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Characterization of Large Language Model Development in the Datacenter
Large Language Models (LLMs) have presented impressive performance across several transformative tasks. However, it is non-trivial to …
Qinghao Hu, Zhisheng YE, Zerui Wang, Guoteng Wang, Meng Zhang, Qiaoling Chen, Peng Sun, Dahua Lin, Xiaolin Wang, Yingwei Luo, Yonggang Wen, Tianwei Zhang
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Characterization of Large Language Model Development in the Datacenter
Hydro: Surrogate-Based Hyperparameter Tuning Service in Datacenters
Hyperparameter tuning is an essential step in deep learning model development that provides better model performance at the cost of …
Qinghao Hu, Zhisheng YE, Meng Zhang, Qiaoling Chen, Peng Sun, Yonggang Wen, Tianwei Zhang
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Hydro: Surrogate-Based Hyperparameter Tuning Service in Datacenters
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
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