Xupeng Miao

According to our database, Xupeng Miao authored at least 59 papers between 2019 and 2024.

Collaborative distances:

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

2024

Distributed Graph Neural Network Training: A Survey.

Yingxia Shao, Hongzheng Li, Xizhi Gu, Hongbo Yin, Yawen Li, Xupeng Miao, Wentao Zhang, Bin Cui, Lei Chen

ACM Comput. Surv., August, 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

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

PQCache: Product Quantization-based KVCache for Long Context LLM Inference.

Hailin Zhang, Xiaodong Ji, Yilin Chen, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Weipeng Chen, Bin Cui

CoRR, 2024

GraphPipe: Improving Performance and Scalability of DNN Training with Graph Pipeline Parallelism.

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

CoRR, 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, Xupeng Miao, Jidong Zhai

CoRR, 2024

Helix: Distributed Serving of Large Language Models via Max-Flow on Heterogeneous GPUs.

Yixuan Mei, Yonghao Zhuang, Xupeng Miao, Juncheng Yang, Zhihao Jia, Rashmi Vinayak

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

Quantized Side Tuning: Fast and Memory-Efficient Tuning of Quantized Large Language Models.

Zhengxin Zhang, Dan Zhao, Xupeng Miao, Gabriele Oliaro, Qing Li, Yong Jiang, Zhihao Jia

CoRR, 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, Xupeng Miao, Bin Cui

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

Demystifying Data Management for Large Language Models.

Xupeng Miao, Zhihao Jia, Bin Cui

Proceedings of the Companion of the 2024 International Conference on Management of Data, 2024

Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances.

Jiangfei Duan, Ziang Song, Xupeng Miao, Xiaoli Xi, Dahua Lin, Harry Xu, Minjia Zhang, Zhihao Jia

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

X-former Elucidator: Reviving Efficient Attention for Long Context Language Modeling.

Xupeng Miao, Shenhan Zhu, Fangcheng Fu, Ziyu Guo, Zhi Yang, Yaofeng Tu, Zhihao Jia, Bin Cui

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

MFIX: An Efficient and Reliable Index Advisor via Multi-Fidelity Bayesian Optimization.

Zhuo Chang, Xinyi Zhang, Yang Li, Xupeng Miao, Yanzhao Qin, Bin Cui

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Generative Dense Retrieval: Memory Can Be a Burden.

Peiwen Yuan, Xinglin Wang, Shaoxiong Feng, Boyuan Pan, Yiwei Li, Heda Wang, Xupeng Miao, Kan Li

Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024

SpotServe: Serving Generative Large Language Models on Preemptible Instances.

Xupeng Miao, Chunan Shi, Jiangfei Duan, Xiaoli Xi, Dahua Lin, Bin Cui, Zhihao Jia

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

SpecInfer: Accelerating Large Language Model Serving with Tree-based Speculative Inference and Verification.

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

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 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, Xupeng Miao, Jidong Zhai, Zhihao Jia

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

Quantized Side Tuning: Fast and Memory-Efficient Tuning of Quantized Large Language Models.

Zhengxin Zhang, Dan Zhao, Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, Qing Li, Yong Jiang, Zhihao Jia

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Accelerating Text-to-Image Editing via Cache-Enabled Sparse Diffusion Inference.

Zihao Yu, Haoyang Li, Fangcheng Fu, Xupeng Miao, Bin Cui

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Experimental Analysis of Large-scale Learnable Vector Storage Compression.

Hailin Zhang, Penghao Zhao, Xupeng Miao, Yingxia Shao, Zirui Liu, Tong Yang, Bin Cui

Proc. VLDB Endow., December, 2023

P²CG: a privacy preserving collaborative graph neural network training framework.

Xupeng Miao, Wentao Zhang, Yuezihan Jiang, Fangcheng Fu, Yingxia Shao, Lei Chen, Yangyu Tao, Gang Cao, Bin Cui

VLDB J., July, 2023

Hetu: a highly efficient automatic parallel distributed deep learning system.

Xupeng Miao, Xiaonan Nie, Hailin Zhang, Tong Zhao, Bin Cui

Sci. China Inf. Sci., January, 2023

Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-Aware Deep Architecture.

Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang

IEEE Trans. Knowl. Data Eng., 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

Proc. VLDB Endow., 2023

SDPipe: A Semi-Decentralized Framework for Heterogeneity-aware Pipeline-parallel Training.

Xupeng Miao, Yining Shi, Zhi Yang, Bin Cui, Zhihao Jia

Proc. VLDB Endow., 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

Proc. ACM Manag. Data, 2023

Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems.

Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, Xinhao Cheng, Hongyi Jin, Tianqi Chen, Zhihao Jia

CoRR, 2023

Improving Automatic Parallel Training via Balanced Memory Workload Optimization.

Yujie Wang, Youhe Jiang, Xupeng Miao, Fangcheng Fu, Xiaonan Nie, Bin Cui

CoRR, 2023

FISEdit: Accelerating Text-to-image Editing via Cache-enabled Sparse Diffusion Inference.

Zihao Yu, Haoyang Li, Fangcheng Fu, Xupeng Miao, Bin Cui

CoRR, 2023

SpecInfer: Accelerating Generative LLM Serving with Speculative Inference and Token Tree Verification.

Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, Xinhao Cheng, Zeyu Wang, Rae Ying Yee Wong, Zhuoming Chen, Daiyaan Arfeen, Reyna Abhyankar, Zhihao Jia

CoRR, 2023

EINNET: Optimizing Tensor Programs with Derivation-Based Transformations.

Liyan Zheng, Haojie Wang, Jidong Zhai, Muyan Hu, Zixuan Ma, Tuowei Wang, Shuhong Huang, Xupeng Miao, Shizhi Tang, Kezhao Huang, Zhihao Jia

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

Model-enhanced Vector Index.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning.

Youhe Jiang, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Bin Cui

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

CALIP: Zero-Shot Enhancement of CLIP with Parameter-Free Attention.

Ziyu Guo, Renrui Zhang, Longtian Qiu, Xianzheng Ma, Xupeng Miao, Xuming He, Bin Cui

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

CuWide: Towards Efficient Flow-Based Training for Sparse Wide Models on GPUs.

Xupeng Miao, Lingxiao Ma, Zhi Yang, Yingxia Shao, Bin Cui, Lele Yu, Jiawei Jiang

IEEE Trans. Knowl. Data Eng., 2022

Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism.

Xupeng Miao, Yujie Wang, Youhe Jiang, Chunan Shi, Xiaonan Nie, Hailin Zhang, Bin Cui

Proc. VLDB Endow., 2022

Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Update.

Fangcheng Fu, Xupeng Miao, Jiawei Jiang, Huanran Xue, Bin Cui

Proc. VLDB Endow., 2022

OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning.

Youhe Jiang, Xupeng Miao, Xiaonan Nie, Bin Cui

CoRR, 2022

Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates.

Fangcheng Fu, Xupeng Miao, Jiawei Jiang, Huanran Xue, Bin Cui

CoRR, 2022

HetuMoE: An Efficient Trillion-scale Mixture-of-Expert Distributed Training System.

Xiaonan Nie, Pinxue Zhao, Xupeng Miao, Tong Zhao, Bin Cui

CoRR, 2022

HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training.

Xupeng Miao, Yining Shi, Hailin Zhang, Xin Zhang, Xiaonan Nie, Zhi Yang, Bin Cui

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

TSPLIT: Fine-grained GPU Memory Management for Efficient DNN Training via Tensor Splitting.

Xiaonan Nie, Xupeng Miao, Zhi Yang, Bin Cui

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture (Extended Abstract).

Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Zoomer: Boosting Retrieval on Web-scale Graphs by Regions of Interest.

Yuezihan Jiang, Yu Cheng, Hanyu Zhao, Wentao Zhang, Xupeng Miao, Yu He, Liang Wang, Zhi Yang, Bin Cui

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

HET-KG: Communication-Efficient Knowledge Graph Embedding Training via Hotness-Aware Cache.

Sicong Dong, Xupeng Miao, Pengkai Liu, Xin Wang, Bin Cui, Jianxin Li

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

PointCLIP: Point Cloud Understanding by CLIP.

Renrui Zhang, Ziyu Guo, Wei Zhang, Kunchang Li, Xupeng Miao, Bin Cui, Yu Qiao, Peng Gao, Hongsheng Li

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Scalable Graph Sampling on GPUs with Compressed Graph.

Hongbo Yin, Yingxia Shao, Xupeng Miao, Yawen Li, Bin Cui

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Memory-aware framework for fast and scalable second-order random walk over billion-edge natural graphs.

Yingxia Shao, Shiyue Huang, Yawen Li, Xupeng Miao, Bin Cui, Lei Chen

VLDB J., 2021

HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework.

Xupeng Miao, Hailin Zhang, Yining Shi, Xiaonan Nie, Zhi Yang, Yangyu Tao, Bin Cui

Proc. VLDB Endow., 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, Bin Cui

CoRR, 2021

Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce.

Xupeng Miao, Xiaonan Nie, Yingxia Shao, Zhi Yang, Jiawei Jiang, Lingxiao Ma, Bin Cui

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

ROD: Reception-aware Online Distillation for Sparse Graphs.

Wentao Zhang, Yuezihan Jiang, Yang Li, Zeang Sheng, Yu Shen, Xupeng Miao, Liang Wang, Zhi Yang, Bin Cui

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

DeGNN: Improving Graph Neural Networks with Graph Decomposition.

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

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

CuWide: Towards Efficient Flow-based Training for Sparse Wide Models on GPUs (Extended Abstract).

Xupeng Miao, Lingxiao Ma, Zhi Yang, Yingxia Shao, Bin Cui, Lele Yu, Jiawei Jiang

Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

2020

Reliable Data Distillation on Graph Convolutional Network.

Wentao Zhang, Xupeng Miao, Yingxia Shao, Jiawei Jiang, Lei Chen, Olivier Ruas, Bin Cui

Proceedings of the 2020 International Conference on Management of Data, 2020

Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs.

Yingxia Shao, Shiyue Huang, Xupeng Miao, Bin Cui, Lei Chen

Proceedings of the 2020 International Conference on Management of Data, 2020

PSGraph: How Tencent trains extremely large-scale graphs with Spark?

Jiawei Jiang, Pin Xiao, Lele Yu, Xiaosen Li, Jiefeng Cheng, Xupeng Miao, Zhipeng Zhang, Bin Cui

Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

2019

PS2: Parameter Server on Spark.

Zhipeng Zhang, Bin Cui, Yingxia Shao, Lele Yu, Jiawei Jiang, Xupeng Miao

Proceedings of the 2019 International Conference on Management of Data, 2019