GraM: scaling graph computation to the trillions. - Ming Wu 007; Fan Yang 024; Jilong Xue; Wencong Xiao; Youshan Miao; Lan Wei; Haoxiang Lin; Yafei Dai; Lidong Zhou (SoCC, 2015)

Memory Efficient Loss Recovery for Hardware-based Transport in Datacenter. - Yuanwei Lu; Guo Chen 001; Zhenyuan Ruan; Wencong Xiao; Bojie Li; Jiansong Zhang 001; Yongqiang Xiong; Peng Cheng 005; Enhong Chen (APNet, 2017)

Tux2: Distributed Graph Computation for Machine Learning. - Wencong Xiao; Jilong Xue; Youshan Miao; Zhen Li; Cheng Chen; Ming Wu 007; Wei Li 022; Lidong Zhou (NSDI, 2017)

KV-Direct: High-Performance In-Memory Key-Value Store with Programmable NIC. - Bojie Li; Zhenyuan Ruan; Wencong Xiao; Yuanwei Lu; Yongqiang Xiong; Andrew Putnam; Enhong Chen; Lintao Zhang (SOSP, 2017)

Scheduling CPU for GPU-based Deep Learning Jobs. - Wencong Xiao; Zhenhua Han; Hanyu Zhao; Xuan Peng; Quanlu Zhang; Fan Yang 024; Lidong Zhou (SoCC, 2018)

Gandiva: Introspective Cluster Scheduling for Deep Learning. - Wencong Xiao; Romil Bhardwaj; Ramachandran Ramjee; Muthian Sivathanu; Nipun Kwatra; Zhenhua Han; Pratyush Patel; Xuan Peng; Hanyu Zhao; Quanlu Zhang; Fan Yang 024; Lidong Zhou (OSDI, 2018)

Balanced Sparsity for Efficient DNN Inference on GPU. - Zhuliang Yao; Shijie Cao; Wencong Xiao; Chen Zhang 001; Lanshun Nie (AAAI, 2019)

SeerNet: Predicting Convolutional Neural Network Feature-Map Sparsity Through Low-Bit Quantization. - Shijie Cao; Lingxiao Ma; Wencong Xiao; Chen Zhang 001; Yunxin Liu 001; Lintao Zhang; Lanshun Nie; Zhi Yang 001 (CVPR, 2019)

Efficient and Effective Sparse LSTM on FPGA with Bank-Balanced Sparsity. - Shijie Cao; Chen Zhang 001; Zhuliang Yao; Wencong Xiao; Lanshun Nie; De-chen Zhan; Yunxin Liu 001; Ming Wu 007; Lintao Zhang (FPGA, 2019)

Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads. - Myeongjae Jeon; Shivaram Venkataraman; Amar Phanishayee; Junjie Qian; Wencong Xiao; Fan Yang 024 (USENIX ATC, 2019)

BeamRaster: A Practical Fast Massive MU-MIMO System With Pre-Computed Precoders. - Meng Meng; Wencong Xiao; Tong He; Yuechen Tao; Kun Tan; Jiansong Zhang 001; Wenjie Wang 001 (IEEE Trans. Mob. Comput., 2019)

An empirical study on program failures of deep learning jobs. - Ru Zhang; Wencong Xiao; Hongyu Zhang 002; Yu Liu; Haoxiang Lin; Mao Yang 004 (ICSE, 2020)

AntMan: Dynamic Scaling on GPU Clusters for Deep Learning. - Wencong Xiao; Shiru Ren; Yong Li 020; Yang Zhang; Pengyang Hou; Zhi Li; Yihui Feng; Wei Lin 016; Yangqing Jia (OSDI, 2020)

Focusing More on Conflicts with Mis-Predictions Helps Language Pre-Training. - Chen Xing; Wencong Xiao; Yong Li 020; Wei Lin 016 (CoRR, 2020)

Distributed Graph Computation Meets Machine Learning. - Wencong Xiao; Jilong Xue; Youshan Miao; Zhen Li; Cheng Chen; Ming Wu 007; Wei Li 022; Lidong Zhou (IEEE Trans. Parallel Distributed Syst., 2020)

Zico: Efficient GPU Memory Sharing for Concurrent DNN Training. - Gangmuk Lim; Jeongseob Ahn; Wencong Xiao; Youngjin Kwon; Myeongjae Jeon (USENIX ATC, 2021)

MLaaS in the Wild: Workload Analysis and Scheduling in Large-Scale Heterogeneous GPU Clusters. - Qizhen Weng; Wencong Xiao; Yinghao Yu; Wei Wang 030; Cheng Wang; Jian He; Yong Li 020; Liping Zhang; Wei Lin 016; Yu Ding (NSDI, 2022)

CoGNN: Efficient Scheduling for Concurrent GNN Training on GPUs. - Qingxiao Sun; Yi Liu 013; Hailong Yang 002; Ruizhe Zhang 012; Ming Dun; Mingzhen Li 001; Xiaoyan Liu; Wencong Xiao; Yong Li 020; Zhongzhi Luan; Depei Qian (SC, 2022)

Whale: Efficient Giant Model Training over Heterogeneous GPUs. - Xianyan Jia; Le Jiang; Ang Wang; Wencong Xiao; Ziji Shi; Jie Zhang 078; Xinyuan Li; Langshi Chen; Yong Li 020; Zhen Zheng; Xiaoyong Liu; Wei Lin 016 (USENIX ATC, 2022)

EasyScale: Accuracy-consistent Elastic Training for Deep Learning. - Mingzhen Li 001; Wencong Xiao; Biao Sun; Hanyu Zhao; Hailong Yang 002; Shiru Ren; Zhongzhi Luan; Xianyan Jia; Yi Liu 013; Yong Li 020; Depei Qian; Wei Lin 016 (CoRR, 2022)

EasyScale: Elastic Training with Consistent Accuracy and Improved Utilization on GPUs. - Mingzhen Li 001; Wencong Xiao; Hailong Yang 002; Biao Sun; Hanyu Zhao; Shiru Ren; Zhongzhi Luan; Xianyan Jia; Yi Liu 013; Yong Li 020; Wei Lin 016; Depei Qian (SC, 2023)

MIGPerf: A Comprehensive Benchmark for Deep Learning Training and Inference Workloads on Multi-Instance GPUs. - Huaizheng Zhang; Yuanming Li; Wencong Xiao; Yizheng Huang 001; Xing Di; Jianxiong Yin; Simon See; Yong Luo 002; Chiew Tong Lau; Yang You (CoRR, 2023)

FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Driving. - Tengju Ye; Wei Jing; Chunyong Hu; Shikun Huang; Lingping Gao; Fangzhen Li; Jingke Wang; Ke Guo; Wencong Xiao; Weibo Mao; Hang Zheng; Kun Li; et al. (CoRR, 2023)

GoldMiner: Elastic Scaling of Training Data Pre-Processing Pipelines for Deep Learning. - Hanyu Zhao; Zhi Yang 001; Yu Cheng; Chao Tian 001; Shiru Ren; Wencong Xiao; Man Yuan; Langshi Chen; Kaibo Liu; Yang Zhang; Yong Li 020; Wei Lin 016 (Proc. ACM Manag. Data, 2023)

Llumnix: Dynamic Scheduling for Large Language Model Serving. - Biao Sun; Ziming Huang; Hanyu Zhao; Wencong Xiao; Xinyi Zhang; Yong Li 020; Wei Lin 016 (OSDI, 2024)

Crux: GPU-Efficient Communication Scheduling for Deep Learning Training. - Jiamin Cao; Yu Guan; Kun Qian; Jiaqi Gao; Wencong Xiao; Jianbo Dong; Binzhang Fu; Dennis Cai; Ennan Zhai (SIGCOMM, 2024)

Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache. - Bin Lin; Tao Peng; Chen Zhang; Minmin Sun; Lanbo Li; Hanyu Zhao; Wencong Xiao; Qi Xu; Xiafei Qiu; Shen Li; Zhigang Ji; Yong Li 020; et al. (CoRR, 2024)

Boosting Large-scale Parallel Training Efficiency with C4: A Communication-Driven Approach. - Jianbo Dong; Bin Luo; Jun Zhang; Pengcheng Zhang; Fei Feng; Yikai Zhu; Ang Liu; Zian Chen; Yi Shi; Hairong Jiao; Gang Lu; Yu Guan; et al. (CoRR, 2024)

Rubick: Exploiting Job Reconfigurability for Deep Learning Cluster Scheduling. - Xinyi Zhang; Hanyu Zhao; Wencong Xiao; Xianyan Jia; Fei Xu; Yong Li 020; Wei Lin 016; Fangming Liu (CoRR, 2024)

ElasticBatch: A Learning-Augmented Elastic Scheduling System for Batch Inference on MIG. - Jiaxing Qi; Wencong Xiao; Mingzhen Li 001; Chaojie Yang; Yong Li 020; Wei Lin 016; Hailong Yang 002; Zhongzhi Luan; Depei Qian (IEEE Trans. Parallel Distributed Syst., 2024)

Multi-residual unit fusion and Wasserstein distance-based deep transfer learning for mill load recognition. - Huazhi Xu; Xiaoyan Luo; Wencong Xiao (Signal Image Video Process., 2024)

Enhancing Large-Scale AI Training Efficiency: The C4 Solution for Real-Time Anomaly Detection and Communication Optimization. - Jianbo Dong; Bin Luo; Jun Zhang; Pengcheng Zhang; Fei Feng; Yikai Zhu; Ang Liu; Zian Chen; Yi Shi; Hairong Jiao; Gang Lu; Yu Guan; et al. (HPCA, 2025)

Subdivision load identification of ball mill based on multi-domain feature extraction and UMAP-BOXGBoost. - Gaipin Cai; Wencong Xiao; Huazhi Xu; Junliang Wan (Signal Image Video Process., 2025)

BootSeer: Analyzing and Mitigating Initialization Bottlenecks in Large-Scale LLM Training. - Rui Li; Xiaoyun Zhi; Jinxin Chi; Menghan Yu; Lixin Huang; Jia Zhu; Weilun Zhang; Xing Ma; Wenjia Liu; Zhicheng Zhu; Daowen Luo; Zuquan Song; et al. (CoRR, 2025)

Fine-Grained Structured Sparse Computing for FPGA-Based AI Inference. - Chen Zhang 001; Shijie Cao; Guohao Dai; Chenbo Geng; Zhuliang Yao; Wencong Xiao; Yunxin Liu 001; Ming Wu 007; Lintao Zhang; Guangyu Sun 003; Zhigang Ji; Runsheng Wang; et al. (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)