MAgent: A Many-Agent Reinforcement Learning Platform for Artificial Collective Intelligence. - Lianmin Zheng; Jiacheng Yang; Han Cai; Weinan Zhang 001; Jun Wang 012; Yong Yu 001 (CoRR, 2017)

MAgent: A Many-Agent Reinforcement Learning Platform for Artificial Collective Intelligence. - Lianmin Zheng; Jiacheng Yang; Han Cai; Ming Zhou 006; Weinan Zhang 001; Jun Wang 012; Yong Yu 001 (AAAI, 2018)

Learning to Optimize Tensor Programs. - Tianqi Chen 001; Lianmin Zheng; Eddie Q. Yan; Ziheng Jiang; Thierry Moreau; Luis Ceze; Carlos Guestrin; Arvind Krishnamurthy (NeurIPS, 2018)

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning. - Tianqi Chen 001; Thierry Moreau; Ziheng Jiang; Lianmin Zheng; Eddie Q. Yan; Haichen Shen; Meghan Cowan; Leyuan Wang; Yuwei Hu; Luis Ceze; Carlos Guestrin; Arvind Krishnamurthy (OSDI, 2018)

Size-to-depth: A New Perspective for Single Image Depth Estimation. - Yiran Wu; Sihao Ying; Lianmin Zheng (CoRR, 2018)

A Unified Optimization Approach for CNN Model Inference on Integrated GPUs. - Leyuan Wang; Zhi Chen 030; Yizhi Liu; Yao Wang; Lianmin Zheng; Mu Li 003; Yida Wang 003 (ICPP, 2019)

A Hardware-Software Blueprint for Flexible Deep Learning Specialization. - Thierry Moreau; Tianqi Chen 001; Luis Vega; Jared Roesch; Eddie Q. Yan; Lianmin Zheng; Josh Fromm; Ziheng Jiang; Luis Ceze; Carlos Guestrin; Arvind Krishnamurthy (IEEE Micro, 2019)

Ansor: Generating High-Performance Tensor Programs for Deep Learning. - Lianmin Zheng; Chengfan Jia; Minmin Sun; Zhao Wu; Cody Hao Yu; Ameer Haj-Ali; Yida Wang 003; Jun Yang; Danyang Zhuo; Koushik Sen; Joseph E. Gonzalez; Ion Stoica (OSDI, 2020)

ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training. - Jianfei Chen; Lianmin Zheng; Zhewei Yao; Dequan Wang; Ion Stoica; Michael W. Mahoney; Joseph Gonzalez 001 (ICML, 2021)

Simple and Automatic Distributed Machine Learning on Ray. - Hao Zhang 025; Zhuohan Li 001; Lianmin Zheng; Ion Stoica (KDD, 2021)

TenSet: A Large-scale Program Performance Dataset for Learned Tensor Compilers. - Lianmin Zheng; Ruochen Liu; Junru Shao; Tianqi Chen 001; Joseph Gonzalez 001; Ion Stoica; Ameer Haj-Ali (NeurIPS Datasets and Benchmarks, 2021)

GACT: Activation Compressed Training for Generic Network Architectures. - Xiaoxuan Liu; Lianmin Zheng; Dequan Wang; Yukuo Cen; Weize Chen; Xu Han 007; Jianfei Chen; Zhiyuan Liu 001; Jie Tang 001; Joey Gonzalez; Michael W. Mahoney; Alvin Cheung (ICML, 2022)

Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning. - Lianmin Zheng; Zhuohan Li 001; Hao Zhang 025; Yonghao Zhuang 001; Zhifeng Chen; Yanping Huang; Yida Wang 003; Yuanzhong Xu; Danyang Zhuo; Eric P. Xing; Joseph E. Gonzalez; Ion Stoica (OSDI, 2022)

Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning. - Lianmin Zheng; Zhuohan Li 001; Hao Zhang 025; Yonghao Zhuang 001; Zhifeng Chen; Yanping Huang; Yida Wang 003; Yuanzhong Xu; Danyang Zhuo; Joseph E. Gonzalez; Ion Stoica (CoRR, 2022)

GACT: Activation Compressed Training for General Architectures. - Xiaoxuan Liu; Lianmin Zheng; Dequan Wang; Yukuo Cen; Weize Chen; Xu Han 007; Jianfei Chen; Zhiyuan Liu 001; Jie Tang 001; Joey Gonzalez; Michael W. Mahoney; Alvin Cheung (CoRR, 2022)

NumS: Scalable Array Programming for the Cloud. - Melih Elibol; Vinamra Benara; Samyu Yagati; Lianmin Zheng; Alvin Cheung; Michael I. Jordan; Ion Stoica (CoRR, 2022)

TensorIR: An Abstraction for Automatic Tensorized Program Optimization. - Siyuan Feng; Bohan Hou; Hongyi Jin; Wuwei Lin; Junru Shao; Ruihang Lai; Zihao Ye 001; Lianmin Zheng; Cody Hao Yu; Yong Yu 001; Tianqi Chen 001 (ASPLOS (2), 2023)

FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU. - Ying Sheng 007; Lianmin Zheng; Binhang Yuan; Zhuohan Li 001; Max Ryabinin; Beidi Chen; Percy Liang; Christopher Ré; Ion Stoica; Ce Zhang 001 (ICML, 2023)

On Optimizing the Communication of Model Parallelism. - Yonghao Zhuang 001; Lianmin Zheng; Zhuohan Li 001; Eric P. Xing; Qirong Ho; Joseph Gonzalez 001; Ion Stoica; Hao Zhang 025; Hexu Zhao (MLSys, 2023)

H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. - Zhenyu Zhang 015; Ying Sheng 007; Tianyi Zhou 001; Tianlong Chen 001; Lianmin Zheng; Ruisi Cai; Zhao Song 002; Yuandong Tian; Christopher Ré; Clark W. Barrett; Zhangyang Wang; Beidi Chen (NeurIPS, 2023)

Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena. - Lianmin Zheng; Wei-Lin Chiang; Ying Sheng 007; Siyuan Zhuang; Zhanghao Wu; Yonghao Zhuang 001; Zi Lin; Zhuohan Li 001; Dacheng Li; Eric P. Xing; Hao Zhang 025; Joseph E. Gonzalez; et al. (NeurIPS, 2023)

Towards Optimal Caching and Model Selection for Large Model Inference. - Banghua Zhu; Ying Sheng 007; Lianmin Zheng; Clark W. Barrett; Michael I. Jordan; Jiantao Jiao (NeurIPS, 2023)

AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving. - Zhuohan Li 001; Lianmin Zheng; Yinmin Zhong; Vincent Liu 001; Ying Sheng 007; Xin Jin 008; Yanping Huang; Zhifeng Chen; Hao Zhang 025; Joseph E. Gonzalez; Ion Stoica (OSDI, 2023)

Efficient Memory Management for Large Language Model Serving with PagedAttention. - Woosuk Kwon; Zhuohan Li 001; Siyuan Zhuang; Ying Sheng 007; Lianmin Zheng; Cody Hao Yu; Joseph Gonzalez 001; Hao Zhang 025; Ion Stoica (SOSP, 2023)

High-throughput Generative Inference of Large Language Models with a Single GPU. - Ying Sheng 007; Lianmin Zheng; Binhang Yuan; Zhuohan Li 001; Max Ryabinin; Daniel Y. Fu; Zhiqiang Xie; Beidi Chen; Clark W. Barrett; Joseph E. Gonzalez; Percy Liang; Christopher Ré; et al. (CoRR, 2023)

On Optimal Caching and Model Multiplexing for Large Model Inference. - Banghua Zhu; Ying Sheng 007; Lianmin Zheng; Clark W. Barrett; Michael I. Jordan; Jiantao Jiao (CoRR, 2023)

H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. - Zhenyu Zhang 015; Ying Sheng 007; Tianyi Zhou 002; Tianlong Chen 001; Lianmin Zheng; Ruisi Cai; Zhao Song 002; Yuandong Tian; Christopher Ré; Clark W. Barrett; Zhangyang Wang; Beidi Chen (CoRR, 2023)

S-LoRA: Serving Thousands of Concurrent LoRA Adapters. - Ying Sheng 007; Shiyi Cao; Dacheng Li; Coleman Hooper; Nicholas Lee; Shuo Yang; Christopher Chou; Banghua Zhu; Lianmin Zheng; Kurt Keutzer; Joseph E. Gonzalez; Ion Stoica (CoRR, 2023)

Rethinking Benchmark and Contamination for Language Models with Rephrased Samples. - Shuo Yang; Wei-Lin Chiang; Lianmin Zheng; Joseph E. Gonzalez; Ion Stoica (CoRR, 2023)

Efficiently Programming Large Language Models using SGLang. - Lianmin Zheng; Liangsheng Yin; Zhiqiang Xie; Jeff Huang 001; Chuyue Sun; Cody Hao Yu; Shiyi Cao; Christos Kozyrakis; Ion Stoica; Joseph E. Gonzalez; Clark W. Barrett; Ying Sheng 007 (CoRR, 2023)

LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset. - Lianmin Zheng; Wei-Lin Chiang; Ying Sheng 007; Tianle Li; Siyuan Zhuang; Zhanghao Wu; Yonghao Zhuang 001; Zhuohan Li 001; Zi Lin; Eric P. Xing; Joseph E. Gonzalez; Ion Stoica; et al. (ICLR, 2024)

Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference. - Wei-Lin Chiang; Lianmin Zheng; Ying Sheng 007; Anastasios Nikolas Angelopoulos; Tianle Li; Dacheng Li; Banghua Zhu; Hao Zhang 025; Michael I. Jordan; Joseph E. Gonzalez; Ion Stoica (ICML, 2024)

SLoRA: Scalable Serving of Thousands of LoRA Adapters. - Ying Sheng 007; Shiyi Cao; Dacheng Li; Coleman Hooper; Nicholas Lee; Shuo Yang; Christopher Chou; Banghua Zhu; Lianmin Zheng; Kurt Keutzer; Joseph Gonzalez 001; Ion Stoica (MLSys, 2024)

SGLang: Efficient Execution of Structured Language Model Programs. - Lianmin Zheng; Liangsheng Yin; Zhiqiang Xie; Chuyue Sun; Jeff Huang 001; Cody Hao Yu; Shiyi Cao; Christos Kozyrakis; Ion Stoica; Joseph E. Gonzalez; Clark W. Barrett; Ying Sheng 007 (NeurIPS, 2024)

Post-Training Sparse Attention with Double Sparsity. - Shuo Yang; Ying Sheng 007; Joseph E. Gonzalez; Ion Stoica; Lianmin Zheng (CoRR, 2024)

BlendServe: Optimizing Offline Inference for Auto-regressive Large Models with Resource-aware Batching. - Yilong Zhao; Shuo Yang; Kan Zhu; Lianmin Zheng; Baris Kasikci; Yang Zhou; Jiarong Xing; Ion Stoica (CoRR, 2024)

Scalable and Efficient Systems for Large Deep Learning Models - Lianmin Zheng (2024)