Xiaonan Nie

According to our database, Xiaonan Nie authored at least 31 papers between 2021 and 2025.

Collaborative distances:

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

2025

Acceleration Algorithms in GNNs: A Survey.

Lu Ma, Zeang Sheng, Xunkai Li, Xinyi Gao, Zhezheng Hao, Ling Yang, Xiaonan Nie, Jiawei Jiang, Wentao Zhang, Bin Cui

IEEE Trans. Knowl. Data Eng., June, 2025

PQCache: Product Quantization-based KVCache for Long Context LLM Inference.

Hailin Zhang, Xiaodong Ji, Yilin Chen, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Weipeng Chen, Bin Cui

Proc. ACM Manag. Data, June, 2025

Malleus: Straggler-Resilient Hybrid Parallel Training of Large-scale Models via Malleable Data and Model Parallelization.

Haoyang Li, Fangcheng Fu, Hao Ge, Sheng Lin, Xuanyu Wang, Jiawen Niu, Yujie Wang, Hailin Zhang, Xiaonan Nie, Bin Cui

Proc. ACM Manag. Data, June, 2025

Seedance 1.0: Exploring the Boundaries of Video Generation Models.

Yu Gao, Haoyuan Guo, Tuyen Hoang, Weilin Huang, Lu Jiang, Fangyuan Kong, Huixia Li, Jiashi Li, Liang Li, Xiaojie Li, Xunsong Li, Yifu Li, Shanchuan Lin, Zhijie Lin, Jiawei Liu, Shu Liu, Xiaonan Nie, Zhiwu Qing, Yuxi Ren, Limin Sun, Zhi Tian, Rui Wang, Sen Wang, Guoqiang Wei, Guohong Wu, Jie Wu, Ruiqi Xia, Fei Xiao, Xuefeng Xiao, Jiangqiao Yan, Ceyuan Yang, Jianchao Yang, Runkai Yang, Tao Yang, Yihang Yang, Zilyu Ye, Xuejiao Zeng, Yan Zeng, Heng Zhang, Yang Zhao, Xiaozheng Zheng, Peihao Zhu, Jiaxin Zou, Feilong Zuo

CoRR, June, 2025

Efficient and scalable huge embedding model training via distributed cache management.

Xupeng Miao, Hailin Zhang, Yining Shi, Xiaonan Nie, Zhi Yang, Yangyu Tao, Jie Jiang, Bin Cui

VLDB J., May, 2025

Emerging Properties in Unified Multimodal Pretraining.

Chaorui Deng, Deyao Zhu, Kunchang Li, Chenhui Gou, Feng Li, Zeyu Wang, Shu Zhong, Weihao Yu, Xiaonan Nie, Ziang Song, Shi Guang, Haoqi Fan

CoRR, May, 2025

MEMO: Fine-grained Tensor Management For Ultra-long Context LLM Training.

Pinxue Zhao, Hailin Zhang, Fangcheng Fu, Xiaonan Nie, Qibin Liu, Fang Yang, Yuanbo Peng, Dian Jiao, Shuaipeng Li, Jinbao Xue, Yangyu Tao, Bin Cui

Proc. ACM Manag. Data, February, 2025

ByteScale: Efficient Scaling of LLM Training with a 2048K Context Length on More Than 12,000 GPUs.

Hao Ge, Junda Feng, Qi Huang, Fangcheng Fu, Xiaonan Nie, Lei Zuo, Haibin Lin, Bin Cui, Xin Liu

CoRR, February, 2025

NetMoE: Accelerating MoE Training through Dynamic Sample Placement.

Xinyi Liu, Yujie Wang, Fangcheng Fu, Xupeng Miao, Shenhan Zhu, Xiaonan Nie, Bin Cui

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

DataSculpt: A Holistic Data Management Framework for Long-Context LLMs Training.

Keer Lu, Xiaonan Nie, Zheng Liang, Da Pan, Shusen Zhang, Keshi Zhao, Weipeng Chen, Zenan Zhou, Guosheng Dong, Bin Cui, Wentao Zhang

Proceedings of the 41st IEEE International Conference on Data Engineering, 2025

2024

Improving Automatic Parallel Training via Balanced Memory Workload Optimization.

Yujie Wang, Youhe Jiang, Xupeng Miao, Fangcheng Fu, Shenhan Zhu, Xiaonan Nie, Yaofeng Tu, Bin Cui

IEEE Trans. Knowl. Data Eng., 2024

FlashFlex: Accommodating Large Language Model Training over Heterogeneous Environment.

Ran Yan, Youhe Jiang, Wangcheng Tao, Xiaonan Nie, Bin Cui, Binhang Yuan

CoRR, 2024

DataSculpt: Crafting Data Landscapes for LLM Post-Training through Multi-objective Partitioning.

Keer Lu, Zheng Liang, Xiaonan Nie, Da Pan, Shusen Zhang, Keshi Zhao, Weipeng Chen, Zenan Zhou, Guosheng Dong, Wentao Zhang, Bin Cui

CoRR, 2024

BaichuanSEED: Sharing the Potential of ExtensivE Data Collection and Deduplication by Introducing a Competitive Large Language Model Baseline.

Guosheng Dong, Da Pan, Yiding Sun, Shusen Zhang, Zheng Liang, Xin Wu, Yanjun Shen, Fan Yang, Haoze Sun, Tianpeng Li, Mingan Lin, Jianhua Xu, Yufan Zhang, Xiaonan Nie, Lei Su, Bingning Wang, Wentao Zhang, Jiaxin Mao, Zenan Zhou, Weipeng Chen

CoRR, 2024

Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs.

Pinxue Zhao, Hailin Zhang, Fangcheng Fu, Xiaonan Nie, Qibin Liu, Fang Yang, Yuanbo Peng, Dian Jiao, Shuaipeng Li, Jinbao Xue, Yangyu Tao, Bin Cui

CoRR, 2024

Clover: Regressive Lightweight Speculative Decoding with Sequential Knowledge.

Bin Xiao, Chunan Shi, Xiaonan Nie, Fan Yang, Xiangwei Deng, Lei Su, Weipeng Chen, Bin Cui

CoRR, 2024

Enabling Parallelism Hot Switching for Efficient Training of Large Language Models.

Hao Ge, Fangcheng Fu, Haoyang Li, Xuanyu Wang, Sheng Lin, Yujie Wang, Xiaonan Nie, Hailin Zhang, Xupeng Miao, Bin Cui

Proceedings of the ACM SIGOPS 30th Symposium on Operating Systems Principles, 2024

LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing.

Xiaonan Nie, Qibin Liu, Fangcheng Fu, Shenhan Zhu, Xupeng Miao, Xiaoyang Li, Yang Zhang, Shouda Liu, Bin Cui

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Hetu: a highly efficient automatic parallel distributed deep learning system.

Xupeng Miao, Xiaonan Nie, Hailin Zhang, Tong Zhao, Bin Cui

Sci. China Inf. Sci., January, 2023

Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent.

Xiaonan Nie, Yi Liu, Fangcheng Fu, Jinbao Xue, Dian Jiao, Xupeng Miao, Yangyu Tao, Bin Cui

Proc. VLDB Endow., 2023

FlexMoE: Scaling Large-scale Sparse Pre-trained Model Training via Dynamic Device Placement.

Xiaonan Nie, Xupeng Miao, Zilong Wang, Zichao Yang, Jilong Xue, Lingxiao Ma, Gang Cao, Bin Cui

Proc. ACM Manag. Data, 2023

Improving Automatic Parallel Training via Balanced Memory Workload Optimization.

Yujie Wang, Youhe Jiang, Xupeng Miao, Fangcheng Fu, Xiaonan Nie, Bin Cui

CoRR, 2023

OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning.

Youhe Jiang, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Bin Cui

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism.

Xupeng Miao, Yujie Wang, Youhe Jiang, Chunan Shi, Xiaonan Nie, Hailin Zhang, Bin Cui

Proc. VLDB Endow., 2022

OSDP: Optimal Sharded Data Parallel for Distributed Deep Learning.

Youhe Jiang, Xupeng Miao, Xiaonan Nie, Bin Cui

CoRR, 2022

HetuMoE: An Efficient Trillion-scale Mixture-of-Expert Distributed Training System.

Xiaonan Nie, Pinxue Zhao, Xupeng Miao, Tong Zhao, Bin Cui

CoRR, 2022

HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training.

Xupeng Miao, Yining Shi, Hailin Zhang, Xin Zhang, Xiaonan Nie, Zhi Yang, Bin Cui

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

TSPLIT: Fine-grained GPU Memory Management for Efficient DNN Training via Tensor Splitting.

Xiaonan Nie, Xupeng Miao, Zhi Yang, Bin Cui

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

2021

HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework.

Xupeng Miao, Hailin Zhang, Yining Shi, Xiaonan Nie, Zhi Yang, Yangyu Tao, Bin Cui

Proc. VLDB Endow., 2021

Dense-to-Sparse Gate for Mixture-of-Experts.

Xiaonan Nie, Shijie Cao, Xupeng Miao, Lingxiao Ma, Jilong Xue, Youshan Miao, Zichao Yang, Zhi Yang, Bin Cui

CoRR, 2021

Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce.

Xupeng Miao, Xiaonan Nie, Yingxia Shao, Zhi Yang, Jiawei Jiang, Lingxiao Ma, Bin Cui

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021