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2020 – today
- 2026
[i2]Chia-Chi Hsieh, Zan Zong, Xinyang Chen, Jianjiang Li, Jidong Zhai, Lijie Wen:
FlowPrefill: Decoupling Preemption from Prefill Scheduling Granularity to Mitigate Head-of-Line Blocking in LLM Serving. CoRR abs/2602.16603 (2026)- 2025
- [j5]Zan Zong, Minkun Guo, Mingshu Zhai, Yinan Tang, Jianjiang Li, Jidong Zhai:
Training Large Models on Heterogeneous and Geo-Distributed Resource with Constricted Networks. Big Data Min. Anal. 8(4): 966-980 (2025) - [j4]Leilei Lin
, Yunuo Cao, Wenlong Chen, Zan Zong, Chen Qian, Lijie Wen:
Multi-View Trace Clustering Based on Graph Convolutional Networks in Process Mining. IEEE Trans. Serv. Comput. 18(4): 2226-2237 (2025) - [c9]Yuyang Jin, Xirui Shui, Mingshu Zhai, Zan Zong, Feng Zhang, Felix Wolf, Jidong Zhai:
TraceFlow: Efficient Trace Analysis for Large-Scale Parallel Applications via Interaction Pattern-Aware Trace Distribution. SC 2025: 383-396 - [c8]Haoyu Yang, Zan Zong, Yuyang Jin, Kinman Lei, Jiaao He, Qigang Yang, Jidong Zhai:
UltraAttn: Efficiently Parallelizing Attention through Hierarchical Context-Tiling. SC 2025: 1769-1784 - [i1]Lijuan Jiang, Xingjian Qian, Zhenxiang Ma, Zan Zong, Hengjie Li, Chao Yang, Jidong Zhai:
A Flexible Programmable Pipeline Parallelism Framework for Efficient DNN Training. CoRR abs/2510.05112 (2025) - 2023
- [j3]Zan Zong, Li Lin, Leilei Lin, Lijie Wen, Yu Sun:
STR: Hybrid Tensor Re-Generation to Break Memory Wall for DNN Training. IEEE Trans. Parallel Distributed Syst. 34(8): 2403-2418 (2023) - [c7]Mingshu Zhai, Jiaao He, Zixuan Ma, Zan Zong, Runqing Zhang, Jidong Zhai:
SmartMoE: Efficiently Training Sparsely-Activated Models through Combining Offline and Online Parallelization. USENIX ATC 2023: 961-975 - 2022
- [j2]Zan Zong, Lijie Wen, Xuming Hu, Rui Han, Chen Qian, Li Lin:
MespaConfig: Memory-Sparing Configuration Auto-Tuning for Co-Located In-Memory Cluster Computing Jobs. IEEE Trans. Serv. Comput. 15(5): 2883-2896 (2022) - [c6]Lijie Wen, Zan Zong, Li Lin, Leilei Lin:
A Swap Dominated Tensor Re-Generation Strategy for Training Deep Learning Models. IPDPS 2022: 996-1006 - 2021
- [c5]Li Lin, Zan Zong, Lijie Wen, Chen Qian, Shuang Li, Jianmin Wang:
MM-CPred: A Multi-task Predictive Model for Continuous-Time Event Sequences with Mixture Learning Losses. DASFAA (1) 2021: 509-525 - 2020
- [c4]Chen Qian, Lijie Wen, Akhil Kumar, Leilei Lin, Li Lin, Zan Zong, Shu'ang Li, Jianmin Wang:
An Approach for Process Model Extraction by Multi-grained Text Classification. CAiSE 2020: 268-282 - [c3]Zan Zong, Lijie Wen, Xiao Liu, Li Lin, Chen Qian, Leilei Lin:
Scaleplus: Towards Fast Scaling of Distributed Streaming Dataflows. ISPA/BDCloud/SocialCom/SustainCom 2020: 260-268
2010 – 2019
- 2019
- [j1]Rui Han, Chi Harold Liu, Zan Zong, Lydia Y. Chen, Wending Liu, Siyi Wang, Jianfeng Zhan:
Workload-Adaptive Configuration Tuning for Hierarchical Cloud Schedulers. IEEE Trans. Parallel Distributed Syst. 30(12): 2879-2895 (2019) - 2018
- [c2]Rui Han, Zan Zong, Lydia Y. Chen, Siyi Wang, Jianfeng Zhan:
AdaptiveConfig: Run-Time Configuration of Cluster Schedulers for Cloud Short-Running Jobs. ICDCS 2018: 1519-1526 - 2017
- [c1]Rui Han, Zan Zong, Fan Zhang, José Luis Vázquez-Poletti, Zhen Jia, Lei Wang:
CloudMix: Generating Diverse and Reducible Workloads for Cloud Systems. CLOUD 2017: 496-503
Coauthor Index
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