network data processing.

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Abstract

The invention relates to the field of neural networks, in particular to a vector fusion calculation method and device applied to neural network data processing, and the method and device adopt an instruction set control mode to encode two different Route operators and Shartcut operators into different parameters in an instruction set, and control the operation of a system through a state machine mode. The SRAM of the instruction set stores the function information of each layer of the network, then decodes the function information in the decoding state of the state machine, and when the operator type of the instruction set is decoded to be Route or Shartcut, corresponding operator processing is carried out. As the Route operator and the Shartcut operator both carry out data processing on the two intermediate layers in the network layer, no matter splicing or corresponding position data addition is carried out, the feature information of the output feature map is increased, and the subsequent processing precision of the image can be improved.

Description

technical field [0001] The present invention relates to the field of neural networks, in particular, to a vector fusion calculation method and device applied in neural network data processing. Background technique [0002] As the structure of the neural network becomes more and more complex, and the number of network layers becomes deeper and deeper, the accuracy of the network begins to reach saturation or even degenerate. Ensure the accuracy and precision of network data. Because in the convolutional neural network, as the depth of the network becomes larger and larger, some of the previous data information will be removed after the image undergoes convolution or pooling operations, resulting in the loss of part of the feature information of the image, which in turn leads to the appearance of image recognition results. deviation or error. [0003] The prior art also has some processing methods for the above-mentioned defects, but there are still the following shortcoming...

Claims

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Application Information

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IPC IPC(8): G06N3/04
CPCG06N3/045Y02D10/00
Inventor 王峥肖玺
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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