Sizhe Tang1, Mengmeng Cui1,*, Lianyong Qi2, Xiaolong Xu1
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 5-42, 2023, DOI:10.32604/cmes.2023.023684
Abstract With the rapid development of deep learning, the size of data sets and deep neural networks (DNNs) models are also
booming. As a result, the intolerable long time for models’ training or inference with conventional strategies can
not meet the satisfaction of modern tasks gradually. Moreover, devices stay idle in the scenario of edge computing
(EC), which presents a waste of resources since they can share the pressure of the busy devices but they do not.
To address the problem, the strategy leveraging distributed processing has been applied to load computation tasks
from a single processor to a group of… More >
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