Model-driven Cluster Resource Management for AI Workloads in Edge Clouds
Since emerging edge applications such as Internet of Things (IoT) analytics and augmented reality have tight latency constraints, hardware AI accelerators have been recently proposed to speed up deep neural network (DNN) inference run by these applications. Resource-constrained edge servers and acce...
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Published in | ACM transactions on autonomous and adaptive systems Vol. 18; no. 1; pp. 1 - 26 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
New York, NY
ACM
27.03.2023
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Subjects | |
Online Access | Get full text |
ISSN | 1556-4665 1556-4703 |
DOI | 10.1145/3582080 |
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