卢宇彤

教授

联系邮箱： luyutong@mail.sysu.edu.cn

教师简介: 

卢宇彤，女，博士，二级教授，博导，现任中山大学计算机学院教授、国家超级计算广州/深圳中心主任、教育部超算工程软件研究中心主任、国际超算ISC Fellow和CCF Fellow、国家高层次人才、全国三八红旗手标兵，曾任世界“六连冠”天河超算系统副总设计师、现任世界超算TOP500性能第一的国产新一代E级超算系统“灵晟”总设计师。

卢教授长期从事高性能计算系统（HPC）研究与工程实现，参加了多台超算系统的研制工作。面向高性能计算系统结构、并行运行支撑系统、大规模存储、HPC+AI超智融合系统及HPC+AI For科学工程计算应用等方面取得了一系列重要的技术创新与突破。多次在国际顶级超算会议SC、ISC、IPDPS上做大会主旨报告，国际超算大会ISC2019、亚洲超算大会HPCAsia2019的大会主席，以及多个重要国际会议的TPC。

卢教授获得国家科技进步特等奖1项、一等奖1项，省部级科技进步特等和一等奖6项。在发表论文200余篇，授权专利60多项。承担国家重点研发计划、国家自然科学基金重点项目等多个重要项目。

研究领域: 

超智融合高性能计算系统、并行系统软件，面向领域的HPC+AI超算应用支撑平台、大模型存储技术、超智量协同计算技术。

代表性论文: 

  • [CCF-A, HPCA 2026] Fuyu Wang, Minghua Shen, Yufei Ding, Nong Xiao, and Yutong Lu, “SFD: Towards Segment Fusion Dataflow for Spatial Accelerators”. 
  • [CCF-A, PPoPP 2026] Jiazhi Jiang, Xijia Yao, Jiayu Chen, Jinhui Wei, Dan Huang, and Yutong Lu, “ASM-SpMM: Unleashing the Potential of Arm SME for Sparse Matrix Multiplication Acceleration”. 
  • [CCF-A, TPDS 2026] Jiazhi Jiang, Yao Chen, Zining Zhang, Bingsheng He, Pingyi Luo, Mian Lu, Yuqiang Chen, Hongbin Zhang, Jiangsu Du, Dan Huang, and Yutong Lu, “Efficient KV Cache Spillover Management on Memory-Constrained GPU for LLM Inference”. 
  • [CCF-A, OSDI 2026] Jiangsu Du, Hongbin Zhang, Taosheng Wei, Zhenyi Zheng, Jiazhi Jiang, Kaiyi Wu, Zhiguang Chen, and Yutong Lu, “Efficient LLM Serving on Commodity GPU Clusters with Data-Reduced Cross-Instance Orchestration”. 
  • [CCF-A, EuroSys 2026] Yizhuo Rao, Xingjian Cui, Jiabin Xie, Shangzhi Pang, Guangnan Feng, Jinhui Wei, Zhiguang Chen, and Yutong Lu, “Matrix-PIC: Harnessing Matrix Outer-product for High-Performance Particle-in-Cell Simulations”. 
  • [CCF-A, ASPLOS 2026] Zejia Lin, Hongxin Xu, Guanyi Chen, Zhiguang Chen, Yutong Lu, and Xianwei Zhang, “Bullet: Boosting GPU Utilization for LLM Serving via Dynamic Spatial-Temporal Orchestration”. 
  • [CCF-A, TACO 2026] Jinhui Wei, Shenggan Cheng, Wei Zhu, Jiazhi Jiang, Dan Huang, Zhiguang Chen, Jiangsu Du, and Yutong Lu, “Dynamic Latency-Throughput Balancing in Distributed Large Model Inference with Interleaved Parallelism”. 
  • [CCF-A, TACO 2026] Shaoyin Huang, Ziyan Zhang, Jiazhi Jiang, Yang Liu, Yutong Lu, and Zhiguang Chen, “OR-LSM: Optimizing Read Performance for LSM-KVS via Adaptive Caching Management and Scan Mode Selection”. 
  • [CCF-A, SIGMOD 2026] Fengyao Bai, Hongbin Zhang, Zhitao Chen, Jiangsu Du, Zhiguang Chen, and Yutong Lu, “AlignedServe: Orchestrating Prefix-aware Batching to Build a High-throughput and Computing-efficient LLM Serving System”. 
  • [CCF-A, ACL 2026] Yujia Fu, Heming Zhong, Dan Huang, and Yutong Lu, “FLARE: Fine-Grained Length-Aware Routing for Resource-Efficient Heterogeneous LLM Serving”. 
  • [CCF-A, AAAI 2026] Xiean Wang, Pin Chen, Liqin Tan, Yutong Lu, and Qingsong Zou, “FUSION: Dataset Pruning via Fusing Uncertainty with Structural Information for Optimal Neural Training in Crystal Property Prediction”. 
  • [CCF-A, KDD 2026] Yuewen Huang, Pin Chen, and Yutong Lu, “UniHam: A Large-Scale SOC-Complete Dataset and Benchmark for Hamiltonian Learning in Materials”. 
  • [CCF-A, TPDS 2025] Jiangsu Du, Yuanxin Wei, Shengyuan Ye, Jiazhi Jiang, Xu Chen, Dan Huang, and Yutong Lu, “Co-Designing Transformer Architectures for Distributed Inference With Low Communication”. 
  • [CCF-A, SC 2025] Yuhao Gu, Haoquan Chen, Xianjie Chen, Jiangsu Du, Zhiguang Chen, Nong Xiao, Xianwei Zhang, and Yutong Lu, “coMtainer: Compilation-assisted HPC Container Images with Enhanced Adaptability”. 
  • [CCF-A, SC 2025] Tianyu Guo, Xianwei Zhang, Jiangsu Du, Zhiguang Chen, Nong Xiao, and Yutong Lu, “gLLM: Global Balanced Pipeline Parallelism Systems for Distributed LLMs Serving with Token Throttling”. 
  • [CCF-A, SC 2025] Han Huang, Jiabin Xie, Guangnan Feng, Xianwei Zhang, Dan Huang, Zhiguang Chen, and Yutong Lu, “HStencil: Matrix-Vector Stencil Computation with Interleaved Outer Product and MLA”. 
  • [CCF-A, TACO 2025] Fuyu Wang, Minghua Shen, Yutong Lu, and Nong Xiao, “Ceiba: An Efficient and Scalable DNN Scheduler for Spatial Accelerators”. 
  • [CCF-A, ICCV 2025] Xinzi Cao, Ke Chen, Feidiao Yang, Xiawu Zheng, Yonghong Tian, and Yutong Lu, “AllGCD: Leveraging All Unlabeled Data for Generalized Category Discovery”. 
  • [CCF-A, IJCAI 2025] Menghan Liu, Jianhuan Cen, Ziyang Zhou, Haolong Fan, Hongji Li, Ping Wei, Guohang Peng, Changye He, Yuzhe Qin, Yutong Lu, and Qingsong Zou, “CFDONEval: A Comprehensive Evaluation of Operator-Learning Neural Network Models for Computational Fluid Dynamics”. 
  • [CCF-A, TMC 2025] Shengyuan Ye, Bei Ouyang, Jiangsu Du, Liekang Zeng, Tianyi Qian, Wenzhong Ou, Xiaowen Chu, Deke Guo, Yutong Lu, and Xu Chen, “Resource-Efficient Collaborative Edge Transformer Inference With Hybrid Model Parallelism”. 
  • [CCF-A, TOS 2025] Yubo Liu, Yongfeng Wang, Zhiguang Chen, Yutong Lu, and Ming Zhao, “WALSH: Write-Aggregating Log-Structured Hashing for Hybrid Memory”. 
  • [CCF-A, PPoPP 2024] Jiabin Xie, Guangnan Feng, Han Huang, Junxuan Feng, Zhiguang Chen, and Yutong Lu, “Extreme-scale Direct Numerical Simulation of Incompressible Turbulence on the Heterogeneous Many-core System”. 
  • [CCF-A, PPoPP 2024] Jiangsu Du, Jinhui Wei, Jiazhi Jiang, Shenggan Cheng, Dan Huang, Zhiguang Chen, and Yutong Lu, “Liger: Interleaving Intra- and Inter-Operator Parallelism for Distributed Large Model Inference”. 
  • [CCF-A, TPDS 2024] Rui Tian, Jiazhi Jiang, Jiangsu Du, Dan Huang, and Yutong Lu, “Sophisticated Orchestrating Concurrent DLRM Training on CPU/GPU Platform”. 
  • [CCF-A, SC 2024] Yuanxin Wei, Jiangsu Du, Jiazhi Jiang, Xiao Shi, Xianwei Zhang, Dan Huang, Nong Xiao, and Yutong Lu, “APTMoE: Affinity-Aware Pipeline Tuning for MoE Models on Bandwidth-Constrained GPU Nodes”. 
  • [CCF-A, CVPR 2024] Xinzi Cao, Xiawu Zheng, Guanhong Wang, Weijiang Yu, Yunhang Shen, Ke Li, Yutong Lu, and Yonghong Tian, “Solving the Catastrophic Forgetting Problem in Generalized Category Discovery”. 
  • [CCF-A, ICML 2024] Peijia Lin, Pin Chen, Rui Jiao, Qing Mo, Jianhuan Cen, Wenbing Huang, Yang Liu, Dan Huang, and Yutong Lu, “Equivariant Diffusion for Crystal Structure Prediction”. 
  • [CCF-A, INFOCOM 2024] Shengyuan Ye, Jiangsu Du, Liekang Zeng, Wenzhong Ou, Xiaowen Chu, Yutong Lu, and Xu Chen, “Galaxy: A Resource-Efficient Collaborative Edge AI System for In-situ Transformer Inference”. 
  • [CCF-A, SCIS 2024] Jiazhi Jiang, Dan Huang, Hu Chen, Yutong Lu, and Xiangke Liao, “HTDcr: a job execution framework for high-throughput computing on supercomputers”. 
  • [CCF-A, TC 2024] Fuyu Wang, Minghua Shen, Yutong Lu, and Nong Xiao, “TensorMap: A Deep RL-Based Tensor Mapping Framework for Spatial Accelerators”. 
  • [CCF-A, TPDS 2023] Jiazhi Jiang, Jiangsu Du, Dan Huang, Zhiguang Chen, Yutong Lu, and Xiangke Liao, “Full-Stack Optimizing Transformer Inference on ARM Many-Core CPU”. 
  • [CCF-A, TACO 2023] Jiazhi Jiang, Zijian Huang, Dan Huang, Jiangsu Du, Lin Chen, Ziguan Chen, and Yutong Lu, “Hierarchical Model Parallelism for Optimizing Inference on Many-core Processor via Decoupled 3D-CNN Structure”. 
  • [CCF-A, TACO 2023] Jiangsu Du, Jiazhi Jiang, Jiang Zheng, Hongbin Zhang, Dan Huang, and Yutong Lu, “Improving Computation and Memory Efficiency for Real-world Transformer Inference on GPUs”. 
  • [CCF-A, NeurIPS 2023] Rui Jiao, Wenbing Huang, Peijia Lin, Jiaqi Han, Pin Chen, Yutong Lu, and Yang Liu, “Crystal Structure Prediction by Joint Equivariant Diffusion”. 
  • [CCF-A, MM 2023] Xinzi Cao, Xiawu Zheng, Yunhang Shen, Ke Li, Jie Chen, Yutong Lu, and Yonghong Tian, “LocLoc: Low-level Cues and Local-area Guides for Weakly Supervised Object Localization”. 
  • [CCF-A, TPAMI 2023] Gaojie Wu, Wei-Shi Zheng, Yutong Lu, and Qi Tian, “PSLT: A Light-weight Vision Transformer with Ladder Self-Attention and Progressive Shift”. 
  • [CCF-A, TOSEM 2023] Zibin Zheng, Weili Chen, Zhijie Zhong, Zhiguang Chen, and Yutong Lu, “Securing the Ethereum from Smart Ponzi Schemes: Identification Using Static Features”. 
  • [CCF-A, TPDS 2022] Yinjin Fu, Yutong Lu, Zhiguang Chen, Yang Wu, and Nong Xiao, “Design and Simulation of Content-Aware Hybrid DRAM-PCM Memory System”. 
  • [CCF-A, DAC 2022] Jinxi Kuang, Minghua Shen, Yutong Lu, and Nong Xiao, “Exploiting Data Locality in Memory for ORAM to Reduce Memory Access Overheads”. 
  • [CCF-A, MM 2022] Yupan Huang, Tengchao Lv, Lei Cui, Yutong Lu, and Furu Wei, “LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking”. 
  • [CCF-A, TPDS 2021] Xia Liao, Shengguo Li, Yutong Lu, and Jose E. Roman, “A Parallel Structured Divide-and-Conquer Algorithm for Symmetric Tridiagonal Eigenvalue Problems”. 
  • [CCF-A, TPDS 2021] Jiangsu Du, Xin Zhu, Minghua Shen, Yunfei Du, Yutong Lu, Nong Xiao, and Xiangke Liao, “Model Parallelism Optimization for Distributed Inference Via Decoupled CNN Structure”. 
  • [CCF-A, SC 2021] Hongzheng Chen, Minghua Shen, Nong Xiao, and Yutong Lu, “Krill: A Compiler and Runtime System for Concurrent Graph Processing”. 
  • [CCF-A, TSC 2021] Yatao Yang, Zibin Zheng, Xiangdong Niu, Mingdong Tang, Yutong Lu, and Xiangke Liao, “A Location-Based Factorization Machine Model for Web Service QoS Prediction”. 
  • [CCF-A, AAAI 2021] Fengyang Xu, Guanbin Li, Yunfei Du, Zhiguang Chen, and Yutong Lu, “Multi-Layer Networks for Ensemble Precipitation Forecasts Postprocessing”. 
  • [CCF-A, ICCV 2021] Yi Zhu, Yue Weng, Fengda Zhu, Xiaodan Liang, Qixiang Ye, Yutong Lu, and Jianbin Jiao, “Self-Motivated Communication Agent for Real-World Vision-Dialog Navigation”. 
  • [CCF-A, MM 2021] Yupan Huang, Hongwei Xue, Bei Liu, and Yutong Lu, “Unifying Multimodal Transformer for Bi-directional Image and Text Generation”. 
  • [CCF-A, TPDS 2020] Tao Gao, Yanfei Guo, Boyu Zhang, Pietro Cicotti, Yutong Lu, Pavan Balaji, and Michela Taufer, “Memory-Efficient and Skew-Tolerant MapReduce Over MPI for Supercomputing Systems”. 
  • [CCF-A, IJCAI 2020] Ying Song, Shuangjia Zheng, Zhangming Niu, Zhang-hua Fu, Yutong Lu, and Yuedong Yang, “Communicative Representation Learning on Attributed Molecular Graphs”. 
  • [CCF-A, IJCAI 2020] Weili Chen, Xiongfeng Guo, Zhiguang Chen, Zibin Zheng, and Yutong Lu, “Phishing Scam Detection on Ethereum: Towards Financial Security for Blockchain Ecosystem”. 
  • [CCF-A, WWW 2020] Weili Chen, Tuo Zhang, Zhiguang Chen, Zibin Zheng, and Yutong Lu, “Traveling the token world: A graph analysis of Ethereum ERC20 token ecosystem”.