Binary neural network forward propagation framework suitable for mobile terminal

A binary neural network and forward propagation technology, applied in the field of binary neural network forward propagation framework, can solve the problems of high energy consumption, low computing efficiency, slow speed, etc., achieve efficient operation, improve computing speed, and reduce storage The effect of occupation

Pending Publication Date: 2020-05-15
SUN YAT SEN UNIV
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Problems solved by technology

[0005] The present invention provides a binary neural network forward propagation framework suitable for mobile terminals in order to overcome the problems of low computational efficiency, high energy consumption and slow speed caused by the mobile terminal

Method used

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  • Binary neural network forward propagation framework suitable for mobile terminal
  • Binary neural network forward propagation framework suitable for mobile terminal
  • Binary neural network forward propagation framework suitable for mobile terminal

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Embodiment 1

[0046] Such as Figure 1-2 Shown is an embodiment of a binary neural network forward propagation framework suitable for mobile terminals, including a model conversion module and a forward propagation module; the model conversion module is used to convert the trained binary neural network into a dedicated framework The model is used for data processing and pre-computation during the conversion process; forward propagation is used to perform forward propagation calculations on the converted binary neural network model;

[0047] Among them, the converted binary neural network model is expressed according to the granularity from coarse to fine: network, layer, and tensor; in the framework, the network is divided into layer structures one by one, and each layer has corresponding parameters. The data in the frame is all stored in tensors. The network framework uses its own GPU memory management and recycling system to allocate the memory resources required for each step in the firs...

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Abstract

The invention relates to a binary neural network forward propagation framework suitable for a mobile terminal. The binary neural network forward propagation framework comprises a model conversion module and a forward propagation module, wherein the forward propagation model comprises a data storage unit, an operation unit and an optimization unit; the data storage unit stores data in a data layoutmode of number, height, width and channel number and compresses the data; wherein the arithmetic unit is a GPU arithmetic unit and merges the operation layers of the binarized neural network; the optimization unit balances the thread read-write data amount and the calculated amount in the arithmetic unit. Compared with the traditional neural network framework, the scheme of forward propagation onthe mobile phone is provided, the storage occupation is reduced, the operation speed is improved, the energy consumption ratio of the binary neural network running on the mobile phone is improved byutilizing the GPU, and the binary neural network can be efficiently run on the mobile terminal.

Description

technical field [0001] The present invention relates to the field of neural network frameworks, and more particularly, relates to a binary neural network forward propagation framework suitable for mobile terminals. Background technique [0002] Artificial Neural Networks (ANNs for short), also referred to as Neural Networks (NNs) or Connection Model, is a kind of algorithmic mathematics that imitates the behavior characteristics of animal neural networks and performs distributed parallel information processing. Model. This kind of network depends on the complexity of the system, and achieves the purpose of processing information by adjusting the interconnection relationship between a large number of internal nodes. [0003] When applying an artificial neural network, it is generally divided into four steps: 1. Train the corresponding neural network according to the requirements; 2. Adjust and optimize the trained neural network to obtain a suitable model for deployment; 3. ...

Claims

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Application Information

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IPC IPC(8): G06N3/04G06N3/08
CPCG06N3/082G06N3/045
Inventor 陈刚何晟宇
Owner SUN YAT SEN UNIV
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