Edge Intelligence with Distributed Processing of DNNs: A Survey
نویسندگان
چکیده
With the rapid development of deep learning, size data sets and neural networks (DNNs) models are also booming. As a result, intolerable long time for models’ training or inference with conventional strategies can not meet satisfaction modern tasks gradually. Moreover, devices stay idle in scenario edge computing (EC), which presents waste resources since they share pressure busy but do not. To address problem, strategy leveraging distributed processing has been applied to load computation from single processor group devices, results acceleration DNN promotes high utilization computing. Compared existing papers, this paper an enlightening novel review applying model parallelism improve learning Considering practicalities, commonly used lightweight system introduced as well. key technique, parallel will be described detail. Then some typical applications analyzed. Finally, challenges described.
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ژورنال
عنوان ژورنال: Cmes-computer Modeling in Engineering & Sciences
سال: 2023
ISSN: ['1526-1492', '1526-1506']
DOI: https://doi.org/10.32604/cmes.2023.023684