Wencong Xiao

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 31

Top Topics

Convolutional Neural Network

Top Venues

USENIX Annual Technical Conference

Publications

Jianbo Dong, Bin Luo, Jun Zhang, Pengcheng Zhang, Fei Feng, Yikai Zhu, Ang Liu, Zian Chen, Yi Shi, Hairong Jiao, Gang Lu, Yu Guan, Ennan Zhai, Wencong Xiao, Hanyu Zhao, Man Yuan, Siran Yang, Xiang Li, Jiamang Wang, Rui Men, Jianwei Zhang, Huang Zhong, Dennis Cai, Yuan Xie, Binzhang Fu
Boosting Large-scale Parallel Training Efficiency with C4: A Communication-Driven Approach. CoRR (2024)
Biao Sun, Ziming Huang, Hanyu Zhao, Wencong Xiao, Xinyi Zhang, Yong Li, Wei Lin
Llumnix: Dynamic Scheduling for Large Language Model Serving. OSDI (2024)
Jiamin Cao, Yu Guan, Kun Qian, Jiaqi Gao, Wencong Xiao, Jianbo Dong, Binzhang Fu, Dennis Cai, Ennan Zhai
Crux: GPU-Efficient Communication Scheduling for Deep Learning Training. SIGCOMM (2024)
Biao Sun, Ziming Huang, Hanyu Zhao, Wencong Xiao, Xinyi Zhang, Yong Li, Wei Lin
Llumnix: Dynamic Scheduling for Large Language Model Serving. CoRR (2024)
Bin Lin, Tao Peng, Chen Zhang, Minmin Sun, Lanbo Li, Hanyu Zhao, Wencong Xiao, Qi Xu, Xiafei Qiu, Shen Li, Zhigang Ji, Yong Li, Wei Lin
Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache. CoRR (2024)
Huazhi Xu, Xiaoyan Luo, Wencong Xiao
Multi-residual unit fusion and Wasserstein distance-based deep transfer learning for mill load recognition. Signal Image Video Process. 18 (4) (2024)
Hanyu Zhao, Zhi Yang, Yu Cheng, Chao Tian, Shiru Ren, Wencong Xiao, Man Yuan, Langshi Chen, Kaibo Liu, Yang Zhang, Yong Li, Wei Lin
GoldMiner: Elastic Scaling of Training Data Pre-Processing Pipelines for Deep Learning. Proc. ACM Manag. Data 1 (2) (2023)
Huaizheng Zhang, Yuanming Li, Wencong Xiao, Yizheng Huang, Xing Di, Jianxiong Yin, Simon See, Yong Luo, Chiew Tong Lau, Yang You
MIGPerf: A Comprehensive Benchmark for Deep Learning Training and Inference Workloads on Multi-Instance GPUs. CoRR (2023)
Mingzhen Li, Wencong Xiao, Hailong Yang, Biao Sun, Hanyu Zhao, Shiru Ren, Zhongzhi Luan, Xianyan Jia, Yi Liu, Yong Li, Wei Lin, Depei Qian
EasyScale: Elastic Training with Consistent Accuracy and Improved Utilization on GPUs. SC (2023)
Tengju Ye, Wei Jing, Chunyong Hu, Shikun Huang, Lingping Gao, Fangzhen Li, Jingke Wang, Ke Guo, Wencong Xiao, Weibo Mao, Hang Zheng, Kun Li, Junbo Chen, Kaicheng Yu
FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Driving. CoRR (2023)
Qingxiao Sun, Yi Liu, Hailong Yang, Ruizhe Zhang, Ming Dun, Mingzhen Li, Xiaoyan Liu, Wencong Xiao, Yong Li, Zhongzhi Luan, Depei Qian
CoGNN: Efficient Scheduling for Concurrent GNN Training on GPUs. SC (2022)
Xianyan Jia, Le Jiang, Ang Wang, Wencong Xiao, Ziji Shi, Jie Zhang, Xinyuan Li, Langshi Chen, Yong Li, Zhen Zheng, Xiaoyong Liu, Wei Lin
Whale: Efficient Giant Model Training over Heterogeneous GPUs. USENIX Annual Technical Conference (2022)
Qizhen Weng, Wencong Xiao, Yinghao Yu, Wei Wang, Cheng Wang, Jian He, Yong Li, Liping Zhang, Wei Lin, Yu Ding
MLaaS in the Wild: Workload Analysis and Scheduling in Large-Scale Heterogeneous GPU Clusters. NSDI (2022)
Mingzhen Li, Wencong Xiao, Biao Sun, Hanyu Zhao, Hailong Yang, Shiru Ren, Zhongzhi Luan, Xianyan Jia, Yi Liu, Yong Li, Depei Qian, Wei Lin
EasyScale: Accuracy-consistent Elastic Training for Deep Learning. CoRR (2022)
Gangmuk Lim, Jeongseob Ahn, Wencong Xiao, Youngjin Kwon, Myeongjae Jeon
Zico: Efficient GPU Memory Sharing for Concurrent DNN Training. USENIX Annual Technical Conference (2021)
Chen Xing, Wencong Xiao, Yong Li, Wei Lin
Focusing More on Conflicts with Mis-Predictions Helps Language Pre-Training. CoRR (2020)
Wencong Xiao, Shiru Ren, Yong Li, Yang Zhang, Pengyang Hou, Zhi Li, Yihui Feng, Wei Lin, Yangqing Jia
AntMan: Dynamic Scaling on GPU Clusters for Deep Learning. OSDI (2020)
Wencong Xiao, Jilong Xue, Youshan Miao, Zhen Li, Cheng Chen, Ming Wu, Wei Li, Lidong Zhou
Distributed Graph Computation Meets Machine Learning. IEEE Trans. Parallel Distributed Syst. 31 (7) (2020)
Ru Zhang, Wencong Xiao, Hongyu Zhang, Yu Liu, Haoxiang Lin, Mao Yang
An empirical study on program failures of deep learning jobs. ICSE (2020)
Zhuliang Yao, Shijie Cao, Wencong Xiao, Chen Zhang, Lanshun Nie
Balanced Sparsity for Efficient DNN Inference on GPU. AAAI (2019)
Myeongjae Jeon, Shivaram Venkataraman, Amar Phanishayee, Junjie Qian, Wencong Xiao, Fan Yang
Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads. CoRR (2019)
Myeongjae Jeon, Shivaram Venkataraman, Amar Phanishayee, Junjie Qian, Wencong Xiao, Fan Yang
Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads. USENIX Annual Technical Conference (2019)
Shijie Cao, Lingxiao Ma, Wencong Xiao, Chen Zhang, Yunxin Liu, Lintao Zhang, Lanshun Nie, Zhi Yang
SeerNet: Predicting Convolutional Neural Network Feature-Map Sparsity Through Low-Bit Quantization. CVPR (2019)
Meng Meng, Wencong Xiao, Tong He, Yuechen Tao, Kun Tan, Jiansong Zhang, Wenjie Wang
BeamRaster: A Practical Fast Massive MU-MIMO System With Pre-Computed Precoders. IEEE Trans. Mob. Comput. 18 (5) (2019)
Shijie Cao, Chen Zhang, Zhuliang Yao, Wencong Xiao, Lanshun Nie, De-chen Zhan, Yunxin Liu, Ming Wu, Lintao Zhang
Efficient and Effective Sparse LSTM on FPGA with Bank-Balanced Sparsity. FPGA (2019)
Wencong Xiao, Zhenhua Han, Hanyu Zhao, Xuan Peng, Quanlu Zhang, Fan Yang, Lidong Zhou
Scheduling CPU for GPU-based Deep Learning Jobs. SoCC (2018)
Wencong Xiao, Romil Bhardwaj, Ramachandran Ramjee, Muthian Sivathanu, Nipun Kwatra, Zhenhua Han, Pratyush Patel, Xuan Peng, Hanyu Zhao, Quanlu Zhang, Fan Yang, Lidong Zhou
Gandiva: Introspective Cluster Scheduling for Deep Learning. OSDI (2018)
Zhuliang Yao, Shijie Cao, Wencong Xiao, Chen Zhang, Lanshun Nie
Balanced Sparsity for Efficient DNN Inference on GPU. CoRR (2018)
Bojie Li, Zhenyuan Ruan, Wencong Xiao, Yuanwei Lu, Yongqiang Xiong, Andrew Putnam, Enhong Chen, Lintao Zhang
KV-Direct: High-Performance In-Memory Key-Value Store with Programmable NIC. SOSP (2017)
Wencong Xiao, Jilong Xue, Youshan Miao, Zhen Li, Cheng Chen, Ming Wu, Wei Li, Lidong Zhou
: Distributed Graph Computation for Machine Learning. NSDI (2017)
Yuanwei Lu, Guo Chen, Zhenyuan Ruan, Wencong Xiao, Bojie Li, Jiansong Zhang, Yongqiang Xiong, Peng Cheng, Enhong Chen
Memory Efficient Loss Recovery for Hardware-based Transport in Datacenter. APNet (2017)
Ming Wu, Fan Yang, Jilong Xue, Wencong Xiao, Youshan Miao, Lan Wei, Haoxiang Lin, Yafei Dai, Lidong Zhou
GraM: scaling graph computation to the trillions. SoCC (2015)