PS2: Parameter Server on Spark. - Zhipeng Zhang; Bin Cui 001; Yingxia Shao; Lele Yu; Jiawei Jiang 001; Xupeng Miao (SIGMOD Conference, 2019)

PSGraph: How Tencent trains extremely large-scale graphs with Spark? - Jiawei Jiang 001; Pin Xiao; Lele Yu; Xiaosen Li; Jiefeng Cheng; Xupeng Miao; Zhipeng Zhang; Bin Cui 001 (ICDE, 2020)

Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs. - Yingxia Shao; Shiyue Huang; Xupeng Miao; Bin Cui 001; Lei Chen 002 (SIGMOD Conference, 2020)

Reliable Data Distillation on Graph Convolutional Network. - Wentao Zhang 001; Xupeng Miao; Yingxia Shao; Jiawei Jiang 001; Lei Chen 002; Olivier Ruas; Bin Cui 001 (SIGMOD Conference, 2020)

CuWide: Towards Efficient Flow-based Training for Sparse Wide Models on GPUs (Extended Abstract). - Xupeng Miao; Lingxiao Ma; Zhi Yang 001; Yingxia Shao; Bin Cui 001; Lele Yu; Jiawei Jiang 001 (ICDE, 2021)

DeGNN: Improving Graph Neural Networks with Graph Decomposition. - Xupeng Miao; Nezihe Merve Gürel; Wentao Zhang 001; Zhichao Han 001; Bo Li 026; Wei Min; Susie Xi Rao; Hansheng Ren; Yinan Shan; Yingxia Shao; Yujie Wang; Fan Wu 011; et al. (KDD, 2021)

ROD: Reception-aware Online Distillation for Sparse Graphs. - Wentao Zhang 001; Yuezihan Jiang; Yang Li 106; Zeang Sheng; Yu Shen 003; Xupeng Miao; Liang Wang 001; Zhi Yang 001; Bin Cui 001 (KDD, 2021)

Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce. - Xupeng Miao; Xiaonan Nie; Yingxia Shao; Zhi Yang 001; Jiawei Jiang 001; Lingxiao Ma; Bin Cui 001 (SIGMOD Conference, 2021)

Dense-to-Sparse Gate for Mixture-of-Experts. - Xiaonan Nie; Shijie Cao; Xupeng Miao; Lingxiao Ma; Jilong Xue; Youshan Miao; Zichao Yang; Zhi Yang 001; Bin Cui 001 (CoRR, 2021)

HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework. - Xupeng Miao; Hailin Zhang 004; Yining Shi 001; Xiaonan Nie; Zhi Yang 001; Yangyu Tao; Bin Cui 001 (Proc. VLDB Endow., 2021)

Memory-aware framework for fast and scalable second-order random walk over billion-edge natural graphs. - Yingxia Shao; Shiyue Huang; Yawen Li 001; Xupeng Miao; Bin Cui 001; Lei Chen 002 (VLDB J., 2021)

Scalable Graph Sampling on GPUs with Compressed Graph. - Hongbo Yin; Yingxia Shao; Xupeng Miao; Yawen Li 001; Bin Cui 001 (CIKM, 2022)

PointCLIP: Point Cloud Understanding by CLIP. - Renrui Zhang; Ziyu Guo; Wei Zhang 056; Kunchang Li 002; Xupeng Miao; Bin Cui 001; Yu Qiao 001; Peng Gao 007; Hongsheng Li 001 (CVPR, 2022)

HET-KG: Communication-Efficient Knowledge Graph Embedding Training via Hotness-Aware Cache. - Sicong Dong; Xupeng Miao; Pengkai Liu; Xin Wang 030; Bin Cui 001; Jianxin Li 001 (ICDE, 2022)

Zoomer: Boosting Retrieval on Web-scale Graphs by Regions of Interest. - Yuezihan Jiang; Yu Cheng; Hanyu Zhao; Wentao Zhang 001; Xupeng Miao; Yu He; Liang Wang 001; Zhi Yang 001; Bin Cui 001 (ICDE, 2022)

Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture (Extended Abstract). - Xupeng Miao; Wentao Zhang 001; Yingxia Shao; Bin Cui 001; Lei Chen 002; Ce Zhang 001; Jiawei Jiang 001 (ICDE, 2022)

TSPLIT: Fine-grained GPU Memory Management for Efficient DNN Training via Tensor Splitting. - Xiaonan Nie; Xupeng Miao; Zhi Yang 001; Bin Cui 001 (ICDE, 2022)

HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training. - Xupeng Miao; Yining Shi 001; Hailin Zhang 004; Xin Zhang; Xiaonan Nie; Zhi Yang 001; Bin Cui 001 (SIGMOD Conference, 2022)

HetuMoE: An Efficient Trillion-scale Mixture-of-Expert Distributed Training System. - Xiaonan Nie; Pinxue Zhao; Xupeng Miao; Tong Zhao; Bin Cui 001 (CoRR, 2022)

Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates. - Fangcheng Fu; Xupeng Miao; Jiawei Jiang 001; Huanran Xue; Bin Cui 001 (CoRR, 2022)

OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning. - Youhe Jiang; Xupeng Miao; Xiaonan Nie; Bin Cui 001 (CoRR, 2022)

Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Update. - Fangcheng Fu; Xupeng Miao; Jiawei Jiang 001; Huanran Xue; Bin Cui 001 (Proc. VLDB Endow., 2022)

Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism. - Xupeng Miao; Yujie Wang; Youhe Jiang; Chunan Shi; Xiaonan Nie; Hailin Zhang 004; Bin Cui 001 (Proc. VLDB Endow., 2022)

CuWide: Towards Efficient Flow-Based Training for Sparse Wide Models on GPUs. - Xupeng Miao; Lingxiao Ma; Zhi Yang 001; Yingxia Shao; Bin Cui 001; Lele Yu; Jiawei Jiang 001 (IEEE Trans. Knowl. Data Eng., 2022)

CALIP: Zero-Shot Enhancement of CLIP with Parameter-Free Attention. - Ziyu Guo; Renrui Zhang; Longtian Qiu; Xianzheng Ma; Xupeng Miao; Xuming He 001; Bin Cui 001 (AAAI, 2023)

OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning. - Youhe Jiang; Fangcheng Fu; Xupeng Miao; Xiaonan Nie; Bin Cui 001 (IJCAI, 2023)

Model-enhanced Vector Index. - Hailin Zhang 004; Yujing Wang; Qi Chen 009; Ruiheng Chang; Ting Zhang 002; Ziming Miao; Yingyan Hou; Yang Ding; Xupeng Miao; Haonan Wang; Bochen Pang; Yuefeng Zhan; et al. (NeurIPS, 2023)

EINNET: Optimizing Tensor Programs with Derivation-Based Transformations. - Liyan Zheng 001; Haojie Wang; Jidong Zhai; Muyan Hu; Zixuan Ma; Tuowei Wang; Shuhong Huang; Xupeng Miao; Shizhi Tang; Kezhao Huang; Zhihao Jia (OSDI, 2023)

SpecInfer: Accelerating Generative LLM Serving with Speculative Inference and Token Tree Verification. - Xupeng Miao; Gabriele Oliaro; Zhihao Zhang 001; Xinhao Cheng; Zeyu Wang; Rae Ying Yee Wong; Zhuoming Chen; Daiyaan Arfeen; Reyna Abhyankar; Zhihao Jia (CoRR, 2023)

FISEdit: Accelerating Text-to-image Editing via Cache-enabled Sparse Diffusion Inference. - Zihao Yu; Haoyang Li; Fangcheng Fu; Xupeng Miao; Bin Cui 001 (CoRR, 2023)

Improving Automatic Parallel Training via Balanced Memory Workload Optimization. - Yujie Wang; Youhe Jiang; Xupeng Miao; Fangcheng Fu; Xiaonan Nie; Bin Cui 001 (CoRR, 2023)

Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems. - Xupeng Miao; Gabriele Oliaro; Zhihao Zhang 001; Xinhao Cheng; Hongyi Jin; Tianqi Chen 001; Zhihao Jia (CoRR, 2023)

FlexMoE: Scaling Large-scale Sparse Pre-trained Model Training via Dynamic Device Placement. - Xiaonan Nie; Xupeng Miao; Zilong Wang; Zichao Yang; Jilong Xue; Lingxiao Ma; Gang Cao; Bin Cui 001 (Proc. ACM Manag. Data, 2023)

SDPipe: A Semi-Decentralized Framework for Heterogeneity-aware Pipeline-parallel Training. - Xupeng Miao; Yining Shi 001; Zhi Yang 001; Bin Cui 001; Zhihao Jia (Proc. VLDB Endow., 2023)

Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent. - Xiaonan Nie; Yi Liu; Fangcheng Fu; Jinbao Xue; Dian Jiao; Xupeng Miao; Yangyu Tao; Bin Cui 001 (Proc. VLDB Endow., 2023)

Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-Aware Deep Architecture. - Xupeng Miao; Wentao Zhang 001; Yingxia Shao; Bin Cui 001; Lei Chen 002; Ce Zhang 001; Jiawei Jiang 001 (IEEE Trans. Knowl. Data Eng., 2023)

Hetu: a highly efficient automatic parallel distributed deep learning system. - Xupeng Miao; Xiaonan Nie; Hailin Zhang 004; Tong Zhao; Bin Cui 001 (Sci. China Inf. Sci., 2023)

P2CG: a privacy preserving collaborative graph neural network training framework. - Xupeng Miao; Wentao Zhang 001; Yuezihan Jiang; Fangcheng Fu; Yingxia Shao; Lei Chen 002; Yangyu Tao; Gang Cao; Bin Cui 001 (VLDB J., 2023)

Experimental Analysis of Large-scale Learnable Vector Storage Compression. - Hailin Zhang 004; Penghao Zhao; Xupeng Miao; Yingxia Shao; Zirui Liu 002; Tong Yang 003; Bin Cui 001 (Proc. VLDB Endow., 2023)

Accelerating Text-to-Image Editing via Cache-Enabled Sparse Diffusion Inference. - Zihao Yu; Haoyang Li; Fangcheng Fu; Xupeng Miao; Bin Cui 001 (AAAI, 2024)

Quantized Side Tuning: Fast and Memory-Efficient Tuning of Quantized Large Language Models. - Zhengxin Zhang; Dan Zhao 003; Xupeng Miao; Gabriele Oliaro; Zhihao Zhang 001; Qing Li 006; Yong Jiang 001; Zhihao Jia (ACL (1), 2024)

Optimal Kernel Orchestration for Tensor Programs with Korch. - Muyan Hu; Ashwin Venkatram; Shreyashri Biswas; Balamurugan Marimuthu; Bohan Hou; Gabriele Oliaro; Haojie Wang; Liyan Zheng 001; Xupeng Miao; Jidong Zhai; Zhihao Jia (ASPLOS (3), 2024)

SpecInfer: Accelerating Large Language Model Serving with Tree-based Speculative Inference and Verification. - Xupeng Miao; Gabriele Oliaro; Zhihao Zhang 001; Xinhao Cheng; Zeyu Wang; Zhengxin Zhang; Rae Ying Yee Wong; Alan Zhu 001; Lijie Yang 003; Xiaoxiang Shi; Chunan Shi; Zhuoming Chen; et al. (ASPLOS (3), 2024)

SpotServe: Serving Generative Large Language Models on Preemptible Instances. - Xupeng Miao; Chunan Shi; Jiangfei Duan; Xiaoli Xi; Dahua Lin; Bin Cui 001; Zhihao Jia (ASPLOS (2), 2024)

Generative Dense Retrieval: Memory Can Be a Burden. - Peiwen Yuan; Xinglin Wang; Shaoxiong Feng; Boyuan Pan; Yiwei Li 001; Heda Wang; Xupeng Miao; Kan Li 001 (EACL (1), 2024)

MFIX: An Efficient and Reliable Index Advisor via Multi-Fidelity Bayesian Optimization. - Zhuo Chang; Xinyi Zhang 002; Yang Li 106; Xupeng Miao; Yanzhao Qin; Bin Cui 001 (ICDE, 2024)

X-former Elucidator: Reviving Efficient Attention for Long Context Language Modeling. - Xupeng Miao; Shenhan Zhu; Fangcheng Fu; Ziyu Guo; Zhi Yang 001; Yaofeng Tu; Zhihao Jia; Bin Cui 001 (IJCAI, 2024)

LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing. - Xiaonan Nie; Qibin Liu; Fangcheng Fu; Shenhan Zhu; Xupeng Miao; Xiaoyang Li; Yang Zhang; Shouda Liu; Bin Cui 001 (NeurIPS, 2024)

Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances. - Jiangfei Duan; Ziang Song; Xupeng Miao; Xiaoli Xi; Dahua Lin; Harry Xu 001; Minjia Zhang; Zhihao Jia (NSDI, 2024)

Atlas: Hierarchical Partitioning for Quantum Circuit Simulation on GPUs. - Mingkuan Xu; Shiyi Cao; Xupeng Miao; Umut A. Acar; Zhihao Jia (SC, 2024)

Demystifying Data Management for Large Language Models. - Xupeng Miao; Zhihao Jia; Bin Cui 001 (SIGMOD Conference Companion, 2024)

Enabling Parallelism Hot Switching for Efficient Training of Large Language Models. - Hao Ge; Fangcheng Fu; Haoyang Li; Xuanyu Wang; Sheng Lin; Yujie Wang; Xiaonan Nie; Hailin Zhang 004; Xupeng Miao; Bin Cui 001 (SOSP, 2024)

Quantized Side Tuning: Fast and Memory-Efficient Tuning of Quantized Large Language Models. - Zhengxin Zhang; Dan Zhao 003; Xupeng Miao; Gabriele Oliaro; Qing Li 006; Yong Jiang 001; Zhihao Jia (CoRR, 2024)

FlexLLM: A System for Co-Serving Large Language Model Inference and Parameter-Efficient Finetuning. - Xupeng Miao; Gabriele Oliaro; Xinhao Cheng; Mengdi Wu; Colin Unger; Zhihao Jia (CoRR, 2024)

Helix: Distributed Serving of Large Language Models via Max-Flow on Heterogeneous GPUs. - Yixuan Mei; Yonghao Zhuang 001; Xupeng Miao; Juncheng Yang; Zhihao Jia; Rashmi Vinayak (CoRR, 2024)

Atlas: Hierarchical Partitioning for Quantum Circuit Simulation on GPUs (Extended Version). - Mingkuan Xu; Shiyi Cao; Xupeng Miao; Umut A. Acar; Zhihao Jia (CoRR, 2024)

Efficient Multi-Task Large Model Training via Data Heterogeneity-aware Model Management. - Yujie Wang; Shenhan Zhu; Fangcheng Fu; Xupeng Miao; Jie Zhang; Juan Zhu; Fan Hong; Yong Li; Bin Cui 001 (CoRR, 2024)

A System for Microserving of LLMs. - Hongyi Jin; Ruihang Lai; Charlie F. Ruan; Yingcheng Wang; Todd C. Mowry; Xupeng Miao; Zhihao Jia; Tianqi Chen 001 (CoRR, 2024)

Improving Automatic Parallel Training via Balanced Memory Workload Optimization. - Yujie Wang; Youhe Jiang; Xupeng Miao; Fangcheng Fu; Shenhan Zhu; Xiaonan Nie; Yaofeng Tu; Bin Cui 001 (IEEE Trans. Knowl. Data Eng., 2024)

Distributed Graph Neural Network Training: A Survey. - Yingxia Shao; Hongzheng Li; Xizhi Gu; Hongbo Yin; Yawen Li 001; Xupeng Miao; Wentao Zhang 001; Bin Cui 001; Lei Chen 002 (ACM Comput. Surv., 2024)

GraphPipe: Improving Performance and Scalability of DNN Training with Graph Pipeline Parallelism. - Byungsoo Jeon; Mengdi Wu; Shiyi Cao; Sunghyun Kim; Sunghyun Park 004; Neeraj Aggarwal; Colin Unger; Daiyaan Arfeen; Peiyuan Liao; Xupeng Miao; Mohammad Alizadeh; Gregory R. Ganger; et al. (ASPLOS (1), 2025)

Helix: Serving Large Language Models over Heterogeneous GPUs and Network via Max-Flow. - Yixuan Mei; Yonghao Zhuang 001; Xupeng Miao; Juncheng Yang; Zhihao Jia; Rashmi Vinayak (ASPLOS (1), 2025)

Spindle: Efficient Distributed Training of Multi-Task Large Models via Wavefront Scheduling. - Yujie Wang; Shenhan Zhu; Fangcheng Fu; Xupeng Miao; Jie Zhang; Juan Zhu; Fan Hong; Yong Li; Bin Cui 001 (ASPLOS (2), 2025)

NetMoE: Accelerating MoE Training through Dynamic Sample Placement. - Xinyi Liu; Yujie Wang; Fangcheng Fu; Xupeng Miao; Shenhan Zhu; Xiaonan Nie; Bin Cui 001 (ICLR, 2025)

Mirage: A Multi-Level Superoptimizer for Tensor Programs. - Mengdi Wu; Xinhao Cheng; Shengyu Liu; Chunan Shi; Jianan Ji; Man Kit Ao; Praveen Velliengiri; Xupeng Miao; Oded Padon; Zhihao Jia (OSDI, 2025)

AdaServe: SLO-Customized LLM Serving with Fine-Grained Speculative Decoding. - Zikun Li; Zhuofu Chen; Remi Delacourt; Gabriele Oliaro; Zeyu Wang; Qinghan Chen; Shuhuai Lin; April Yang; Zhihao Zhang 001; Zhuoming Chen; Sean Lai; Xupeng Miao; et al. (CoRR, 2025)

Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs. - Youhe Jiang; Fangcheng Fu; Xiaozhe Yao; Guoliang He; Xupeng Miao; Ana Klimovic; Bin Cui 001; Binhang Yuan; Eiko Yoneki (CoRR, 2025)

Hetu v2: A General and Scalable Deep Learning System with Hierarchical and Heterogeneous Single Program Multiple Data Annotations. - Haoyang Li; Fangcheng Fu; Hao Ge; Sheng Lin; Xuanyu Wang; Jiawen Niu; Xupeng Miao; Bin Cui 001 (CoRR, 2025)

Efficient and scalable huge embedding model training via distributed cache management. - Xupeng Miao; Hailin Zhang 004; Yining Shi 001; Xiaonan Nie; Zhi Yang 001; Yangyu Tao; Jie Jiang; Bin Cui 001 (VLDB J., 2025)

PQCache: Product Quantization-based KVCache for Long Context LLM Inference. - Hailin Zhang 004; Xiaodong Ji; Yilin Chen; Fangcheng Fu; Xupeng Miao; Xiaonan Nie; Weipeng Chen; Bin Cui 001 (Proc. ACM Manag. Data, 2025)