Lianmin Zheng

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 43

Top Topics

Depth Estimation

Tens Of Thousands

Top Venues

Publications

Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Hao Zhang, Banghua Zhu, Michael I. Jordan, Joseph E. Gonzalez, Ion Stoica
Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference. CoRR (2024)
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Hao Zhang
LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset. ICLR (2024)
Ying Sheng, Shiyi Cao, Dacheng Li, Coleman Hooper, Nicholas Lee, Shuo Yang, Christopher Chou, Banghua Zhu, Lianmin Zheng, Kurt Keutzer, Joseph Gonzalez, Ion Stoica
SLoRA: Scalable Serving of Thousands of LoRA Adapters. MLSys (2024)
Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark W. Barrett, Zhangyang Wang, Beidi Chen
O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. CoRR (2023)
Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Daniel Y. Fu, Zhiqiang Xie, Beidi Chen, Clark W. Barrett, Joseph E. Gonzalez, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang
High-throughput Generative Inference of Large Language Models with a Single GPU. CoRR (2023)
Zhuohan Li, Lianmin Zheng, Yinmin Zhong, Vincent Liu, Ying Sheng, Xin Jin, Yanping Huang, Zhifeng Chen, Hao Zhang, Joseph E. Gonzalez, Ion Stoica
AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving. OSDI (2023)
Shuo Yang, Wei-Lin Chiang, Lianmin Zheng, Joseph E. Gonzalez, Ion Stoica
Rethinking Benchmark and Contamination for Language Models with Rephrased Samples. CoRR (2023)
Zhuohan Li, Lianmin Zheng, Yinmin Zhong, Vincent Liu, Ying Sheng, Xin Jin, Yanping Huang, Zhifeng Chen, Hao Zhang, Joseph E. Gonzalez, Ion Stoica
AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving. CoRR (2023)
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph Gonzalez, Hao Zhang, Ion Stoica
Efficient Memory Management for Large Language Model Serving with PagedAttention. SOSP (2023)
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Hao Zhang
LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset. CoRR (2023)
Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Beidi Chen, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang
FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU. ICML (2023)
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, Ion Stoica
Judging LLM-as-a-judge with MT-Bench and Chatbot Arena. CoRR (2023)
Banghua Zhu, Ying Sheng, Lianmin Zheng, Clark W. Barrett, Michael I. Jordan, Jiantao Jiao
On Optimal Caching and Model Multiplexing for Large Model Inference. CoRR (2023)
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, Ion Stoica
Efficient Memory Management for Large Language Model Serving with PagedAttention. CoRR (2023)
Siyuan Feng, Bohan Hou, Hongyi Jin, Wuwei Lin, Junru Shao, Ruihang Lai, Zihao Ye, Lianmin Zheng, Cody Hao Yu, Yong Yu, Tianqi Chen
TensorIR: An Abstraction for Automatic Tensorized Program Optimization. ASPLOS (2) (2023)
Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, Jeff Huang, Chuyue Sun, Cody Hao Yu, Shiyi Cao, Christos Kozyrakis, Ion Stoica, Joseph E. Gonzalez, Clark W. Barrett, Ying Sheng
Efficiently Programming Large Language Models using SGLang. CoRR (2023)
Banghua Zhu, Ying Sheng, Lianmin Zheng, Clark W. Barrett, Michael I. Jordan, Jiantao Jiao
Towards Optimal Caching and Model Selection for Large Model Inference. NeurIPS (2023)
Ying Sheng, Shiyi Cao, Dacheng Li, Coleman Hooper, Nicholas Lee, Shuo Yang, Christopher Chou, Banghua Zhu, Lianmin Zheng, Kurt Keutzer, Joseph E. Gonzalez, Ion Stoica
S-LoRA: Serving Thousands of Concurrent LoRA Adapters. CoRR (2023)
Yonghao Zhuang, Lianmin Zheng, Zhuohan Li, Eric P. Xing, Qirong Ho, Joseph Gonzalez, Ion Stoica, Hao Zhang, Hexu Zhao
On Optimizing the Communication of Model Parallelism. MLSys (2023)
Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark W. Barrett, Zhangyang Wang, Beidi Chen
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. NeurIPS (2023)
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, Ion Stoica
Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena. NeurIPS (2023)
Lianmin Zheng, Zhuohan Li, Hao Zhang, Yonghao Zhuang, Zhifeng Chen, Yanping Huang, Yida Wang, Yuanzhong Xu, Danyang Zhuo, Joseph E. Gonzalez, Ion Stoica
Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning. CoRR (2022)
Yonghao Zhuang, Hexu Zhao, Lianmin Zheng, Zhuohan Li, Eric P. Xing, Qirong Ho, Joseph E. Gonzalez, Ion Stoica, Hao Zhang
On Optimizing the Communication of Model Parallelism. CoRR (2022)
Siyuan Feng, Bohan Hou, Hongyi Jin, Wuwei Lin, Junru Shao, Ruihang Lai, Zihao Ye, Lianmin Zheng, Cody Hao Yu, Yong Yu, Tianqi Chen
TensorIR: An Abstraction for Automatic Tensorized Program Optimization. CoRR (2022)
Xiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen, Xu Han, Jianfei Chen, Zhiyuan Liu, Jie Tang, Joey Gonzalez, Michael Mahoney, Alvin Cheung
GACT: Activation Compressed Training for General Architectures. CoRR (2022)
Lianmin Zheng, Zhuohan Li, Hao Zhang, Yonghao Zhuang, Zhifeng Chen, Yanping Huang, Yida Wang, Yuanzhong Xu, Danyang Zhuo, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica
Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning. OSDI (2022)
Melih Elibol, Vinamra Benara, Samyu Yagati, Lianmin Zheng, Alvin Cheung, Michael I. Jordan, Ion Stoica
NumS: Scalable Array Programming for the Cloud. CoRR (2022)
Xiaoxuan Liu, Lianmin Zheng, Dequan Wang, Yukuo Cen, Weize Chen, Xu Han, Jianfei Chen, Zhiyuan Liu, Jie Tang, Joey Gonzalez, Michael Mahoney, Alvin Cheung
GACT: Activation Compressed Training for Generic Network Architectures. ICML (2022)
Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael W. Mahoney, Joseph E. Gonzalez
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training. CoRR (2021)
Hao Zhang, Zhuohan Li, Lianmin Zheng, Ion Stoica
Simple and Automatic Distributed Machine Learning on Ray. KDD (2021)
Lianmin Zheng, Ruochen Liu, Junru Shao, Tianqi Chen, Joseph Gonzalez, Ion Stoica, Ameer Haj-Ali
TenSet: A Large-scale Program Performance Dataset for Learned Tensor Compilers. NeurIPS Datasets and Benchmarks (2021)
Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael W. Mahoney, Joseph Gonzalez
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training. ICML (2021)
Lianmin Zheng, Chengfan Jia, Minmin Sun, Zhao Wu, Cody Hao Yu, Ameer Haj-Ali, Yida Wang, Jun Yang, Danyang Zhuo, Koushik Sen, Joseph E. Gonzalez, Ion Stoica
Ansor : Generating High-Performance Tensor Programs for Deep Learning. CoRR (2020)
Lianmin Zheng, Chengfan Jia, Minmin Sun, Zhao Wu, Cody Hao Yu, Ameer Haj-Ali, Yida Wang, Jun Yang, Danyang Zhuo, Koushik Sen, Joseph E. Gonzalez, Ion Stoica
Ansor: Generating High-Performance Tensor Programs for Deep Learning. OSDI (2020)
Leyuan Wang, Zhi Chen, Yizhi Liu, Yao Wang, Lianmin Zheng, Mu Li, Yida Wang
A Unified Optimization Approach for CNN Model Inference on Integrated GPUs. ICPP (2019)
Thierry Moreau, Tianqi Chen, Luis Vega, Jared Roesch, Eddie Q. Yan, Lianmin Zheng, Josh Fromm, Ziheng Jiang, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy
A Hardware-Software Blueprint for Flexible Deep Learning Specialization. IEEE Micro 39 (5) (2019)
Leyuan Wang, Zhi Chen, Yizhi Liu, Yao Wang, Lianmin Zheng, Mu Li, Yida Wang
A Unified Optimization Approach for CNN Model Inference on Integrated GPUs. CoRR (2019)
Tianqi Chen, Lianmin Zheng, Eddie Q. Yan, Ziheng Jiang, Thierry Moreau, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy
Learning to Optimize Tensor Programs. CoRR (2018)
Tianqi Chen, Thierry Moreau, Ziheng Jiang, Lianmin Zheng, Eddie Q. Yan, Haichen Shen, Meghan Cowan, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy
TVM: An Automated End-to-End Optimizing Compiler for Deep Learning. OSDI (2018)
Tianqi Chen, Lianmin Zheng, Eddie Q. Yan, Ziheng Jiang, Thierry Moreau, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy
Learning to Optimize Tensor Programs. NeurIPS (2018)
Yiran Wu, Sihao Ying, Lianmin Zheng
Size-to-depth: A New Perspective for Single Image Depth Estimation. CoRR (2018)
Lianmin Zheng, Jiacheng Yang, Han Cai, Ming Zhou, Weinan Zhang, Jun Wang, Yong Yu
MAgent: A Many-Agent Reinforcement Learning Platform for Artificial Collective Intelligence. AAAI (2018)
Lianmin Zheng, Jiacheng Yang, Han Cai, Weinan Zhang, Jun Wang, Yong Yu
MAgent: A Many-Agent Reinforcement Learning Platform for Artificial Collective Intelligence. CoRR (2017)