Yong Li

According to our database, Yong Li authored at least 34 papers between 2018 and 2025.

Collaborative distances:

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

2025

Efficient Long Context Fine-tuning with Chunk Flow.

Xiulong Yuan, Hongtao Xu, Wenting Shen, Ang Wang, Xiafei Qiu, Jie Zhang, Yuqiong Liu, Bowen Yu, Junyang Lin, Mingzhen Li, Weile Jia, Yong Li, Wei Lin

CoRR, March, 2025

Qwen2.5-1M Technical Report.

An Yang, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoyan Huang, Jiandong Jiang, Jianhong Tu, Jianwei Zhang, Jingren Zhou, Junyang Lin, Kai Dang, Kexin Yang, Le Yu, Mei Li, Minmin Sun, Qin Zhu, Rui Men, Tao He, Weijia Xu, Wenbiao Yin, Wenyuan Yu, Xiafei Qiu, Xingzhang Ren, Xinlong Yang, Yong Li, Zhiying Xu, Zipeng Zhang

CoRR, January, 2025

Helios: Efficient Distributed Dynamic Graph Sampling for Online GNN Inference.

Jie Sun, Zuocheng Shi, Li Su, Wenting Shen, Zeke Wang, Yong Li, Wenyuan Yu, Wei Lin, Fei Wu, Bingsheng He, Jingren Zhou

Proceedings of the 30th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, 2025

2024

ElasticBatch: A Learning-Augmented Elastic Scheduling System for Batch Inference on MIG.

Jiaxing Qi, Wencong Xiao, Mingzhen Li, Chaojie Yang, Yong Li, Wei Lin, Hailong Yang, Zhongzhi Luan, Depei Qian

IEEE Trans. Parallel Distributed Syst., 2024

Rubick: Exploiting Job Reconfigurability for Deep Learning Cluster Scheduling.

Xinyi Zhang, Hanyu Zhao, Wencong Xiao, Xianyan Jia, Fei Xu, Yong Li, Wei Lin, Fangming Liu

CoRR, 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, Wei Lin

CoRR, 2024

Llumnix: Dynamic Scheduling for Large Language Model Serving.

Biao Sun, Ziming Huang, Hanyu Zhao, Wencong Xiao, Xinyi Zhang, Yong Li, Wei Lin

Proceedings of the 18th USENIX Symposium on Operating Systems Design and Implementation, 2024

2023

Flash-LLM: Enabling Low-Cost and Highly-Efficient Large Generative Model Inference With Unstructured Sparsity.

Haojun Xia, Zhen Zheng, Yuchao Li, Donglin Zhuang, Zhongzhu Zhou, Xiafei Qiu, Yong Li, Wei Lin, Shuaiwen Leon Song

Proc. VLDB Endow., 2023

GoldMiner: Elastic Scaling of Training Data Pre-Processing Pipelines for Deep Learning.

Hanyu Zhao, Zhi Yang, Yu Cheng, Chao Tian, Shiru Ren, Wencong Xiao, Man Yuan, Langshi Chen, Kaibo Liu, Yang Zhang, Yong Li, Wei Lin

Proc. ACM Manag. Data, 2023

Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity.

Haojun Xia, Zhen Zheng, Yuchao Li, Donglin Zhuang, Zhongzhu Zhou, Xiafei Qiu, Yong Li, Wei Lin, Shuaiwen Leon Song

CoRR, 2023

TAP: Accelerating Large-Scale DNN Training Through Tensor Automatic Parallelisation.

Ziji Shi, Le Jiang, Ang Wang, Jie Zhang, Xianyan Jia, Yong Li, Chencan Wu, Jialin Li, Wei Lin

CoRR, 2023

Legion: Automatically Pushing the Envelope of Multi-GPU System for Billion-Scale GNN Training.

Jie Sun, Li Su, Zuocheng Shi, Wenting Shen, Zeke Wang, Lei Wang, Jie Zhang, Yong Li, Wenyuan Yu, Jingren Zhou, Fei Wu

Proceedings of the 2023 USENIX Annual Technical Conference, 2023

EasyScale: Elastic Training with Consistent Accuracy and Improved Utilization on GPUs.

Mingzhen Li, Wencong Xiao, Hailong Yang, Biao Sun, Hanyu Zhao, Shiru Ren, Zhongzhi Luan, Xianyan Jia, Yi Liu, Yong Li, Wei Lin, Depei Qian

Proceedings of the International Conference for High Performance Computing, 2023

uGrapher: High-Performance Graph Operator Computation via Unified Abstraction for Graph Neural Networks.

Yangjie Zhou, Jingwen Leng, Yaoxu Song, Shuwen Lu, Mian Wang, Chao Li, Minyi Guo, Wenting Shen, Yong Li, Wei Lin, Xiangwen Liu, Hanqing Wu

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

2022

EasyScale: Accuracy-consistent Elastic Training for Deep Learning.

Mingzhen Li, Wencong Xiao, Biao Sun, Hanyu Zhao, Hailong Yang, Shiru Ren, Zhongzhi Luan, Xianyan Jia, Yi Liu, Yong Li, Depei Qian, Wei Lin

CoRR, 2022

Whale: Efficient Giant Model Training over Heterogeneous GPUs.

Xianyan Jia, Le Jiang, Ang Wang, Wencong Xiao, Ziji Shi, Jie Zhang, Xinyuan Li, Langshi Chen, Yong Li, Zhen Zheng, Xiaoyong Liu, Wei Lin

Proceedings of the 2022 USENIX Annual Technical Conference, 2022

CoGNN: Efficient Scheduling for Concurrent GNN Training on GPUs.

Qingxiao Sun, Yi Liu, Hailong Yang, Ruizhe Zhang, Ming Dun, Mingzhen Li, Xiaoyan Liu, Wencong Xiao, Yong Li, Zhongzhi Luan, Depei Qian

Proceedings of the SC22: International Conference for High Performance Computing, 2022

MLaaS in the Wild: Workload Analysis and Scheduling in Large-Scale Heterogeneous GPU Clusters.

Qizhen Weng, Wencong Xiao, Yinghao Yu, Wei Wang, Cheng Wang, Jian He, Yong Li, Liping Zhang, Wei Lin, Yu Ding

Proceedings of the 19th USENIX Symposium on Networked Systems Design and Implementation, 2022

PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems.

Yuanxing Zhang, Langshi Chen, Siran Yang, Man Yuan, Huimin Yi, Jie Zhang, Jiamang Wang, Jianbo Dong, Yunlong Xu, Yue Song, Yong Li, Di Zhang, Wei Lin, Lin Qu, Bo Zheng

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

Revisiting and Advancing Chinese Natural Language Understanding with Accelerated Heterogeneous Knowledge Pre-training.

Taolin Zhang, Junwei Dong, Jianing Wang, Chengyu Wang, Ang Wang, Yinghui Liu, Jun Huang, Yong Li, Xiaofeng He

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: EMNLP 2022 - Industry Track, Abu Dhabi, UAE, December 7, 2022

2021

GraphScope: A Unified Engine For Big Graph Processing.

Wenfei Fan, Tao He, Longbin Lai, Xue Li, Yong Li, Zhao Li, Zhengping Qian, Chao Tian, Lei Wang, Jingbo Xu, Youyang Yao, Qiang Yin, Wenyuan Yu, Kai Zeng, Kun Zhao, Jingren Zhou, Diwen Zhu, Rong Zhu

Proc. VLDB Endow., 2021

M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining.

Junyang Lin, An Yang, Jinze Bai, Chang Zhou, Le Jiang, Xianyan Jia, Ang Wang, Jie Zhang, Yong Li, Wei Lin, Jingren Zhou, Hongxia Yang

CoRR, 2021

Exploring Sparse Expert Models and Beyond.

An Yang, Junyang Lin, Rui Men, Chang Zhou, Le Jiang, Xianyan Jia, Ang Wang, Jie Zhang, Jiamang Wang, Yong Li, Di Zhang, Wei Lin, Lin Qu, Jingren Zhou, Hongxia Yang

CoRR, 2021

M6: A Chinese Multimodal Pretrainer.

Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, Jin Yu, Yong Li, Wei Lin, Jingren Zhou, Jie Tang, Hongxia Yang

CoRR, 2021

MicroRec: Efficient Recommendation Inference by Hardware and Data Structure Solutions.

Wenqi Jiang, Zhenhao He, Shuai Zhang, Thomas B. Preußer, Kai Zeng, Liang Feng, Jiansong Zhang, Tongxuan Liu, Yong Li, Jingren Zhou, Ce Zhang, Gustavo Alonso

Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

FleetRec: Large-Scale Recommendation Inference on Hybrid GPU-FPGA Clusters.

Wenqi Jiang, Zhenhao He, Shuai Zhang, Kai Zeng, Liang Feng, Jiansong Zhang, Tongxuan Liu, Yong Li, Jingren Zhou, Ce Zhang, Gustavo Alonso

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

2020

Focusing More on Conflicts with Mis-Predictions Helps Language Pre-Training.

Chen Xing, Wencong Xiao, Yong Li, Wei Lin

CoRR, 2020

EasyTransfer - A Simple and Scalable Deep Transfer Learning Platform for NLP Applications.

Minghui Qiu, Peng Li, Hanjie Pan, Chengyu Wang, Ang Wang, Cen Chen, Yaliang Li, Dehong Gao, Jun Huang, Yong Li, Jun Yang, Deng Cai, Wei Lin

CoRR, 2020

Whale: A Unified Distributed Training Framework.

Ang Wang, Xianyan Jia, Le Jiang, Jie Zhang, Yong Li, Wei Lin

CoRR, 2020

MicroRec: Accelerating Deep Recommendation Systems to Microseconds by Hardware and Data Structure Solutions.

Wenqi Jiang, Zhenhao He, Shuai Zhang, Thomas B. Preußer, Kai Zeng, Liang Feng, Jiansong Zhang, Tongxuan Liu, Yong Li, Jingren Zhou, Ce Zhang, Gustavo Alonso

CoRR, 2020

AntMan: Dynamic Scaling on GPU Clusters for Deep Learning.

Wencong Xiao, Shiru Ren, Yong Li, Yang Zhang, Pengyang Hou, Zhi Li, Yihui Feng, Wei Lin, Yangqing Jia

Proceedings of the 14th USENIX Symposium on Operating Systems Design and Implementation, 2020

2019

AliGraph: A Comprehensive Graph Neural Network Platform.

Rong Zhu, Kun Zhao, Hongxia Yang, Wei Lin, Chang Zhou, Baole Ai, Yong Li, Jingren Zhou

Proc. VLDB Endow., 2019

2018

GA-BPNN Based Hybrid Steering Control Approach for Unmanned Driving Electric Vehicle with In-Wheel Motors.

Yong Li, Xing Xu, Wujie Wang

Complex., 2018

A Nonlinear Decoupling Control Approach Using RBFNNI-Based Robust Pole Placement for a Permanent Magnet In-Wheel Motor.

Yong Li, Bin Li, Xing Xu, Xiaodong Sun

IEEE Access, 2018