Zhisheng Ye

According to our database, Zhisheng Ye authored at least 14 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

ResiHP: Taming LLM Training Failures with Dynamic Hybrid Parallelism.

Tenghui Ma, Jihu Guo, Wei Gao, Sitian Lu, Zhisheng Ye, Hanjing Wang, Dahua Lin

CoRR, May, 2026

CONCUR: High-Throughput Agentic Batch Inference of LLM via Congestion-Based Concurrency Control.

Qiaoling Chen, Zhisheng Ye, Tian Tang, Peng Sun, Boyu Tian, Guoteng Wang, Shenggui Li, Yonggang Wen, Zhenhua Han, Tianwei Zhang

CoRR, January, 2026

Latency-SLO-Aware Memory Offloading for Large Language Model Inference.

Chenxiang Ma, Hanyu Zhao, Zhisheng Ye, Zehua Yang, Tianhao Fu, Jiaxun Han, Jie Zhang, Yingwei Luo, Xiaolin Wang, Zhenlin Wang, Yong Li, Diyu Zhou

Proceedings of the 40th ACM International Conference on Supercomputing, 2026

2025

LEMUR: Large scale End-to-end MUltimodal Recommendation.

Xintian Han, Honggang Chen, Quan Lin, Jingyue Gao, Xiangyuan Ren, Lifei Zhu, Zhisheng Ye, Shikang Wu, Xionghang Xie, Xiaochu Gan, Bingzheng Wei, Peng Xu, Zhe Wang, Yuchao Zheng, Jingjian Lin, Di Wu, Junfeng Ge

CoRR, November, 2025

Memory Offloading for Large Language Model Inference with Latency SLO Guarantees.

Chenxiang Ma, Zhisheng Ye, Hanyu Zhao, Zehua Yang, Tianhao Fu, Jiaxun Han, Jie Zhang, Yingwei Luo, Xiaolin Wang, Zhenlin Wang, Yong Li, Diyu Zhou

CoRR, February, 2025

2024

UniSched: A Unified Scheduler for Deep Learning Training Jobs With Different User Demands.

Wei Gao, Zhisheng Ye, Peng Sun, Tianwei Zhang, Yonggang Wen

IEEE Trans. Computers, June, 2024

Deep Learning Workload Scheduling in GPU Datacenters: A Survey.

Zhisheng Ye, Wei Gao, Qinghao Hu, Peng Sun, Xiaolin Wang, Yingwei Luo, Tianwei Zhang, Yonggang Wen

ACM Comput. Surv., June, 2024

Characterization of Large Language Model Development in the Datacenter.

Qinghao Hu, Zhisheng Ye, Zerui Wang, Guoteng Wang, Meng Zhang, Qiaoling Chen, Peng Sun, Dahua Lin, Xiaolin Wang, Yingwei Luo, Yonggang Wen, Tianwei Zhang

Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation, 2024

2023

AMSP: Super-Scaling LLM Training via Advanced Model States Partitioning.

Qiaoling Chen, Qinghao Hu, Zhisheng Ye, Guoteng Wang, Peng Sun, Yonggang Wen, Tianwei Zhang

CoRR, 2023

Hydro: Surrogate-Based Hyperparameter Tuning Service in Datacenters.

Qinghao Hu, Zhisheng Ye, Meng Zhang, Qiaoling Chen, Peng Sun, Yonggang Wen, Tianwei Zhang

Proceedings of the 17th USENIX Symposium on Operating Systems Design and Implementation, 2023

2022

Astraea: A Fair Deep Learning Scheduler for Multi-Tenant GPU Clusters.

Zhisheng Ye, Peng Sun, Wei Gao, Tianwei Zhang, Xiaolin Wang, Shengen Yan, Yingwei Luo

IEEE Trans. Parallel Distributed Syst., 2022

Deep Learning Workload Scheduling in GPU Datacenters: Taxonomy, Challenges and Vision.

Wei Gao, Qinghao Hu, Zhisheng Ye, Peng Sun, Xiaolin Wang, Yingwei Luo, Tianwei Zhang, Yonggang Wen

CoRR, 2022

Tear Up the Bubble Boom: Lessons Learned From a Deep Learning Research and Development Cluster.

Zehua Yang, Zhisheng Ye, Tianhao Fu, Jing Luo, Xiong Wei, Yingwei Luo, Xiaolin Wang, Zhenlin Wang, Tianwei Zhang

Proceedings of the IEEE 40th International Conference on Computer Design, 2022

2021

Chronus: A Novel Deadline-aware Scheduler for Deep Learning Training Jobs.

Wei Gao, Zhisheng Ye, Peng Sun, Yonggang Wen, Tianwei Zhang

Proceedings of the SoCC '21: ACM Symposium on Cloud Computing, 2021