Qizhen Weng

According to our database, Qizhen Weng authored at least 20 papers between 2018 and 2026.

Collaborative distances:

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

2026

Mosaic: Towards Efficient Training of Multimodal Models with Spatial Resource Multiplexing.

Yanbo Wang, Yuxuan Wang, Chen Chen, Chunyu Xue, Yu Feng, Anbang Wu, Quan Chen, Yin Chen, Qizhen Weng

CoRR, May, 2026

CALVO: Improve Serving Efficiency for LLM Inferences with Intense Network Demands.

Weiye Wang, Chen Chen, Junxue Zhang, Zhusheng Wang, Hui Yuan, Zixuan Guan, Xiaolong Zheng, Qizhen Weng, Yin Chen, Minyi Guo

CoRR, March, 2026

Efficient Data Passing for Serverless Inference Workflows: A GPU-Centric Approach.

Hao Wu, Yaochen Liu, Minchen Yu, Qizhen Weng, Junxiao Deng, Yue Yu, Hao Fan, Song Wu, Wei Wang, Hai Jin

Proceedings of the 21st European Conference on Computer Systems, 2026

Suika: Efficient and High-quality Re-scheduling of 3D-parallelized LLM Training Jobs in Shared Clusters.

Yuxuan Wang, Yanbo Wang, Chen Chen, Chunyu Xue, Qizhen Weng, Yin Chen, Zeren Li, Xuqi Zhu, Yongqiang Yang, Quan Chen, Minyi Guo

Proceedings of the 21st European Conference on Computer Systems, 2026

2025

Janus: Disaggregating Attention and Experts for Scalable MoE Inference.

Zhexiang Zhang, Ye Wang, Xiangyu Wang, Yumiao Zhao, Jingzhe Jiang, Qizhen Weng, Shaohuai Shi, Yin Chen, Minchen Yu

CoRR, December, 2025

Efficient Unified Caching for Accelerating Heterogeneous AI Workloads.

Tianze Wang, Yifei Liu, Chen Chen, Pengfei Zuo, Jiawei Zhang, Qizhen Weng, Yin Chen, Zhenhua Han, Jieru Zhao, Quan Chen, Minyi Guo

CoRR, June, 2025

Toppings: CPU-Assisted, Rank-Aware Adapter Serving for LLM Inference.

Suyi Li, Hanfeng Lu, Tianyuan Wu, Minchen Yu, Qizhen Weng, Xusheng Chen, Yizhou Shan, Binhang Yuan, Wei Wang

Proceedings of the 2025 USENIX Annual Technical Conference, 2025

GPU-Disaggregated Serving for Deep Learning Recommendation Models at Scale.

Lingyun Yang, Yongchen Wang, Yinghao Yu, Qizhen Weng, Jianbo Dong, Kan Liu, Chi Zhang, Yanyi Zi, Hao Li, Zechao Zhang, Nan Wang, Yu Dong, Menglei Zheng, Lanlan Xi, Xiaowei Lu, Liang Ye, Guodong Yang, Binzhang Fu, Tao Lan, Liping Zhang, Lin Qu, Wei Wang

Proceedings of the 22nd USENIX Symposium on Networked Systems Design and Implementation, 2025

2024

Efficient Training of Large Language Models on Distributed Infrastructures: A Survey.

Jiangfei Duan, Shuo Zhang, Zerui Wang, Lijuan Jiang, Wenwen Qu, Qinghao Hu, Guoteng Wang, Qizhen Weng, Hang Yan, Xingcheng Zhang, Xipeng Qiu, Dahua Lin, Yonggang Wen, Xin Jin, Tianwei Zhang, Peng Sun

CoRR, 2024

InternLM2 Technical Report.

Zheng Cai, Maosong Cao, Haojiong Chen, Kai Chen, Keyu Chen, Xin Chen, Xun Chen, Zehui Chen, Zhi Chen, Pei Chu, Xiaoyi Dong, Haodong Duan, Qi Fan, Zhaoye Fei, Yang Gao, Jiaye Ge, Chenya Gu, Yuzhe Gu, Tao Gui, Aijia Guo, Qipeng Guo, Conghui He, Yingfan Hu, Ting Huang, Tao Jiang, Penglong Jiao, Zhenjiang Jin, Zhikai Lei, Jiaxing Li, Jingwen Li, Linyang Li, Shuaibin Li, Wei Li, Yining Li, Hongwei Liu, Jiangning Liu, Jiawei Hong, Kaiwen Liu, Kuikun Liu, Xiaoran Liu, Chengqi Lv, Haijun Lv, Kai Lv, Li Ma, Runyuan Ma, Zerun Ma, Wenchang Ning, Linke Ouyang, Jiantao Qiu, Yuan Qu, Fukai Shang, Yunfan Shao, Demin Song, Zifan Song, Zhihao Sui, Peng Sun, Yu Sun, Huanze Tang, Bin Wang, Guoteng Wang, Jiaqi Wang, Jiayu Wang, Rui Wang, Yudong Wang, Ziyi Wang, Xingjian Wei, Qizhen Weng, Fan Wu, Yingtong Xiong, Xiaomeng Zhao, et al.

CoRR, 2024

CaraServe: CPU-Assisted and Rank-Aware LoRA Serving for Generative LLM Inference.

Suyi Li, Hanfeng Lu, Tianyuan Wu, Minchen Yu, Qizhen Weng, Xusheng Chen, Yizhou Shan, Binhang Yuan, Wei Wang

CoRR, 2024

2023

Accelerating Distributed Learning in Non-Dedicated Environments.

Chen Chen, Qizhen Weng, Wei Wang, Baochun Li, Bo Li

IEEE Trans. Cloud Comput., 2023

Beware of Fragmentation: Scheduling GPU-Sharing Workloads with Fragmentation Gradient Descent.

Qizhen Weng, Lingyun Yang, Yinghao Yu, Wei Wang, Xiaochuan Tang, Guodong Yang, Liping Zhang

Proceedings of the 2023 USENIX Annual Technical Conference, 2023

2022

MLaaS in the Wild: Workload Analysis and Scheduling in Large-Scale Heterogeneous GPU Clusters.

Qizhen Weng, Wencong Xiao, Yinghao Yu, Wei Wang, Cheng Wang, Jian He, Yong Li, Liping Zhang, Wei Lin, Yu Ding

Proceedings of the 19th USENIX Symposium on Networked Systems Design and Implementation, 2022

Workload consolidation in alibaba clusters: the good, the bad, and the ugly.

Yongkang Zhang, Yinghao Yu, Wei Wang, Qiukai Chen, Jie Wu, Zuowei Zhang, Jiang Zhong, Tianchen Ding, Qizhen Weng, Lingyun Yang, Cheng Wang, Jian He, Guodong Yang, Liping Zhang

Proceedings of the 13th Symposium on Cloud Computing, SoCC 2022, 2022

2020

Metis: learning to schedule long-running applications in shared container clusters at scale.

Luping Wang, Qizhen Weng, Wei Wang, Chen Chen, Bo Li

Proceedings of the International Conference for High Performance Computing, 2020

Semi-dynamic load balancing: efficient distributed learning in non-dedicated environments.

Chen Chen, Qizhen Weng, Wei Wang, Baochun Li, Bo Li

Proceedings of the SoCC '20: ACM Symposium on Cloud Computing, 2020

2019

Towards Framework-Independent, Non-Intrusive Performance Characterization for Dataflow Computation.

Huangshi Tian, Qizhen Weng, Wei Wang

Proceedings of the 10th ACM SIGOPS Asia-Pacific Workshop on Systems, 2019

2018

OpuS: Fair and Efficient Cache Sharing for In-Memory Data Analytics.

Yinghao Yu, Wei Wang, Jun Zhang, Qizhen Weng, Khaled Ben Letaief

Proceedings of the 38th IEEE International Conference on Distributed Computing Systems, 2018

Fast Distributed Deep Learning via Worker-adaptive Batch Sizing.

Chen Chen, Qizhen Weng, Wei Wang, Baochun Li, Bo Li

Proceedings of the ACM Symposium on Cloud Computing, 2018