DREAM: A Dynamic Scheduler for Dynamic Real-time Multi-model ML Workloads

Emerging real-time multi-model ML (RTMM) workloads such as AR/VR and drone control involve dynamic behaviors in various granularity; task, model, and layers within a model. Such dynamic behaviors introduce new challenges to the system software in an ML system since the overall system load is not com...

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Bibliographische Detailangaben

Hauptverfasser:	Kim, Seah, Kwon, Hyoukjun, Song, Jinook, Jo, Jihyuck, Chen, Yu-Hsin, Lai, Liangzhen, Chandra, Vikas
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Distributed, Parallel, and Cluster Computing Computer Science - Learning
Online-Zugang:	Volltext bestellen
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