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Registered METHOD AND APPARATUS FOR PARTITIONING DEEP NEURAL NETWORKS

Inventors
Lee Chang Sik, Hong Sung Back, Seungwoo Hong, Ryu Ho Yong
Application No.
16830253 (2020.03.25)
Publication No.
20200311546 (2020.10.01)
Registration No.
11521066 (2022.12.06)
Country
UNITED STATES
Project Code
19HH2100, A Development for Intellectualized Edge Networking based on AI, Tae Yeon Kim
Abstract
A processor partitions a deep neural network having a plurality of exit points and at least one partition point in a branch corresponding to each of the exit points, for distributed processing in an edge device and a cloud. The processor sets environmental variables and training variables for training, selects an action to move at least one of an exit point and a partition point from a combination of the exit point and the partition point corresponding to a current state, performs the training by accumulating experience data using a reward according to the selected action and then moves to a next state, and outputs a combination of an optimal exit point and a partition point as a result of the training.
KSP Keywords
Current state, Deep neural network(DNN), Edge devices, Partition point, distributed processing, environmental variables, neural network
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Status Patent Country KIPRIS
Registered METHOD AND APPARATUS FOR PARTITIONING DEEP NEURAL NETWORKS KOREA