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UniSched: A Unified Scheduler for Deep Learning Training Jobs with Different User Demands
We present UniSched, a unified scheduler to optimize different types of scheduling objectives (e.g., guaranteeing the deadlines of SLO jobs, minimizing the latency of best-effort jobs).
Wei Gao, Zhisheng YE, Peng Sun, Tianwei Zhang, Yonggang Wen
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UniSched: A Unified Scheduler for Deep Learning Training Jobs with Different User Demands
Deep Learning Workload Scheduling in GPU Datacenters: A Survey
Deep learning (DL) shows its prosperity in a wide variety of fields. The development of a DL model is a time-consuming and …
Zhisheng YE, Wei Gao, Qinghao Hu, Peng Sun, Xiaolin Wang, Yingwei Luo, Tianwei Zhang, Yonggang Wen
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Deep Learning Workload Scheduling in GPU Datacenters: A Survey
ASTRAEA: A Fair Deep Learning Scheduler for Multi-tenant GPU Clusters
We design a new and practical GPU scheduler, ASTRAEA, to enforce the desired fairness among tenants and jobs for deep learning training clusters.
Zhisheng YE, Peng Sun, Wei Gao, Tianwei Zhang, Xiaolin Wang, Shengen Yan, Yingwei Luo
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ASTRAEA: A Fair Deep Learning Scheduler for Multi-tenant GPU Clusters