Automatic Pipeline Parallelism: A Parallel Inference Framework for Deep Learning Applications in 6G Mobile Communication Systems

With the rapid development of wireless communication, achieving the neXt generation Ultra-Reliable and Low-Latency Communications (xURLLC) in 6G mobile communication systems has become a critical problem. Among many applications in xURLLC, deep learning model inference requires improvement over its...

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Veröffentlicht in:	IEEE journal on selected areas in communications 2023-07, Vol.41 (7), p.1-1
Hauptverfasser:	Shi, Hongjian, Zheng, Weichu, Liu, Zifei, Ma, Ruhui, Guan, Haibing
Format:	Artikel
Sprache:	eng
Schlagworte:	6G mobile communication Communication Computational modeling Data models Deep learning Distributed Learning Edge computing Efficiency Hardware Profiling Inference Machine learning Mobile communication systems Modules Network latency Parallel Inference Parallel processing Pipelines Pipelining (computers) Reliability Schedules System Heterogeneity Task analysis Task Scheduling Training Wireless communications
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