17 citations · 21 across the 8 of their papers we have counts for
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cs.DC2024
TrainMover: An Interruption-Resilient Runtime for ML Training
ChonLam Lao, Jiaqi Gao, Jiamin Cao +13
Large-scale ML training jobs are frequently interrupted by hardware and software anomalies, failures, and management events. Existing solutions like checkpoint-restart or runtime r…
eess.SY2024★ 1 cited
EdgeSight: Enabling Modeless and Cost-Efficient Inference at the Edge
ChonLam Lao, Jiaqi Gao, Ganesh Ananthanarayanan +2
Traditional ML inference is evolving toward modeless inference, which abstracts the complexity of model selection from users, allowing the system to automatically choose the most a…