Accelerated execution method of deep learning model in dynamic change network environment
A network environment and deep learning technology, applied in the field of edge computing and the Internet of Things, can solve the problems of inability to model segmentation, large time complexity, and availability impact, and achieve the effect of accurate segmentation and speeding up the data analysis process.
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[0042] Next, in connection with the specific embodiments, the present invention is further clarified that these examples are intended to illustrate the invention only and are not intended to limit the scope of the invention, and those skilled in the
[0043] A accelerated execution method of depth learning model in a dynamic variation network environment, including 1) Getting the actual operating time of the convolutional neural network on the edge end and the cloud; the output size of each layer; real-time monitoring network bandwidth, according to neural network Each layer output size and network bandwidth are transmitted. 2) Abstraction of the neural network of the neural network is a node, and there is a connection between the two nodes of data transmission to obtain a DAG map. 3) Modeling the DAG model, splitting the three delayed properties of each node into three-way, and establishes a super s...
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