Ke Zhang

According to our database, Ke Zhang authored at least 10 papers between 2023 and 2024.

Collaborative distances:

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

2024

DLRover-RM: Resource Optimization for Deep Recommendation Models Training in the cloud.

Qinlong Wang, Tingfeng Lan, Yinghao Tang, Bo Sang, Ziling Huang, Yiheng Du, Haitao Zhang, Jian Sha, Hui Lu, Yuanchun Zhou, Ke Zhang, Mingjie Tang

Proc. VLDB Endow., August, 2024

LayerKV: Optimizing Large Language Model Serving with Layer-wise KV Cache Management.

Yi Xiong, Hao Wu, Changxu Shao, Ziqing Wang, Rui Zhang, Yuhong Guo, Junping Zhao, Ke Zhang, Zhenxuan Pan

CoRR, 2024

vTensor: Flexible Virtual Tensor Management for Efficient LLM Serving.

Jiale Xu, Rui Zhang, Cong Guo, Weiming Hu, Zihan Liu, Feiyang Wu, Yu Feng, Shixuan Sun, Changxu Shao, Yuhong Guo, Junping Zhao, Ke Zhang, Minyi Guo, Jingwen Leng

CoRR, 2024

Couler: Unified Machine Learning Workflow Optimization in Cloud.

Xiaoda Wang, Yuan Tang, Tengda Guo, Bo Sang, Jingji Wu, Jian Sha, Ke Zhang, Jiang Qian, Mingjie Tang

CoRR, 2024

Couler: Unified Machine Learning Workflow Optimization in Cloud.

Xiaoda Wang, Yuan Tang, Tengda Guo, Bo Sang, Jiewei Wu, Jian Sha, Ke Zhang, Jiang Qian, Mingjie Tang

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

GMLake: Efficient and Transparent GPU Memory Defragmentation for Large-scale DNN Training with Virtual Memory Stitching.

Cong Guo, Rui Zhang, Jiale Xu, Jingwen Leng, Zihan Liu, Ziyu Huang, Minyi Guo, Hao Wu, Shouren Zhao, Junping Zhao, Ke Zhang

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

2023

ASPEN: High-Throughput LoRA Fine-Tuning of Large Language Models with a Single GPU.

Zhengmao Ye, Dengchun Li, Jingqi Tian, Tingfeng Lan, Jie Zuo, Lei Duan, Hui Lu, Yexi Jiang, Jian Sha, Ke Zhang, Mingjie Tang

CoRR, 2023

DLRover: An Elastic Deep Training Extension with Auto Job Resource Recommendation.

Qinlong Wang, Bo Sang, Haitao Zhang, Mingjie Tang, Ke Zhang

CoRR, 2023

Sharpness-Aware Minimization Revisited: Weighted Sharpness as a Regularization Term.

Yun Yue, Jiadi Jiang, Zhiling Ye, Ning Gao, Yongchao Liu, Ke Zhang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Cougar: A General Framework for Jobs Optimization In Cloud.

Bo Sang, Shuwei Gu, Xiaojun Zhan, Mingjie Tang, Jian Liu, Xuan Chen, Jie Tan, Haoyuan Ge, Ke Zhang, Ruoyi Ruan, Wei Yan

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023