Yinmin Zhong

According to our database, Yinmin Zhong authored at least 10 papers between 2023 and 2024.

Collaborative distances:

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

2024

DistMind: Efficient Resource Disaggregation for Deep Learning Workloads.

Xin Jin, Zhihao Bai, Zhen Zhang, Yibo Zhu, Yinmin Zhong, Xuanzhe Liu

IEEE/ACM Trans. Netw., June, 2024

RLHFuse: Efficient RLHF Training for Large Language Models with Inter- and Intra-Stage Fusion.

Yinmin Zhong, Zili Zhang, Bingyang Wu, Shengyu Liu, Yukun Chen, Changyi Wan, Hanpeng Hu, Lei Xia, Ranchen Ming, Yibo Zhu, Xin Jin

CoRR, 2024

DistTrain: Addressing Model and Data Heterogeneity with Disaggregated Training for Multimodal Large Language Models.

Zili Zhang, Yinmin Zhong, Ranchen Ming, Hanpeng Hu, Jianjian Sun, Zheng Ge, Yibo Zhu, Xin Jin

CoRR, 2024

FLUX: Fast Software-based Communication Overlap On GPUs Through Kernel Fusion.

Li-Wen Chang, Wenlei Bao, Qi Hou, Chengquan Jiang, Ningxin Zheng, Yinmin Zhong, Xuanrun Zhang, Zuquan Song, Ziheng Jiang, Haibin Lin, Xin Jin, Xin Liu

CoRR, 2024

LoongServe: Efficiently Serving Long-Context Large Language Models with Elastic Sequence Parallelism.

Bingyang Wu, Shengyu Liu, Yinmin Zhong, Peng Sun, Xuanzhe Liu, Xin Jin

Proceedings of the ACM SIGOPS 30th Symposium on Operating Systems Principles, 2024

DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving.

Yinmin Zhong, Shengyu Liu, Junda Chen, Jianbo Hu, Yibo Zhu, Xuanzhe Liu, Xin Jin, Hao Zhang

Proceedings of the 18th USENIX Symposium on Operating Systems Design and Implementation, 2024

MegaScale: Scaling Large Language Model Training to More Than 10, 000 GPUs.

Ziheng Jiang, Haibin Lin, Yinmin Zhong, Qi Huang, Yangrui Chen, Zhi Zhang, Yanghua Peng, Xiang Li, Cong Xie, Shibiao Nong, Yulu Jia, Sun He, Hongmin Chen, Zhihao Bai, Qi Hou, Shipeng Yan, Ding Zhou, Yiyao Sheng, Zhuo Jiang, Haohan Xu, Haoran Wei, Zhang Zhang, Pengfei Nie, Leqi Zou, Sida Zhao, Liang Xiang, Zherui Liu, Zhe Li, Xiaoying Jia, Jianxi Ye, Xin Jin, Xin Liu

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

2023

Fast Distributed Inference Serving for Large Language Models.

Bingyang Wu, Yinmin Zhong, Zili Zhang, Gang Huang, Xuanzhe Liu, Xin Jin

CoRR, 2023

AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving.

Zhuohan Li, Lianmin Zheng, Yinmin Zhong, Vincent Liu, Ying Sheng, Xin Jin, Yanping Huang, Zhifeng Chen, Hao Zhang, Joseph E. Gonzalez, Ion Stoica

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

ElasticFlow: An Elastic Serverless Training Platform for Distributed Deep Learning.

Diandian Gu, Yihao Zhao, Yinmin Zhong, Yifan Xiong, Zhenhua Han, Peng Cheng, Fan Yang, Gang Huang, Xin Jin, Xuanzhe Liu

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023