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Redundancy-free and load-balanced TGNN training with hierarchical pipeline parallelism Journal article
Xia, Yaqi, Zhang, Zheng, Yang, Donglin, Hu, Chuang, Zhou, Xiaobo, Chen, Hongyang, Sang, Qianlong, Cheng, Dazhao. Redundancy-free and load-balanced TGNN training with hierarchical pipeline parallelism[J]. IEEE Transactions on Parallel and Distributed Systems, 2024, 35(11), 1904-1919.
Authors:  Xia, Yaqi;  Zhang, Zheng;  Yang, Donglin;  Hu, Chuang;  Zhou, Xiaobo; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:5.6/4.5 | Submit date：2024/08/05
Communication Balance  Distributed Training  Dynamic Gnn  Pipeline Parallelism  Redundancy-free  
Raptor-T: A Fused and Memory-Efficient Sparse Transformer for Long and Variable-Length Sequences Journal article
Wang, Hulin, Yang, Donglin, Xia, Yaqi, Zhang, Zheng, Wang, Qigang, Fan, Jianping, Zhou, Xiaobo, Cheng, Dazhao. Raptor-T: A Fused and Memory-Efficient Sparse Transformer for Long and Variable-Length Sequences[J]. IEEE TRANSACTIONS ON COMPUTERS, 2024, 73(7), 1852-1865.
Authors:  Wang, Hulin;  Yang, Donglin;  Xia, Yaqi;  Zhang, Zheng;  Wang, Qigang; et al.
Favorite | TC[WOS]:1 TC[Scopus]:1  IF:3.6/3.2 | Submit date：2024/05/16
Sparse Transformer  Inference Acceleration  Gpu  Deep Learning  Memory Optimization  Resource Management  
Improving BOTDA Performance Based on Differential Pulsewidth Pair and FFDNet Journal article
Ge, Xiaopeng, Wang, Tao, Zhang, Qian, Peng, Jiaxin, Zhu, Yaqi, Zhang, Yongqi, Zhang, Jianzhong, Qiao, Lijun, Zhang, Mingjiang. Improving BOTDA Performance Based on Differential Pulsewidth Pair and FFDNet[J]. IEEE Sensors Journal, 2024, 24(10), 16137-16144.
Authors:  Ge, Xiaopeng;  Wang, Tao;  Zhang, Qian;  Peng, Jiaxin;  Zhu, Yaqi; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:4.3/4.2 | Submit date：2024/06/05
Brillouin Optical Time Domain Analysis (Botda)  Deep Learning  Differential Pulsewidth Pair (Dpp)  Fast And Flexible Denoising Convolutional Neural Network (Ffdnet)  
Tunable Adhesion for All-Dry Transfer of 2D Materials Enabled by the Freezing of Transfer Medium Journal article
Chen, Sensheng, Chen, Ge, Zhao, Yixuan, Bu, Saiyu, Hu, Zhaoning, Mao, Boyang, Wu, Haotian, Liao, Junhao, Li, Fangfang, Zhou, Chaofan, Guo, Bingbing, Liu, Wenlin, Zhu, Yaqi, Lu, Qi, Hu, Jingyi, Shang, Mingpeng, Shi, Zhuofeng, Yu, Beiming, Zhang, Xiaodong, Zhao, Zhenxin, Jia, Kaicheng, Zhang, Yanfeng, Sun, Pengzhan, Liu, Zhongfan, Lin, Li, Wang, Xiaomin. Tunable Adhesion for All-Dry Transfer of 2D Materials Enabled by the Freezing of Transfer Medium[J]. Advanced Materials, 2024, 36(15), 2308950.
Authors:  Chen, Sensheng;  Chen, Ge;  Zhao, Yixuan;  Bu, Saiyu;  Hu, Zhaoning; et al.
Favorite | TC[WOS]:2 TC[Scopus]:3  IF:27.4/30.2 | Submit date：2024/05/02
Cvd Graphene Films  Dry Transfer  Graphene Transfer  Graphene Wafers  Ultraclean Surface  
High Spatial Resolution BOTDA Based on Deconvolution and All Phase Digital Filtering Journal article
Peng, Jiaxin, Wang, Tao, Zhang, Qian, Ge, Xiaopeng, Zhu, Yaqi, Zhang, Yongqi, Zhang, Jianzhong, Li, Jian, Zhang, Mingjiang. High Spatial Resolution BOTDA Based on Deconvolution and All Phase Digital Filtering[J]. IEEE Sensors Journal, 2024, 24(7), 10024-10030.
Authors:  Peng, Jiaxin;  Wang, Tao;  Zhang, Qian;  Ge, Xiaopeng;  Zhu, Yaqi; et al.
Favorite | TC[WOS]:2 TC[Scopus]:2  IF:4.3/4.2 | Submit date：2024/05/02
All Phase Dft Digital Filter  Brillouin Optical Time-domain Analysis  Deconvolution Algorithm  Signal-to-noise Ratio (Snr)  Spatial Resolution  
MPMoE: Memory Efficient MoE for Pre-Trained Models With Adaptive Pipeline Parallelism Journal article
Zhang, Zheng, Xia, Yaqi, Wang, Hulin, Yang, Donglin, Hu, Chuang, Zhou, Xiaobo, Cheng, Dazhao. MPMoE: Memory Efficient MoE for Pre-Trained Models With Adaptive Pipeline Parallelism[J]. IEEE Transactions on Parallel and Distributed Systems, 2024, 35(6), 843-856.
Authors:  Zhang, Zheng;  Xia, Yaqi;  Wang, Hulin;  Yang, Donglin;  Hu, Chuang; et al.
Favorite | TC[WOS]:0 TC[Scopus]:1  IF:5.6/4.5 | Submit date：2024/05/16
Distributed Training  Memory Redundancy  Mixture Of Experts  Performance Model  Pipeline Parallelism  
Recent trends in the transfer of graphene films Journal article
Zhu, Yaqi, Shi, Zhuofeng, Zhao, Yixuan, Bu, Saiyu, Hu, Zhaoning, Liao, Junhao, Lu, Qi, Zhou, Chaofan, Guo, Bingbing, Shang, Mingpeng, Li, Fangfang, Xu, Zhiying, Zhang, Jialin, Xie, Qin, Li, Chunhu, Sun, Pengzhan, Mao, Boyang, Zhang, Xiaodong, Liu, Zhongfan, Lin, Li. Recent trends in the transfer of graphene films[J]. Nanoscale, 2024, 16(16), 7862-7873.
Authors:  Zhu, Yaqi;  Shi, Zhuofeng;  Zhao, Yixuan;  Bu, Saiyu;  Hu, Zhaoning; et al.
Favorite | TC[WOS]:3 TC[Scopus]:3  IF:5.8/6.1 | Submit date：2024/05/16
Single-layer Graphene  Large-area  2-dimensional Materials  Monolayer Graphene  Cvd Graphene  Transparent  Permeation  Growth  Copper  Water  
Redundancy-Free High-Performance Dynamic GNN Training with Hierarchical Pipeline Parallelism Conference paper
Xia, Yaqi, Zhang, Zheng, Wang, Hulin, Yang, Donglin, Zhou, Xiaobo, Cheng, Dazhao. Redundancy-Free High-Performance Dynamic GNN Training with Hierarchical Pipeline Parallelism[C], 2023, 17-13.
Authors:  Xia, Yaqi;  Zhang, Zheng;  Wang, Hulin;  Yang, Donglin;  Zhou, Xiaobo; et al.
Favorite | TC[WOS]:4 TC[Scopus]:5 | Submit date：2023/08/08
MPipeMoE: Memory Efficient MoE for Pre-trained Models with Adaptive Pipeline Parallelism Conference paper
Zhang, Zheng, Yang, Donglin, Xia, Yaqi, Ding, Liang, Tao, Dacheng, Zhou, Xiaobo, Cheng, Dazhao. MPipeMoE: Memory Efficient MoE for Pre-trained Models with Adaptive Pipeline Parallelism[C], USA:Institute of Electrical and Electronics Engineers Inc., 2023, 167-177.
Authors:  Zhang, Zheng;  Yang, Donglin;  Xia, Yaqi;  Ding, Liang;  Tao, Dacheng; et al.
Favorite | TC[WOS]:1 TC[Scopus]:1 | Submit date：2023/08/08
Mixture Of Experts  Pipeline Parallelism  Distributed Training  Memory Efficiency  
Shape and Shear Stress Impact on the Toxicity of Mesoporous Silica Nanoparticles: In Vitro and In Vivo Evidence Journal article
Cheng, Yaxin, Tao, Jinsong, Zhang, Yaqi, Xi, Long, Han, Run, Xu, Meng, Lee, Simon Ming Yuen, Ge, Wei, Gan, Yong, Zheng, Ying. Shape and Shear Stress Impact on the Toxicity of Mesoporous Silica Nanoparticles: In Vitro and In Vivo Evidence[J]. Molecular Pharmaceutics, 2023, 20(6), 3187-3201.
Authors:  Cheng, Yaxin;  Tao, Jinsong;  Zhang, Yaqi;  Xi, Long;  Han, Run; et al.
Favorite | TC[WOS]:3 TC[Scopus]:4  IF:4.5/4.6 | Submit date：2023/07/20
In Vitro Blood Flow Model  Mesoporous Silica Nanoparticles (Msns)  Shape  Shear Stress  Toxicity