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 …
reality have tight latency constraints, hardware AI accelerators have been recently proposed …
[PDF][PDF] Model-driven Cluster Resource Management for AI Workloads in Edge Clouds
Q LIANG, WA HANAFY, A ALI-ELDIN, P SHENOY - 2023 - none.cs.umass.edu
It is increasingly common for such IoT applications to use AI inference as part of their data
processing tasks. In contrast to model training, which involves training a machine learning …
processing tasks. In contrast to model training, which involves training a machine learning …
Model-driven Cluster Resource Management for AI Workloads in Edge Clouds
Q Liang, WA Hanafy, A Ali-Eldin, P Shenoy - arXiv preprint arXiv …, 2022 - arxiv.org
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 …
reality have tight latency constraints, hardware AI accelerators have been recently proposed …
Model-driven Cluster Resource Management for AI Workloads in Edge Clouds
Q Liang, WA Hanafy, A Ali-Eldin, P Shenoy - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
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 …
reality have tight latency constraints, hardware AI accelerators have been recently proposed …
Model-driven Cluster Resource Management for AI Workloads in Edge Clouds
Q Liang, WA Hanafy, A Ali-Eldin, P Shenoy - ACM Transactions on …, 2023 - par.nsf.gov
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 …
reality have tight latency constraints, hardware AI accelerators have been recently proposed …
[PDF][PDF] Model-driven Cluster Resource Management for AI Workloads in Edge Clouds
Q LIANG, WA HANAFY, A ALI-ELDIN, P SHENOY - 2023 - qianlin404.github.io
It is increasingly common for such IoT applications to use AI inference as part of their data
processing tasks. In contrast to model training, which involves training a machine learning …
processing tasks. In contrast to model training, which involves training a machine learning …
[PDF][PDF] Model-driven Cluster Resource Management for AI Workloads in Edge Clouds
Q LIANG, WA HANAFY, A ALI-ELDIN, P SHENOY - 2023 - lass.cs.umass.edu
It is increasingly common for such IoT applications to use AI inference as part of their data
processing tasks. In contrast to model training, which involves training a machine learning …
processing tasks. In contrast to model training, which involves training a machine learning …
[PDF][PDF] Model-driven Cluster Resource Management for AI Workloads in Edge Clouds
Q LIANG, WA HANAFY, A ALI-ELDIN… - arXiv preprint arXiv …, 2022 - qianlin404.github.io
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 …
reality have tight latency constraints, hardware AI accelerators have been recently proposed …