Ekya: Continuous Learning of Video Analytics Models on Edge Compute Servers

no code implementations • 19 Dec 2020 • Romil Bhardwaj, Zhengxu Xia, Ganesh Ananthanarayanan, Junchen Jiang, Nikolaos Karianakis, Yuanchao Shu, Kevin Hsieh, Victor Bahl, Ion Stoica

Compressed models that are deployed on the edge servers for inference suffer from data drift, where the live video data diverges from the training data.

HyperSched: Dynamic Resource Reallocation for Model Development on a Deadline

no code implementations • 8 Jan 2020 • Richard Liaw, Romil Bhardwaj, Lisa Dunlap, Yitian Zou, Joseph Gonzalez, Ion Stoica, Alexey Tumanov

Prior research in resource scheduling for machine learning training workloads has largely focused on minimizing job completion times.

Scheduling