Zhiquan Lai - RankMe

63 papers A* 1A 3B 4C 8Misc 1Journal 29Unranked 17

Year	Rank	Type	Title / Venue / Authors
2026	A	`conf`	AdaCheck: An Adaptive Checkpointing System for Efficient LLM Training with Redundancy Utilization. FAST Weijie Liu, Shengwei Li, Zhiquan Lai, Keshi Ge, Qiaoling Chen, Peng Sun, Dongsheng Li, Kai Lu
2026	J	`jnl`	Prior-Guided Symbolic Regression: Towards Scientific Consistency in Equation Discovery. CoRR Jing Xiao, Xinhai Chen, Jiaming Peng, Qinglin Wang, Menghan Jia, Zhiquan Lai, Guangping Yu, Dongsheng Li, Tiejun Li, Jie Liu
2026	J	`jnl`	Pro-Prophet: A Systematic Load Balancing Method for Efficient Parallel Training of Large-Scale MoE Models. IEEE Trans. Parallel Distributed Syst. Wei Wang, Zhiquan Lai, Dongsheng Li, Shengwei Li, Weijie Liu, Keshi Ge, Ao Shen, Huayou Su
2025	J	`jnl`	Accurate and Efficient Fine-Tuning of Quantized Large Language Models Through Optimal Balance in Adaptation. Trans. Assoc. Comput. Linguistics Ao Shen, Zhiquan Lai, Qiang Wang, Xionglve Li, Lizhi Zhang, Dongsheng Li, Jiaxin Li
2025	J	`jnl`	AutoPipe-H: A Heterogeneity-Aware Data-Paralleled Pipeline Approach on Commodity GPU Servers. IEEE Trans. Computers Weijie Liu, Kai Lu, Zhiquan Lai, Shengwei Li, Keshi Ge, Dongsheng Li, Xicheng Lu
2025	C	`conf`	Capricorn: Efficient In-Memory Checkpointing for MoE Model Training with Dynamicity Awareness. CLUSTER Wenqian Xie, Zhiquan Lai, Shengwei Li, Weijie Liu, Wei Wang, Yanqi Hao, Dongsheng Li
2025	—	`conf`	EAHP: An Efficient Automatic Hybrid Parallelism Approach with Genetic Algorithm. ICA3PP (2) Yichen Gu, Zhiquan Lai, Weijie Liu, Yinghui Gao
2025	J	`jnl`	Efficient deep neural network training via decreasing precision with layer capacity. Frontiers Comput. Sci. Ao Shen, Zhiquan Lai, Tao Sun, Shengwei Li, Keshi Ge, Weijie Liu, Dongsheng Li
2025	J	`jnl`	FMCC-RT: a scalable and fine-grained all-reduce algorithm for large-scale SMP clusters. Sci. China Inf. Sci. Jintao Peng, Jie Liu, Jianbin Fang, Min Xie, Yi Dai, Zhiquan Lai, Bo Yang, Chunye Gong, Xinjun Mao, Guo Mao, Jie Ren
2025	B	`conf`	HMGraph: Boosting GNN Training on Hierarchical Memory via Coordinated Cache. ICPP Lizhi Zhang, Menghan Jia, Zhiquan Lai, Qiao Li, Yiming Zhang, Dongsheng Li
2025	J	`jnl`	Nightjar: Dynamic Adaptive Speculative Decoding for Large Language Models Serving. CoRR Rui Li, Zhaoning Zhang, Libo Zhang, Huaimin Wang, Xiang Fu, Zhiquan Lai
2025	J	`jnl`	Oases: Efficient Large-Scale Model Training on Commodity Servers via Overlapped and Automated Tensor Model Parallelism. IEEE Trans. Parallel Distributed Syst. Shengwei Li, Zhiquan Lai, Dongsheng Li, Yanqi Hao, Weijie Liu, Keshi Ge, Xiaoge Deng, Kai Lu
2025	J	`jnl`	Optimizing Fine-Tuning in Quantized Language Models: An In-Depth Analysis of Key Variables. Comput. Mater. Continua Ao Shen, Zhiquan Lai, Dongsheng Li, Xiaoyu Hu
2024	J	`jnl`	A Memory-Efficient Hybrid Parallel Framework for Deep Neural Network Training. IEEE Trans. Parallel Distributed Syst. Dongsheng Li, Shengwei Li, Zhiquan Lai, Yongquan Fu, Xiangyu Ye, Lei Cai, Linbo Qiao
2024	J	`jnl`	A Multidimensional Communication Scheduling Method for Hybrid Parallel DNN Training. IEEE Trans. Parallel Distributed Syst. Shengwei Li, Kai Lu, Zhiquan Lai, Weijie Liu, Keshi Ge, Dong Sheng Li
2024	J	`jnl`	Accurate and Efficient Fine-Tuning of Quantized Large Language Models Through Optimal Balance. CoRR Ao Shen, Qiang Wang, Zhiquan Lai, Xionglve Li, Dong-sheng Li
2024	C	`conf`	HSDP: Accelerating Large-scale Model Training via Efficient Sharded Data Parallelism. ISPA Yanqi Hao, Zhiquan Lai, Wei Wang, Shengwei Li, Weijie Liu, Keshi Ge, Dongsheng Li
2024	A*	`conf`	Hierarchical Adaptive Pooling by Capturing High-order Dependency for Graph Representation Learning (Extended Abstract). ICDE Ning Liu, Songlei Jian, Dongsheng Li, Yiming Zhang, Zhiquan Lai, Hongzuo Xu
2024	J	`jnl`	Pro-Prophet: A Systematic Load Balancing Method for Efficient Parallel Training of Large-scale MoE Models. CoRR Wei Wang, Zhiquan Lai, Shengwei Li, Weijie Liu, Keshi Ge, Ao Shen, Huayou Su, Dong Sheng Li
2024	A	`conf`	The Self-adaptive and Topology-aware MPI_Bcast leveraging Collective offload on Tianhe Express Interconnect. IPDPS Chongshan Liang, Yi Dai, Jun Xia, Jinbo Xu, Jintao Peng, Weixia Xu, Ming Xie, Jie Liu, Zhiquan Lai, Sheng Ma, Qi Zhu
2023	J	`jnl`	A Survey on Auto-Parallelism of Large-Scale Deep Learning Training. IEEE Trans. Parallel Distributed Syst. Peng Liang, Yu Tang, Xiaoda Zhang, Youhui Bai, Teng Su, Zhiquan Lai, Linbo Qiao, Dongsheng Li
2023	J	`jnl`	Accelerating GNN Training by Adapting Large Graphs to Distributed Heterogeneous Architectures. IEEE Trans. Computers Lizhi Zhang, Kai Lu, Zhiquan Lai, Yongquan Fu, Yu Tang, Dongsheng Li
2023	—	`conf`	Auto-Divide GNN: Accelerating GNN Training with Subgraph Division. Euro-Par Hongyu Chen, Zhejiang Ran, Keshi Ge, Zhiquan Lai, Jingfei Jiang, Dongsheng Li
2023	J	`jnl`	Automated Tensor Model Parallelism with Overlapped Communication for Efficient Foundation Model Training. CoRR Shengwei Li, Zhiquan Lai, Yanqi Hao, Weijie Liu, Keshi Ge, Xiaoge Deng, Dongsheng Li, Kai Lu
2023	—	`conf`	CD-Sched: An Automated Scheduling Framework for Accelerating Neural Network Training on Shared Memory CPU-DSP Platforms. PCCNT Yuanyuan Xiao, Zhiquan Lai, Dongsheng Li
2023	—	`conf`	Communication Analysis for Multidimensional Parallel Training of Large-scale DNN Models. HPCC/DSS/SmartCity/DependSys Zhiquan Lai, Yanqi Hao, Shengwei Li, Dongsheng Li
2023	J	`jnl`	Compressed Collective Sparse-Sketch for Distributed Data-Parallel Training of Deep Learning Models. IEEE J. Sel. Areas Commun. Keshi Ge, Kai Lu, Yongquan Fu, Xiaoge Deng, Zhiquan Lai, Dongsheng Li
2023	—	`conf`	Efficient Large Models Fine-tuning on Commodity Servers via Memory-balanced Pipeline Parallelism. HPCC/DSS/SmartCity/DependSys Yujie Liu, Zhiquan Lai, Weijie Liu, Wei Wang, Dongsheng Li
2023	J	`jnl`	Hierarchical Adaptive Pooling by Capturing High-Order Dependency for Graph Representation Learning. IEEE Trans. Knowl. Data Eng. Ning Liu, Songlei Jian, Dongsheng Li, Yiming Zhang, Zhiquan Lai, Hongzuo Xu
2023	J	`jnl`	Merak: An Efficient Distributed DNN Training Framework With Automated 3D Parallelism for Giant Foundation Models. IEEE Trans. Parallel Distributed Syst. Zhiquan Lai, Shengwei Li, Xudong Tang, Keshi Ge, Weijie Liu, Yabo Duan, Linbo Qiao, Dongsheng Li
2023	C	`conf`	Prophet: Fine-grained Load Balancing for Parallel Training of Large-scale MoE Models. CLUSTER Wei Wang, Zhiquan Lai, Shengwei Li, Weijie Liu, Keshi Ge, Yujie Liu, Ao Shen, Dongsheng Li
2023	—	`conf`	Rethinking the Distributed DNN Training Cluster Design from the Cost-effectiveness View. HPCC/DSS/SmartCity/DependSys Zhiquan Lai, Yujie Liu, Wei Wang, Yanqi Hao, Dongsheng Li
2022	—	`conf`	Accelerating Sample-based GNN Training by Feature Caching on GPUs. SmartCloud Yuqi He, Zhiquan Lai, Zhejiang Ran, Lizhi Zhang, Dongsheng Li
2022	C	`conf`	AutoPipe: A Fast Pipeline Parallelism Approach with Balanced Partitioning and Micro-batch Slicing. CLUSTER Weijie Liu, Zhiquan Lai, Shengwei Li, Yabo Duan, Keshi Ge, Dongsheng Li
2022	J	`jnl`	BRGraph: An efficient graph neural network training system by reusing batch data on GPU. Concurr. Comput. Pract. Exp. Keshi Ge, Zhejiang Ran, Zhiquan Lai, Lizhi Zhang, Dongsheng Li
2022	J	`jnl`	DELTA: Dynamically Optimizing GPU Memory beyond Tensor Recomputation. CoRR Yu Tang, Chenyu Wang, Yufan Zhang, Yuliang Liu, Xingcheng Zhang, Linbo Qiao, Zhiquan Lai, Dongsheng Li
2022	B	`conf`	EmbRace: Accelerating Sparse Communication for Distributed Training of Deep Neural Networks. ICPP Shengwei Li, Zhiquan Lai, Dongsheng Li, Yiming Zhang, Xiangyu Ye, Yabo Duan
2022	C	`conf`	HPH: Hybrid Parallelism on Heterogeneous Clusters for Accelerating Large-scale DNNs Training. CLUSTER Yabo Duan, Zhiquan Lai, Shengwei Li, Weijie Liu, Keshi Ge, Peng Liang, Dongsheng Li
2022	J	`jnl`	Merak: An Efficient Distributed DNN Training Framework with Automated 3D Parallelism for Giant Foundation Models. CoRR Zhiquan Lai, Shengwei Li, Xudong Tang, Keshi Ge, Weijie Liu, Yabo Duan, Linbo Qiao, Dongsheng Li
2022	Misc	`conf`	S2 Reducer: High-Performance Sparse Communication to Accelerate Distributed Deep Learning. ICASSP Keshi Ge, Yongquan Fu, Yiming Zhang, Zhiquan Lai, Xiaoge Deng, Dongsheng Li
2022	—	`conf`	SCGraph: Accelerating Sample-based GNN Training by Staged Caching of Features on GPUs. ISPA/BDCloud/SocialCom/SustainCom Yuqi He, Zhiquan Lai, Zhejiang Ran, Lizhi Zhang, Dongsheng Li
2021	C	`conf`	2PGraph: Accelerating GNN Training over Large Graphs on GPU Clusters. CLUSTER Lizhi Zhang, Zhiquan Lai, Shengwei Li, Yu Tang, Feng Liu, Dongsheng Li
2021	C	`conf`	Accelerate Graph Neural Network Training by Reusing Batch Data on GPUs. IPCCC Zhejiang Ran, Zhiquan Lai, Lizhi Zhang, Dongsheng Li
2021	C	`conf`	CASQ: Accelerate Distributed Deep Learning with Sketch-Based Gradient Quantization. CLUSTER Keshi Ge, Yiming Zhang, Yongquan Fu, Zhiquan Lai, Xiaoge Deng, Dongsheng Li
2021	J	`jnl`	Coordinative Scheduling of Computation and Communication in Data-Parallel Systems. IEEE Trans. Computers Dongsheng Li, Zhiyao Hu, Zhiquan Lai, Yiming Zhang, Kai Lu
2021	J	`jnl`	EmbRace: Accelerating Sparse Communication for Distributed Training of NLP Neural Networks. CoRR Shengwei Li, Zhiquan Lai, Dongsheng Li, Xiangyu Ye, Yabo Duan
2021	—	`conf`	HMA: An Efficient Training Method for NLP Models. ICIAI Yuetong Yang, Zhiquan Lai, Lei Cai, Dongsheng Li
2021	J	`jnl`	Hierarchical Adaptive Pooling by Capturing High-order Dependency for Graph Representation Learning. CoRR Ning Liu, Songlei Jian, Dongsheng Li, Yiming Zhang, Zhiquan Lai, Hongzuo Xu
2021	B	`conf`	Hippie: A Data-Paralleled Pipeline Approach to Improve Memory-Efficiency and Scalability for Large DNN Training. ICPP Xiangyu Ye, Zhiquan Lai, Shengwei Li, Lei Cai, Ding Sun, Linbo Qiao, Dongsheng Li
2021	—	`conf`	PCGraph: Accelerating GNN Inference on Large Graphs via Partition Caching. ISPA/BDCloud/SocialCom/SustainCom Lizhi Zhang, Zhiquan Lai, Yu Tang, Dongsheng Li, Feng Liu, Xiaochun Luo
2021	—	`conf`	Prediction of the Cyanobacteria Coverage in Time-series Images based on Convolutional Neural Network. ICCCV Xiangyu Ye, Zhiquan Lai, Dongsheng Li
2021	J	`jnl`	S2 Reducer: High-Performance Sparse Communication to Accelerate Distributed Deep Learning. CoRR Keshi Ge, Yongquan Fu, Zhiquan Lai, Xiaoge Deng, Dongsheng Li
2020	J	`jnl`	ADMMiRNN: Training RNN with Stable Convergence via An Efficient ADMM Approach. CoRR Yu Tang, Zhigang Kan, Dequan Sun, Linbo Qiao, Jingjing Xiao, Zhiquan Lai, Dongsheng Li
2020	—	`conf`	ADMMiRNN: Training RNN with Stable Convergence via an Efficient ADMM Approach. ECML/PKDD (2) Yu Tang, Zhigang Kan, Dequan Sun, Linbo Qiao, Jingjing Xiao, Zhiquan Lai, Dongsheng Li
2020	—	`conf`	Poster Abstract: Model Average-based Distributed Training for Sparse Deep Neural Networks. INFOCOM Workshops Yuetong Yang, Zhiquan Lai, Lei Cai, Dongsheng Li
2019	A	`conf`	HPDL: Towards a General Framework for High-performance Distributed Deep Learning. ICDCS Dongsheng Li, Zhiquan Lai, Keshi Ge, Yiming Zhang, Zhaoning Zhang, Qinglin Wang, Huaimin Wang
2017	—	`conf`	A Two-Tiered Defence of Techniques to Prevent SQL Injection Attacks. IMIS Yan Zhu, Guidong Zhang, Zhiquan Lai, Boya Niu, Yongjun Shen
2017	J	`jnl`	PoweRock: Power Modeling and Flexible Dynamic Power Management for Many-Core Architectures. IEEE Syst. J. Zhiquan Lai, King Tin Lam, Cho-Li Wang, Jinshu Su
2015	J	`jnl`	Latency-aware DVFS for efficient power state transitions on many-core architectures. J. Supercomput. Zhiquan Lai, King Tin Lam, Cho-Li Wang, Jinshu Su
2014	—	`conf`	A Power Modelling Approach for Many-Core Architectures. SKG Zhiquan Lai, King Tin Lam, Cho-Li Wang, Jinshu Su
2014	—	`conf`	Efficient DVFS to Prevent Hard Faults for Many-Core Architectures. ICT-EurAsia Zhiquan Lai, Baokang Zhao, Jinshu Su
2014	B	`conf`	Rhymes: A shared virtual memory system for non-coherent tiled many-core architectures. ICPADS King Tin Lam, Jinghao Shi, Dominic Hung, Cho-Li Wang, Zhiquan Lai, Wangbin Zhu, Youliang Yan
2012	—	`conf`	Mining of Attack Models in IDS Alerts from Network Backbone by a Two-stage Clustering Method. IPDPS Workshops Lin-Bo Qiao, Bo-Feng Zhang, Zhiquan Lai, Jinshu Su