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2020 – today
- 2024
[j5]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): 3187-3196 (2024)- [j4]Jiaxing Qi
, Wencong Xiao, Mingzhen Li, Chaojie Yang, Yong Li, Wei Lin, Hailong Yang, Zhongzhi Luan, Depei Qian:
ElasticBatch: A Learning-Augmented Elastic Scheduling System for Batch Inference on MIG. IEEE Trans. Parallel Distributed Syst. 35(10): 1708-1720 (2024) - [c19]Biao Sun, Ziming Huang, Hanyu Zhao, Wencong Xiao, Xinyi Zhang, Yong Li, Wei Lin:
Llumnix: Dynamic Scheduling for Large Language Model Serving. OSDI 2024: 173-191 - [c18]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: 1-15 - [i10]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 abs/2401.02669 (2024) - [i9]Biao Sun, Ziming Huang, Hanyu Zhao, Wencong Xiao, Xinyi Zhang, Yong Li, Wei Lin:
Llumnix: Dynamic Scheduling for Large Language Model Serving. CoRR abs/2406.03243 (2024) - [i8]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 abs/2406.04594 (2024) - [i7]Xinyi Zhang, Hanyu Zhao, Wencong Xiao, Xianyan Jia, Fei Xu, Yong Li, Wei Lin, Fangming Liu:
Rubick: Exploiting Job Reconfigurability for Deep Learning Cluster Scheduling. CoRR abs/2408.08586 (2024) - 2023
- [j3]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): 193:1-193:25 (2023) - [c17]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: 55:1-55:14 - [i6]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 abs/2301.00407 (2023) - [i5]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 abs/2308.01006 (2023) - 2022
- [c16]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: 945-960 - [c15]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: 39:1-39:15 - [c14]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 ATC 2022: 673-688 - [i4]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 abs/2208.14228 (2022) - 2021
- [c13]Gangmuk Lim, Jeongseob Ahn, Wencong Xiao, Youngjin Kwon, Myeongjae Jeon:
Zico: Efficient GPU Memory Sharing for Concurrent DNN Training. USENIX ATC 2021: 161-175 - 2020
- [j2]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): 1588-1604 (2020) - [c12]Ru Zhang, Wencong Xiao, Hongyu Zhang, Yu Liu, Haoxiang Lin, Mao Yang:
An empirical study on program failures of deep learning jobs. ICSE 2020: 1159-1170 - [c11]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: 533-548 - [i3]Chen Xing, Wencong Xiao, Yong Li, Wei Lin:
Focusing More on Conflicts with Mis-Predictions Helps Language Pre-Training. CoRR abs/2012.08789 (2020)
2010 – 2019
- 2019
- [j1]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): 1014-1027 (2019) - [c10]Zhuliang Yao, Shijie Cao, Wencong Xiao, Chen Zhang, Lanshun Nie:
Balanced Sparsity for Efficient DNN Inference on GPU. AAAI 2019: 5676-5683 - [c9]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: 11216-11225 - [c8]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: 63-72 - [c7]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 ATC 2019: 947-960 - [i2]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 abs/1901.05758 (2019) - 2018
- [c6]Wencong Xiao, Zhenhua Han, Hanyu Zhao, Xuan Peng, Quanlu Zhang, Fan Yang, Lidong Zhou:
Scheduling CPU for GPU-based Deep Learning Jobs. SoCC 2018: 503 - [c5]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: 595-610 - [i1]Zhuliang Yao, Shijie Cao, Wencong Xiao, Chen Zhang, Lanshun Nie:
Balanced Sparsity for Efficient DNN Inference on GPU. CoRR abs/1811.00206 (2018) - 2017
- [c4]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: 22-28 - [c3]Wencong Xiao, Jilong Xue, Youshan Miao, Zhen Li, Cheng Chen, Ming Wu, Wei Li, Lidong Zhou:
Tux2: Distributed Graph Computation for Machine Learning. NSDI 2017: 669-682 - [c2]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: 137-152 - 2015
- [c1]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: 408-421
Coauthor Index
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