GPU Scheduling

Tear Up the Bubble Boom: Lessons Learned From a Deep Learning Research and Development Cluster
With the proliferation of deep learning, there exists a strong need to efficiently operate GPU clusters for deep learning production in …
Zehua Yang, Zhisheng YE, Tianhao Fu, Jing Luo, Xiong Wei, Yingwei Luo, Xiaolin Wang, Zhenlin Wang, Tianwei Zhang
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Tear Up the Bubble Boom: Lessons Learned From a Deep Learning Research and Development Cluster
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
Chronus: A Novel Deadline-aware Scheduler for Deep Learning Training Jobs
We present Chronus, an end-to-end scheduling system to provide deadline guarantee for SLO jobs and maximize the performance of best-effort jobs for deep learning training jobs.
Wei Gao, Zhisheng YE, Peng Sun, Yonggang Wen, Tianwei Zhang
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Chronus: A Novel Deadline-aware Scheduler for Deep Learning Training Jobs