Workload Characterization

GPU Cluster Scheduling: A Map for Deep Learning Workloads
A technical guide to GPU datacenter scheduling based on our ACM Computing Surveys paper, covering training, inference, HPO, mixed workloads, and future scheduler design.
Zhisheng YE
May 16, 2026 7 min read
GPU Cluster Scheduling: A Map for Deep Learning Workloads
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
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
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