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MingYu Yan
Tytuł
Cytowane przez
Cytowane przez
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Hygcn: A gcn accelerator with hybrid architecture
M Yan, L Deng, X Hu, L Liang, Y Feng, X Ye, Z Zhang, D Fan, Y Xie
2020 IEEE International Symposium on High Performance Computer Architecture …, 2020
1412020
Alleviating irregularity in graph analytics acceleration: A hardware/software co-design approach
M Yan, X Hu, S Li, A Basak, H Li, X Ma, I Akgun, Y Feng, P Gu, L Deng, ...
Proceedings of the 52nd Annual IEEE/ACM International Symposium on …, 2019
602019
Characterizing and understanding GCNs on GPU
M Yan, Z Chen, L Deng, X Ye, Z Zhang, D Fan, Y Xie
IEEE Computer Architecture Letters 19 (1), 22-25, 2020
302020
Rubik: A hierarchical architecture for efficient graph neural network training
X Chen, Y Wang, X Xie, X Hu, A Basak, L Liang, M Yan, L Deng, Y Ding, ...
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2021
23*2021
Sampling methods for efficient training of graph convolutional networks: A survey
X Liu, M Yan, L Deng, G Li, X Ye, D Fan
IEEE/CAA Journal of Automatica Sinica 9 (2), 205-234, 2021
202021
fuseGNN: accelerating graph convolutional neural network training on GPGPU
Z Chen, M Yan, M Zhu, L Deng, G Li, S Li, Y Xie
2020 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 1-9, 2020
72020
Fast search of the optimal contraction sequence in tensor networks
L Liang, J Xu, L Deng, M Yan, X Hu, Z Zhang, G Li, Y Xie
IEEE Journal of Selected Topics in Signal Processing 15 (3), 574-586, 2021
62021
Survey on Graph Neural Network Acceleration: An Algorithmic Perspective
X Liu, M Yan, L Deng, G Li, X Ye, D Fan, S Pan, Y Xie
arXiv preprint arXiv:2202.04822, 2022
32022
Gnnsampler: Bridging the gap between sampling algorithms of gnn and hardware
X Liu, M Yan, S Song, Z Lv, W Li, G Sun, X Ye, D Fan
arXiv preprint arXiv:2108.11571, 2021
32021
Risc-nn: Use risc, not cisc as neural network hardware infrastructure
T Xiang, L Zhang, S An, X Ye, M Zhang, Y Liu, M Yan, D Wang, H Zhang, ...
arXiv preprint arXiv:2103.12393, 2021
22021
图神经网络加速结构综述
李涵, 严明玉, 吕征阳, 李文明, 叶笑春, 范东睿, 唐志敏
计算机研究与发展 58 (6), 1204-1229, 2021
22021
Multi-node Acceleration for Large-scale GCNs
G Sun, M Yan, D Wang, H Li, W Li, X Ye, D Fan, Y Xie
IEEE Transactions on Computers, 2022
12022
General spiking neural network framework for learning trajectory from noisy mmWave radar
X Liu, M Yan, L Deng, Y Wu, D Han, G Li, X Ye, D Fan
Neuromorphic Computing and Engineering, 2022
12022
Hardware acceleration for gcns via bidirectional fusion
H Li, M Yan, X Yang, L Deng, W Li, X Ye, D Fan, Y Xie
IEEE Computer Architecture Letters 20 (1), 66-4, 2021
12021
Balancing memory accesses for energy-efficient graph analytics accelerators
M Yan, X Hu, S Li, I Akgun, H Li, X Ma, L Deng, X Ye, Z Zhang, D Fan, ...
2019 IEEE/ACM International Symposium on Low Power Electronics and Design …, 2019
12019
Rethinking Efficiency and Redundancy in Training Large-scale Graphs
X Liu, X Xiong, M Yan, R Xue, S Pan, X Ye, D Fan
arXiv preprint arXiv:2209.00800, 2022
2022
Characterizing and Understanding HGNNs on GPUs
M Yan, M Zou, X Yang, W Li, X Ye, D Fan, Y Xie
IEEE Computer Architecture Letters 21 (2), 69-72, 2022
2022
Simple and Efficient Heterogeneous Graph Neural Network
X Yang, M Yan, S Pan, X Ye, D Fan
arXiv preprint arXiv:2207.02547, 2022
2022
HetGraph: A High Performance CPU-CGRA Architecture for Matrix-based Graph Analytics
L Tan, M Yan, X Ye, D Fan
Proceedings of the Great Lakes Symposium on VLSI 2022, 387-391, 2022
2022
Characterizing and Understanding Distributed GNN Training on GPUs
H Lin, M Yan, X Yang, M Zou, W Li, X Ye, D Fan
IEEE Computer Architecture Letters 21 (1), 21-24, 2022
2022
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