Xupeng Miao

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 70

Top Topics

Privacy Preserving

Extended Abstract

Top Venues

Proc. VLDB Endow.

SIGMOD Conference

Publications

Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, Xinhao Cheng, Zeyu Wang, Zhengxin Zhang, Rae Ying Yee Wong, Alan Zhu, Lijie Yang, Xiaoxiang Shi, Chunan Shi, Zhuoming Chen, Daiyaan Arfeen, Reyna Abhyankar, Zhihao Jia
SpecInfer: Accelerating Large Language Model Serving with Tree-based Speculative Inference and Verification. ASPLOS (3) (2024)
Hailin Zhang, Xiaodong Ji, Yilin Chen, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Weipeng Chen, Bin Cui
PQCache: Product Quantization-based KVCache for Long Context LLM Inference. CoRR (2024)
Yixuan Mei, Yonghao Zhuang, Xupeng Miao, Juncheng Yang, Zhihao Jia, Rashmi Vinayak
Helix: Distributed Serving of Large Language Models via Max-Flow on Heterogeneous GPUs. CoRR (2024)
Zihao Yu, Haoyang Li, Fangcheng Fu, Xupeng Miao, Bin Cui
Accelerating Text-to-Image Editing via Cache-Enabled Sparse Diffusion Inference. AAAI (2024)
Xupeng Miao, Chunan Shi, Jiangfei Duan, Xiaoli Xi, Dahua Lin, Bin Cui, Zhihao Jia
SpotServe: Serving Generative Large Language Models on Preemptible Instances. ASPLOS (2) (2024)
Peiwen Yuan, Xinglin Wang, Shaoxiong Feng, Boyuan Pan, Yiwei Li, Heda Wang, Xupeng Miao, Kan Li
Generative Dense Retrieval: Memory Can Be a Burden. CoRR (2024)
Zhengxin Zhang, Dan Zhao, Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, Qing Li, Yong Jiang, Zhihao Jia
Quantized Side Tuning: Fast and Memory-Efficient Tuning of Quantized Large Language Models. ACL (1) (2024)
Xupeng Miao, Zhihao Jia, Bin Cui
Demystifying Data Management for Large Language Models. SIGMOD Conference Companion (2024)
Xupeng Miao, Gabriele Oliaro, Xinhao Cheng, Mengdi Wu, Colin Unger, Zhihao Jia
FlexLLM: A System for Co-Serving Large Language Model Inference and Parameter-Efficient Finetuning. CoRR (2024)
Muyan Hu, Ashwin Venkatram, Shreyashri Biswas, Balamurugan Marimuthu, Bohan Hou, Gabriele Oliaro, Haojie Wang, Liyan Zheng, Xupeng Miao, Jidong Zhai, Zhihao Jia
Optimal Kernel Orchestration for Tensor Programs with Korch. ASPLOS (3) (2024)
Byungsoo Jeon, Mengdi Wu, Shiyi Cao, Sunghyun Kim, Sunghyun Park, Neeraj Aggarwal, Colin Unger, Daiyaan Arfeen, Peiyuan Liao, Xupeng Miao, Mohammad Alizadeh, Gregory R. Ganger, Tianqi Chen, Zhihao Jia
GraphPipe: Improving Performance and Scalability of DNN Training with Graph Pipeline Parallelism. CoRR (2024)
Peiwen Yuan, Xinglin Wang, Shaoxiong Feng, Boyuan Pan, Yiwei Li, Heda Wang, Xupeng Miao, Kan Li
Generative Dense Retrieval: Memory Can Be a Burden. EACL (1) (2024)
Jiangfei Duan, Ziang Song, Xupeng Miao, Xiaoli Xi, Dahua Lin, Harry Xu, Minjia Zhang, Zhihao Jia
Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances. NSDI (2024)
Zhengxin Zhang, Dan Zhao, Xupeng Miao, Gabriele Oliaro, Qing Li, Yong Jiang, Zhihao Jia
Quantized Side Tuning: Fast and Memory-Efficient Tuning of Quantized Large Language Models. CoRR (2024)
Muyan Hu, Ashwin Venkatram, Shreyashri Biswas, Balamurugan Marimuthu, Bohan Hou, Gabriele Oliaro, Haojie Wang, Liyan Zheng, Xupeng Miao, Jidong Zhai
Optimal Kernel Orchestration for Tensor Programs with Korch. CoRR (2024)
Yingxia Shao, Hongzheng Li, Xizhi Gu, Hongbo Yin, Yawen Li, Xupeng Miao, Wentao Zhang, Bin Cui, Lei Chen
Distributed Graph Neural Network Training: A Survey. ACM Comput. Surv. 56 (8) (2024)
Jiangfei Duan, Ziang Song, Xupeng Miao, Xiaoli Xi, Dahua Lin, Harry Xu, Minjia Zhang, Zhihao Jia
Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances. CoRR (2024)
Zhuo Chang, Xinyi Zhang, Yang Li, Xupeng Miao, Yanzhao Qin, Bin Cui
MFIX: An Efficient and Reliable Index Advisor via Multi-Fidelity Bayesian Optimization. ICDE (2024)
Liyan Zheng, Haojie Wang, Jidong Zhai, Muyan Hu, Zixuan Ma, Tuowei Wang, Shuhong Huang, Xupeng Miao, Shizhi Tang, Kezhao Huang, Zhihao Jia
EINNET: Optimizing Tensor Programs with Derivation-Based Transformations. OSDI (2023)
Hailin Zhang, Penghao Zhao, Xupeng Miao, Yingxia Shao, Zirui Liu, Tong Yang, Bin Cui
Experimental Analysis of Large-scale Learnable Vector Storage Compression. Proc. VLDB Endow. 17 (4) (2023)
Xupeng Miao, Wentao Zhang, Yuezihan Jiang, Fangcheng Fu, Yingxia Shao, Lei Chen, Yangyu Tao, Gang Cao, Bin Cui
CG: a privacy preserving collaborative graph neural network training framework. VLDB J. 32 (4) (2023)
Xiaonan Nie, Yi Liu, Fangcheng Fu, Jinbao Xue, Dian Jiao, Xupeng Miao, Yangyu Tao, Bin Cui
Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent. CoRR (2023)
Xiaonan Nie, Xupeng Miao, Zilong Wang, Zichao Yang, Jilong Xue, Lingxiao Ma, Gang Cao, Bin Cui
FlexMoE: Scaling Large-scale Sparse Pre-trained Model Training via Dynamic Device Placement. CoRR (2023)
Xiaonan Nie, Yi Liu, Fangcheng Fu, Jinbao Xue, Dian Jiao, Xupeng Miao, Yangyu Tao, Bin Cui
Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent. Proc. VLDB Endow. 16 (12) (2023)
Yujie Wang, Youhe Jiang, Xupeng Miao, Fangcheng Fu, Xiaonan Nie, Bin Cui
Improving Automatic Parallel Training via Balanced Memory Workload Optimization. CoRR (2023)
Ziyu Guo, Renrui Zhang, Longtian Qiu, Xianzheng Ma, Xupeng Miao, Xuming He, Bin Cui
CALIP: Zero-Shot Enhancement of CLIP with Parameter-Free Attention. AAAI (2023)
Hailin Zhang, Yujing Wang, Qi Chen, Ruiheng Chang, Ting Zhang, Ziming Miao, Yingyan Hou, Yang Ding, Xupeng Miao, Haonan Wang, Bochen Pang, Yuefeng Zhan, Hao Sun, Weiwei Deng, Qi Zhang, Fan Yang, Xing Xie, Mao Yang, Bin Cui
Model-enhanced Vector Index. NeurIPS (2023)
Xupeng Miao, Yining Shi, Zhi Yang, Bin Cui, Zhihao Jia
SDPipe: A Semi-Decentralized Framework for Heterogeneity-aware Pipeline-parallel Training. Proc. VLDB Endow. 16 (9) (2023)
Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, Xinhao Cheng, Zeyu Wang, Rae Ying Yee Wong, Zhuoming Chen, Daiyaan Arfeen, Reyna Abhyankar, Zhihao Jia
SpecInfer: Accelerating Generative LLM Serving with Speculative Inference and Token Tree Verification. CoRR (2023)
Hailin Zhang, Yujing Wang, Qi Chen, Ruiheng Chang, Ting Zhang, Ziming Miao, Yingyan Hou, Yang Ding, Xupeng Miao, Haonan Wang, Bochen Pang, Yuefeng Zhan, Hao Sun, Weiwei Deng, Qi Zhang, Fan Yang, Xing Xie, Mao Yang, Bin Cui
Model-enhanced Vector Index. CoRR (2023)
Xupeng Miao, Chunan Shi, Jiangfei Duan, Xiaoli Xi, Dahua Lin, Bin Cui, Zhihao Jia
SpotServe: Serving Generative Large Language Models on Preemptible Instances. CoRR (2023)
Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang
Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-Aware Deep Architecture. IEEE Trans. Knowl. Data Eng. 35 (2) (2023)
Xiaonan Nie, Xupeng Miao, Zilong Wang, Zichao Yang, Jilong Xue, Lingxiao Ma, Gang Cao, Bin Cui
FlexMoE: Scaling Large-scale Sparse Pre-trained Model Training via Dynamic Device Placement. Proc. ACM Manag. Data 1 (1) (2023)
Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, Xinhao Cheng, Hongyi Jin, Tianqi Chen, Zhihao Jia
Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems. CoRR (2023)
Youhe Jiang, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Bin Cui
OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning. CoRR (2023)
Youhe Jiang, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Bin Cui
OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning. IJCAI (2023)
Hailin Zhang, Penghao Zhao, Xupeng Miao, Yingxia Shao, Zirui Liu, Tong Yang, Bin Cui
Experimental Analysis of Large-scale Learnable Vector Storage Compression. CoRR (2023)
Xupeng Miao, Xiaonan Nie, Hailin Zhang, Tong Zhao, Bin Cui
Hetu: a highly efficient automatic parallel distributed deep learning system. Sci. China Inf. Sci. 66 (1) (2023)
Zihao Yu, Haoyang Li, Fangcheng Fu, Xupeng Miao, Bin Cui
FISEdit: Accelerating Text-to-image Editing via Cache-enabled Sparse Diffusion Inference. CoRR (2023)
Renrui Zhang, Ziyu Guo, Wei Zhang, Kunchang Li, Xupeng Miao, Bin Cui, Yu Qiao, Peng Gao, Hongsheng Li
PointCLIP: Point Cloud Understanding by CLIP. CVPR (2022)
Xiaonan Nie, Xupeng Miao, Zhi Yang, Bin Cui
TSPLIT: Fine-grained GPU Memory Management for Efficient DNN Training via Tensor Splitting. ICDE (2022)
Yuezihan Jiang, Yu Cheng, Hanyu Zhao, Wentao Zhang, Xupeng Miao, Yu He, Liang Wang, Zhi Yang, Bin Cui
Zoomer: Boosting Retrieval on Web-scale Graphs by Regions of Interest. ICDE (2022)
Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang
Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture (Extended Abstract). ICDE (2022)
Hongbo Yin, Yingxia Shao, Xupeng Miao, Yawen Li, Bin Cui
Scalable Graph Sampling on GPUs with Compressed Graph. CIKM (2022)
Fangcheng Fu, Xupeng Miao, Jiawei Jiang, Huanran Xue, Bin Cui
Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates. CoRR (2022)
Xupeng Miao, Yujie Wang, Youhe Jiang, Chunan Shi, Xiaonan Nie, Hailin Zhang, Bin Cui
Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism. CoRR (2022)
Youhe Jiang, Xupeng Miao, Xiaonan Nie, Bin Cui
OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning. CoRR (2022)
Ziyu Guo, Renrui Zhang, Longtian Qiu, Xianzheng Ma, Xupeng Miao, Xuming He, Bin Cui
CALIP: Zero-Shot Enhancement of CLIP with Parameter-free Attention. CoRR (2022)
Yingxia Shao, Hongzheng Li, Xizhi Gu, Hongbo Yin, Yawen Li, Xupeng Miao, Wentao Zhang, Bin Cui, Lei Chen
Distributed Graph Neural Network Training: A Survey. CoRR (2022)
Xiaonan Nie, Pinxue Zhao, Xupeng Miao, Tong Zhao, Bin Cui
HetuMoE: An Efficient Trillion-scale Mixture-of-Expert Distributed Training System. CoRR (2022)
Xupeng Miao, Yining Shi, Hailin Zhang, Xin Zhang, Xiaonan Nie, Zhi Yang, Bin Cui
HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training. SIGMOD Conference (2022)
Sicong Dong, Xupeng Miao, Pengkai Liu, Xin Wang, Bin Cui, Jianxin Li
HET-KG: Communication-Efficient Knowledge Graph Embedding Training via Hotness-Aware Cache. ICDE (2022)
Fangcheng Fu, Xupeng Miao, Jiawei Jiang, Huanran Xue, Bin Cui
Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Update. Proc. VLDB Endow. 15 (10) (2022)
Xupeng Miao, Yujie Wang, Youhe Jiang, Chunan Shi, Xiaonan Nie, Hailin Zhang, Bin Cui
Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism. Proc. VLDB Endow. 16 (3) (2022)
Xupeng Miao, Lingxiao Ma, Zhi Yang, Yingxia Shao, Bin Cui, Lele Yu, Jiawei Jiang
CuWide: Towards Efficient Flow-Based Training for Sparse Wide Models on GPUs. IEEE Trans. Knowl. Data Eng. 34 (9) (2022)
Yuezihan Jiang, Yu Cheng, Hanyu Zhao, Wentao Zhang, Xupeng Miao, Yu He, Liang Wang, Zhi Yang, Bin Cui
ZOOMER: Boosting Retrieval on Web-scale Graphs by Regions of Interest. CoRR (2022)
Yingxia Shao, Shiyue Huang, Yawen Li, Xupeng Miao, Bin Cui, Lei Chen
Memory-aware framework for fast and scalable second-order random walk over billion-edge natural graphs. VLDB J. 30 (5) (2021)
Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang, Zhichao Han, Bo Li, Wei Min, Susie Xi Rao, Hansheng Ren, Yinan Shan, Yingxia Shao, Yujie Wang, Fan Wu, Hui Xue, Yaming Yang, Zitao Zhang, Yang Zhao, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang
DeGNN: Improving Graph Neural Networks with Graph Decomposition. KDD (2021)
Wentao Zhang, Yuezihan Jiang, Yang Li, Zeang Sheng, Yu Shen, Xupeng Miao, Liang Wang, Zhi Yang, Bin Cui
ROD: Reception-aware Online Distillation for Sparse Graphs. KDD (2021)
Xupeng Miao, Xiaonan Nie, Yingxia Shao, Zhi Yang, Jiawei Jiang, Lingxiao Ma, Bin Cui
Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce. SIGMOD Conference (2021)
Xiaonan Nie, Shijie Cao, Xupeng Miao, Lingxiao Ma, Jilong Xue, Youshan Miao, Zichao Yang, Zhi Yang, Bin Cui
Dense-to-Sparse Gate for Mixture-of-Experts. CoRR (2021)
Xupeng Miao, Hailin Zhang, Yining Shi, Xiaonan Nie, Zhi Yang, Yangyu Tao, Bin Cui
HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework. CoRR (2021)
Wentao Zhang, Yuezihan Jiang, Yang Li, Zeang Sheng, Yu Shen, Xupeng Miao, Liang Wang, Zhi Yang, Bin Cui
ROD: Reception-aware Online Distillation for Sparse Graphs. CoRR (2021)
Xupeng Miao, Lingxiao Ma, Zhi Yang, Yingxia Shao, Bin Cui, Lele Yu, Jiawei Jiang
CuWide: Towards Efficient Flow-based Training for Sparse Wide Models on GPUs (Extended Abstract). ICDE (2021)
Renrui Zhang, Ziyu Guo, Wei Zhang, Kunchang Li, Xupeng Miao, Bin Cui, Yu Qiao, Peng Gao, Hongsheng Li
PointCLIP: Point Cloud Understanding by CLIP. CoRR (2021)
Xupeng Miao, Hailin Zhang, Yining Shi, Xiaonan Nie, Zhi Yang, Yangyu Tao, Bin Cui
HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework. Proc. VLDB Endow. 15 (2) (2021)
Wentao Zhang, Xupeng Miao, Yingxia Shao, Jiawei Jiang, Lei Chen, Olivier Ruas, Bin Cui
Reliable Data Distillation on Graph Convolutional Network. SIGMOD Conference (2020)
Yingxia Shao, Shiyue Huang, Xupeng Miao, Bin Cui, Lei Chen
Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs. SIGMOD Conference (2020)
Jiawei Jiang, Pin Xiao, Lele Yu, Xiaosen Li, Jiefeng Cheng, Xupeng Miao, Zhipeng Zhang, Bin Cui
PSGraph: How Tencent trains extremely large-scale graphs with Spark? ICDE (2020)
Zhipeng Zhang, Bin Cui, Yingxia Shao, Lele Yu, Jiawei Jiang, Xupeng Miao
PS2: Parameter Server on Spark. SIGMOD Conference (2019)